About the team 

A reliable, privacy-safe, and scalable data foundation is critical to Roku’s rapidly growing advertising business. The Ad Data Activation organization builds the identity systems, device graph pipelines, audience platforms, insights tooling, and data collaboration capabilities that power targeting, measurement, and reporting across Roku Ads. 

We are hiring a Senior Machine Learning Engineer to help drive intelligence across these systems. You will work at the intersection of large-scale data platforms, applied machine learning, and generative AI — building capabilities that make Roku's advertising data more actionable for internal teams and advertisers. This includes building core generative AI platform features for Roku Advertising, while also applying traditional ML techniques to improve accuracy, automation, and decisioning across the ecosystem. If you enjoy working across data, ML, and new Gen-AI patterns — and want to shape how intelligence shows up inside Roku Ads — this role is for you. 

About the role 

In this role, you will design, build, and productionize intelligent capabilities that combine agentic Gen-AI systems with conventional ML pipelines across identity resolution, audience modeling, attribution, and optimization workflows. You will work with massive datasets, develop pipelines that transform raw signals into actionable features, and partner closely with product, data science, and platform teams. 

What you will be doing 

• Develop scalable and effective ML models and data pipelines to power identity, graph enrichment, audience segmentation, and campaign performance intelligence 

• Design and run experiments, measure impact, and translate results into product decisions and customer outcomes 

• Build and productionize agentic, generative-AI features — including reporting and insights agents, campaign-monitoring agents (with human-in-the-loop controls), and a semantic layer for reliable, natural-language analytics 

• Improve automation, reliability, and scalability across model training, feature engineering, deployment, and monitoring frameworks 

• Work closely with software and ML engineers to deliver end-to-end solutions from data ingestion through downstream systems 

• Partner with senior stakeholders to shape ML and Gen-AI strategy for Ad Data Activation — identifying the right problems for AI, ensuring safety, and driving advertiser productivity. 

We’re excited if you have 

• 5+ years of experience applying ML or data science to real business problems at scale 

• Master’s degree (or higher) and 4+ years of experience in CS, CE, ML, or a related field 

• Strong CS fundamentals and ability to design efficient algorithms and production systems 

• Experience with ML approaches used in large-scale data problems (e.g., regression, classification, tree-based methods, embeddings, sequence models, or basic NLP) 

• Strong intuition for defining KPIs, objective functions, and evaluation frameworks for ML-driven systems 

PREFERRED QUALIFICATIONS 

• Knowledge of programming languages such as Python, Scala/Java, C/C++, or similar 

• Experience working with large-scale data platforms (Spark, Presto/Trino, feature stores, data lakes, etc.) 

• Experience building or integrating with LLM/Gen-AI pipelines (prompting, evaluation, retrieval, safety) is a plus 

• Prior publications, patents, or open-source contributions are a plus 

About the role  

Our Search Platform sits at the heart of the Roku experience, powering voice, text, and visual discovery across 100M+ active accounts and every Roku-powered device worldwide.
 We own the entire stack —from ingesting & enriching a multi-million-title knowledge graph, to low-latency retrieval services and large-scale machine-learning systems that personalize results in real time. Our work doesn’t just help users find shows; it drives core product surfaces (home-screen rows, browse hubs, Roku Voice, mobile app search) and fuels partner monetization. If you enjoy turning cutting-edge research into products used billions of times a day, you’ll thrive here.

Roku’s footprint has more than quadrupled in the past five years, and user expectations have leaped just as fast—think LLM-based query understanding, vector-DB retrieval, on-device models, and multimodal search (voice, text, image). We’re now rebuilding our relevance stack for the next decade, blending classic IR with generative-AI techniques. You will be a technical leader spearheading that transformation. 

What you'll be doing 

• Apply state of the art ML on search using techniques in deep learning, bandits, transformers, LLMs, causal inference, and optimizations to make our users more delighted and engaged on the platform 
• Run online AB tests and analyze them against the critical business KPIs 
• Collaborate with US engineering teams as well as cross-functional teams to translate business requirements into technical specifications 
• Nurture our ML ecosystem to make it withstand scale, developer velocity and future business shifts 
• Provide technical leadership to drive technical and ML roadmap for search ranking and monetization 
• Help recruiting new engineers. Interview, train, and mentor new team members 
  
  We're excited if you have 
  
  
• 7+ years of experience (or PhD with 5 years of experience) applying Machine Learning to concrete problems at large-scale in domains like recommendation or search or ads 
• Strong CS fundamentals. Should be able covert ideas to code with ease 
• Good understanding of machine learning fundamentals like classification, deep neural nets, and sequence-based models. Familiarity with modern NLP stack and multi-modal representation learning is a plus 
• We'd love to see that you've worked with big data systems (Spark, S3, and Airflow) and can program (Java, Scala, or Python)  
• Good understanding of system architecture 
• Experience in big data technologies and streaming architecture, data pipelines, etc. 
• MS in Computer Science, Statistics, or related field, but a Ph.D. in CS or related fields is preferred 
  
• AI literacy and curiosity.You have either tried Gen AI in your previous work or outside of work or are curious about Gen AI and have explored it. 

#LI-AK1

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team:

As we expand our product offering as well as our footprint internationally, our transfer pricing policies and documentation will be increasingly subject to scrutiny by governmental authorities. We are seeking an experienced Transfer Pricing Specialist to ensure Stripe is compliant with the ever-changing regulations that govern transfer pricing and to bring subject matter expertise to audit defense and resolution.   

What you’ll do:

The Transfer Pricing Specialist will be a hands-on team member, who works collaboratively across the organization to develop and execute compliant and practical transfer pricing policies and processes. This individual will be an excellent communicator, with the ability to explain transfer pricing concepts in a simplified fashion to non-tax people. The ideal candidate will have experience in a high-growth technology or financial services company partnering with various functional teams and other members of the tax department.

Responsibilities:

• Partner with teams within and outside of Finance to develop, execute, and maintain transfer pricing policies for Stripe’s current and future operating structure and product offerings with a strong moral compass and integrity.  
• Dive deep into financial information in order to design, prepare, and review detailed transfer pricing calculations.
• Assist in the preparation of legal entity forecasts and support the tax provision process.  
• Navigate the transfer pricing impacts of special projects related to restructurings, acquisitions, and corporate initiatives.
• Ensure operating models are fit-for-purpose in the context of evolving global tax frameworks and transfer pricing regulations. 
• Build relationships with technology and business leaders to gain a deep understanding of their organizational structure and activities and flex transfer pricing policies in response to changes therein;
• Assist finance and tax teams in government and regulatory audits. 
• Support Stripe’s participation in tax audits, advanced pricing agreements, and competent authority proceedings. 
• Prepare and maintain the company’s suite of transfer pricing documentation and compliance in accordance with OECD guidelines and local requirements, ensuring efficiency and quality across a subset of assigned jurisdictions.
• Build, and/or streamline, transfer pricing models for clarity, efficiency, and ease of use.

Who you are:

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum Requirements: 

• Bachelor’s or Master’s Degree (or above) in accounting, economics, business, law, or other related fields.
• 8 + years of relevant experience
• Robust knowledge of global transfer pricing laws and regulations.
• Experience with international tax planning for a multinational. 
• Experience managing transfer pricing documentation and compliance.
• Practical experience with various transfer pricing dispute resolution tracks, including audits and advanced pricing agreement / competent authority negotiations.
• Experience with developing, maintaining, and implementing intercompany agreements.
• Knowledge of financial accounting concepts including accounting for intercompany transactions.
• Excellent written, verbal communication and presentation skills coupled with strong interpersonal and team-building capabilities across different functional areas and cultures.
• Enjoys working with, and digging into, data from multiple sources.
• Professional experience in Excel, Oracle, Smartview.
• Curiosity, empathy, and humility.

Preferred qualifications: 

• An advanced degree or professional qualification in tax, accounting, economics or law (CPA, JD, LLM).
• Experience working in a high-growth, rapidly scaling environment.
• Industry experience at a multinational organization; experience working in technology, payments, or financial services is a plus.
• Professional experience in Alteryx and/or robotic process automation software.

At Stripe, our mission is to increase the GDP of the internet. We build the most powerful and flexible tools for running an internet business globally. We handle billions of dollars each year and enable millions of users around the world to scale faster and more efficiently by building their businesses on Stripe. Our tax team works with Stripes across the company to develop an efficient tax structure, as our international business scales and expands into new markets. We are looking for a well-rounded and seasoned tax professional to help us lead this effort.

This function will be responsible for the global Indirect Tax (VAT/GST) Compliance of our Stripe business. This includes building and implementing VAT/GST compliance processes and controls, supporting management, and working with our indirect tax advisory, systems & compliance leads on day to day matters, and much more.

The position will be based in Bangalore and report to the International Indirect Tax Lead.

Responsibilities

• Oversee and manage our global indirect tax compliance function ensuring compliance with VAT/GST, and other indirect tax obligations across multiple jurisdictions.
• Manage VAT/GST registrations across tax authorities.
• Management of indirect tax audits and other indirect tax matters involving tax authorities.
• Collaborate with the international indirect tax planning and advisory team, the international accounting teams and third party service providers on VAT/GST, assisting with the ongoing enhancement of the indirect tax compliance and control processes.
• Work with other tax team members and product and engineering teams to help define compliance requirements and collaborate on the design and implementation of VAT/GST controls. 
• Promote indirect tax awareness and knowledge including training and liaising with business and tax partners on changes to indirect tax legislation, systems, policies and processes.

We are looking for someone with: 

• 4-6 years of experience in global indirect tax compliance, with experience managing large-scale tax initiatives.
• Previous in-house experience within a multinational business and either legal or accountancy firm experience.
• Deep understanding of global indirect tax laws and regulations, including VAT and GST.
• Understanding of diverse business models and associated tax implications, including intercompany service entities and reseller arrangements.
• Exceptional time-management and project-management skills.
• Excellent verbal and written communication skills. You should be able to adjust your communication style based on your audience (users, product teams, advisors, etc.). 
• The ability to prioritize projects in a fast-changing environment.
• Tax qualification or experience.
• Experience in supporting internal and external audit queries.
• Cross functional experience, in particular with system engineers, international accounting, Tax, user support. 
• Systems experience (i.e Oracle AP/AR modules, Alterix, hubble queries). 

Preferred qualifications:

• An advanced degree or professional qualification (CTA/CPA, or equivalent, Masters in Tax, or LLM or equivalent) in tax, law or accounting.  
• Experience working in technology, payments, or financial services.
• Experience working in a high-growth, rapidly scaling environment.
• A willingness to work with a diverse crew of tax nerds who care deeply about Stripe’s tax issues and each other.

To apply please include the following:

• • LinkedIn profile and resume

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

We are experts in data, working to make it cost-effective, understandable, and trustworthy. We build pipelines processing billions of events a day and are stewards of canonical data warehouses and datasets delivering products for Stripe Users while embedding with teams to build their data products.  We are experts in using the Stripe Data Platform and to scale we lead the data culture and data education to enable product teams to own their data. We invest in [AI] Data Ops to scale incident handling and serve as an escalation path for data incidents to minimize their impact. The Data Engineering Solutions team will work closely with product teams delivering trustworthy data / backend code / and innovative (AI) tools/platforms/services for data.

What you’ll do

We're looking for a person who could drive the Data Engineering Solutions Team in solving high-impact, cutting-edge data problems. The ideal candidate will be someone that has built data pipelines for large scale volume, is deeply knowledgeable of Data Engineering tools including Airflow/Spark/Kafka/Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other Stripe teams to understand their use cases and unlock new capabilities.

You will:

• Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success.
• Partner with our recruiting team to attract and hire top talent.
• Deliver cutting-edge data pipelines that scale to users' needs, focusing on reliability and efficiency.
• Develop strong subject matter expertise and manage the SLAs of data pipelines and full stack web applications that support critical stakeholders.
• Collaborate with product managers and peers across the company to create/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data.
• Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems
• Have an opportunity to work with Spark, Flink, Kafka, Trino, Pinot, Airflow, Scala, Java, SQL, and Python and many other big data technologies.
• Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion.
• Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

We’re looking for someone who has: 

• 10+ Years of engineering experience with 5+ Years of hands-on experience building+operating data systems/pipelines, datasets/data warehouses, infrastructure, and leading small teams to deliver exceptional solutions.
• A strong engineering background and passion for data.
• Prior experience with writing and debugging data pipelines using a distributed data framework (Spark / Hadoop / Trino / etc)
• An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues
• Knowledge of a backend development language (such as Scala, Java, or Go) and strong SQL experience
• Extreme customer focus, with a commitment to partnering with Product Managers, leaders, and other Stripe engineers to understand their use cases.
• Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs.
• Thrive with high autonomy and responsibility in an ambiguous environment.
• Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment.

Preferred qualifications

• Expertise in Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, AWS Cloud, and influencing open-source contributions is a plus.
• Experience creating and maintaining Data Marts / Data Warehouses to power business reporting needs
• Experience working with Product or Go-To-Market (GTM - Sales/Marketing) teams
• Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions.
• Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide.

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

In this role, you’d be joining Stripe’s growing US State & Local Tax team. Our tax team works with Stripes across the company to develop an efficient tax structure, and we are looking for a well-rounded and seasoned tax professional to help us lead this effort.  This specific role will assist with a variety of US state sales tax compliance functions for Stripe and its many diverse offerings. 

What you’ll do

We are seeking an experienced State & Local Tax Compliance Specialist to build, improve, and maintain Stripe’s US indirect tax reporting and compliance function. This includes helping form and implement compliance processes, supporting management, and working with our indirect tax systems & compliance leads on day to day matters, and much more. You will work for a rapidly growing Company in a fast paced environment, while collaborating with numerous functional teams across our organization. You will be an excellent communicator, with the ability to explain tax technical concepts and requirements in a simplified fashion to non-tax people. 

The position will be based in Bangalore and report to the State & Local Tax Lead.

Responsibilities

• Ensure compliance with state and local sales tax rules, and other indirect tax obligations across the US.
• Manage US sales tax registrations across state and local tax authorities.
• Gather data for US sales tax audits and other indirect tax matters involving tax authorities.
• Collaborate with the international indirect tax planning team on the ongoing enhancement of the indirect tax compliance and control processes.
• Work with other tax team members and product & engineering teams to help define compliance requirements and collaborate on the design and implementation of US sales tax controls. 
• Promote indirect tax awareness and knowledge including training and liaising with business and tax partners on changes to indirect tax legislation, systems, policies, and processes.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements: 

• 4-6 years of experience in US indirect tax compliance, with experience managing large-scale tax initiatives.
• Previous in-house experience within a multinational business and either legal or accountancy firm experience.
• An understanding of US state and local indirect tax laws and regulations.
• An understanding of tax liability shifting models, including MoR (reseller), marketplace facilitator, and deemed seller.
• Exceptional time-management and project-management skills.
• Excellent verbal and written communication skills. You should be able to adjust your communication style based on your audience (users, product teams, advisors, etc.). 
• The ability to prioritize projects in a fast-changing environment.
• Previous experience in working with engineering teams in scoping and implementing tax compliance requirements.

Preferred qualifications:

• An advanced degree or professional qualification (CPA, JD or equivalent, Masters in Tax, or LLM or equivalent) in tax or law.  
• Experience working in technology, payments, or financial services.
• Experience working in a high-growth, rapidly scaling environment.
• A willingness to work with a diverse crew of tax nerds who care deeply about Stripe’s tax issues and each other.

To apply please include the following:

• LinkedIn profile and resume

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Support Experience engineering organization builds and improves Stripe’s user support from end to end: how users get help within our products, how they get in touch with us when they have questions, and how our teams use internal tools to answer those questions. We’re accountable for the quality and reliability of this support stack and we use data and firsthand experience to continuously improve it. 

Providing great support to users of all sizes is culturally important to everyone at Stripe. We partner closely with Stripe’s design, product, and operational teams across a wide surface area: the external-facing support interfaces (https://support.stripe.com/), self-serve content, entry points, internal tooling, case routing, and helping product teams across the company reduce support volume by improving our products. We are also using the latest generative AI technologies to re-imagine support experiences, and are developing AI assistants for Stripe’s users and to help our operations teams be more productive.

What you’ll do

You’ll lead and grow an established, high-performing engineering team within the Support Experience organization. Your job is to start with what’s been built and make it better: grow the team, elevate the technical bar, and expand the team’s impact across Stripe.

In this role, your team will build support experiences for priority user segments, solving problems such as how platforms, enterprises, and consumer users get help from Stripe. This includes implementing new API endpoints for use across multiple products, data engineering to improve our support operations with real-time insights, or building AI-enabled product experiences designed for each segment’s unique needs. You’ll lead your team to use the best tools for each job, whether that means experimental machine learning applications or proven techniques for building scalable distributed systems.

Responsibilities

• Hire, lead, and manage a team of talented engineers, providing mentorship, guidance, and support to ensure their success.
• Collaborate with cross-functional stakeholders, including product managers and designers, to understand customer needs and translate them into technical solutions.
• Define the technical vision and roadmap for the suite of products managed by the team, aligning it with business objectives and industry best practices.
• Drive the execution of projects, overseeing the entire development lifecycle from planning to delivery, while maintaining high standards of quality and timely completion.
• Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team.
• Stay up-to-date with emerging technologies, industry trends, and advancements in AI and customer experience practices to identify opportunities for improvement and innovation.
• Communicate effectively with stakeholders, providing regular updates on project status, progress, and any potential risks or challenges.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 3+ years of experience managing teams that build and operate full-stack web applications at scale, and 10+ years of overall industry experience
• A passion for supporting both external users and internal customers
• Successfully recruited and built great teams
• The ability to thrive with a high level of autonomy and responsibility
• The desire to encourage a healthy, inclusive work environment that’s both supportive and challenging
• Clear and persuasive writing and in-person communication

Preferred qualifications

• You have experience designing, deploying, and owning Agentic LLM solutions (e.g., multi-step orchestrators, tool use/function calling) specifically for complex customer support or internal workflow automation.
• You are comfortable planning in quarters, and can set a vision for several years
• You are excited about collaborating with teammates across Stripe’s organization to provide a wonderful support experience to users
• You are comfortable working with geographically distributed teams
• Experience managing multiple engineering teams

What You'll Do

At HG Insights, we run one of the most data-rich go-to-market environments in B2B SaaS. We're looking for a Senior AI GTM Automation Engineer who will sit inside our Sales Engineering and Solutions team and build the tools, integrations, and AI-powered workflows that make our Sales Engineers, Solutions Engineers, and Enterprise CSMs dramatically more effective.

This is a force-multiplier role. You'll embed with revenue teams, understand their daily jobs to be done, and turn manual, repetitive work into fast, reliable automations—so our best people spend their time on the work only humans can do.

Core Responsibilities

• Workflow discovery: Shadow and interview Sales Engineers, Solutions Engineers, and Enterprise CSMs to map their day-to-day workflows and build a prioritized automation backlog ranked by impact and effort
• Sales Engineering tools: Build data-assembly tools that pull from HG's APIs, automate technical discovery prep, and generate proof-of-concept materials—reducing manual pre-call and post-call work for SEs
• Solutions Engineering tools: Automate the generation of technical scoping docs, integration-architecture diagrams, and solution briefs; maintain a reusable library of solution templates and sandbox configurations
• Enterprise CSM automations: Build automations for account health briefs, QBR summaries, risk-detection alerts, and personalized outreach workflows using data from Vitally, Salesforce, and Slack
• AI-powered workflow engineering: Design and deploy LLM-based workflows using Claude and the Claude Agent SDK—building agents, MCP server integrations, and agentic pipelines that operate across the GTM tool stack
• Platform ownership: Maintain and evolve the internal GTM automation stack; document every tool so teams can self-serve; instrument monitoring so failures surface quickly

What We're Looking For

Experience

• 3–7 years in a technical role—software engineering, solutions engineering, RevOps engineering, or a closely related field
• Demonstrated track record of building internal tools or automations that eliminated manual work for a GTM or customer-facing team
• Hands-on experience integrating with SaaS APIs (Salesforce, Slack, HubSpot, Vitally, or similar)

Technical skills

• Expert-level user of Claude Code—you use it daily, understand its agentic capabilities, and can build production workflows with it
• Proficiency in Python and/or JavaScript/TypeScript for scripting, API integration, and automation
• Working knowledge of MCP (Model Context Protocol) servers and LLM-based agent frameworks
• Comfort with workflow automation platforms such as n8n, Zapier, or Make
• Familiarity with the GTM tool ecosystem: Salesforce, Vitally, Slack, Gong, Granola, Outreach, or equivalent

How you work

• Business mindset: You understand that tools are only valuable if people use them—you design for adoption, not just functionality
• Discovery-first: You run structured discovery sessions with non-technical stakeholders and translate fuzzy pain points into scoped, buildable solutions
• Ship fast, iterate often: You prefer a useful tool in users' hands over a perfect tool on a roadmap
• High reliability bar: If an automation breaks, the team loses trust—you build with monitoring and graceful failure in mind

Nice to have

• Experience working in or embedded with a Sales Engineering, Solutions Consulting, or Customer Success team
• Familiarity with HG Insights products and use cases—technology intelligence, installed-base data, or intent signals
• Prior experience building Claude-powered agents or working with the Anthropic API at a production level

Why HG Insights

We're the global leader in technology intelligence—the data that helps the world's best B2B sales and marketing teams find and close the right customers. This role offers an uncommon combination of technical depth and business impact: you'll define your own roadmap, work directly with the teams you're serving, and see your work reflected in real revenue outcomes.

We offer competitive compensation, equity, and a team that genuinely invests in your growth as an engineer and as a GTM thinker.

HG Insights is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

About the role

Hiring is one of the most consequential decisions a company makes. 3,000+ enterprises rely on HackerRank to get it right. We are now reinventing how that works for the agentic era. The ML systems that power this platform are not auxiliary features. They are the product.

Open Problems

The agentic era is reshaping every layer of the hiring stack. These are some of the core problems you'll be working across, none of them fully solved.

• Chakra: Building an autonomous AI interviewer that conducts, adapts to, and evaluates technical interviews end to end.
• Integrity: Detecting fraud and suspicious behavior across multiple signal types. The ways candidates game assessments change frequently, and the models need to keep up.
• Evaluation: Measuring technical skill in a world where AI writes the code. The old proxies no longer hold and the new ones have not been defined yet.

Your focus will shift across these depending on where the highest-leverage work is at any given time.

What you will do

• Design and ship production ML systems across Chakra, integrity, and evaluation domains.
• Own the full ML lifecycle: problem framing, data strategy, experimentation, deployment, and iteration.
• Build evaluation infrastructure and benchmarking pipelines that reliably measure model quality before and after deployment.
• Define the architecture and production bar for different signal categories from scratch. 
• Mentor and support junior ML engineers, helping shape their technical thinking and raise the quality bar across the team.
• Establish ML best practices for the team: monitoring, model feedback loops, and quality standards.

Who you are

• 4+ years building and shipping ML systems that run in production at scale.
• Systems thinking comes naturally. Model accuracy, data pipelines, serving infrastructure, and customer outcomes are one problem, not four.
• Evaluation methodology matters as much as model performance. A metric measured wrong is worse than no metric.
• Proficient in Python, with practical experience building data pipelines and deploying models to production.

Even better if you have

• Experience with multimodal systems: vision, NLP, audio, or behavioral signal pipelines.
• LLM experience: fine-tuning, RLHF, or multi-turn agentic systems.
• Background in adversarial ML, fraud detection, or anomaly detection.
• Publications or open-source contributions in detection, robustness, or evaluation methodology.

You will thrive here if

• Messy, undefined problems are more interesting to you than optimizing within clean ones.
• Ambiguity energizes you, especially when the right framing is itself part of the work.
• Direct access to leadership, fast feedback loops, and genuinely unsolved problems is what you are looking for.
• Defining what a system should be is more compelling than maintaining what already exists. 

Role

We are looking for a Senior Threat Researcher to join our Threat Detection Group within ThreatLabz. This is Hybrid role, reporting to a leader in ThreatLabz Team . You will track the evolving threat landscape, analysing emerging threats and identifying TTPs to develop critical detection and protection signatures. As part of our world-class research arm, you will ensure millions of global users remain protected through advanced malware research and behavioural analysis.

What you’ll do (Role Expectations)

• Analyse browser-based threats, including HTML smuggling and phishing, to develop robust protections

• Research vulnerabilities across OWASP, Web API, and LLM Top 10 to author prevention signatures

• Conduct static and dynamic malware analysis to mitigate emerging threats and C2 frameworks

• Develop complex automation tools and prototypes to integrate research findings into Zscaler products

• Contribute to the global security community by publishing in-depth threat analysis blogs and research papers

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.

• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.

• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.

• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.

• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

• 2+ years of dedicated experience in Cyber Security Research with expertise in web attack and DOM/JS analysis

• Proficiency in browser security and analysing/deconstructing payloads within browser environments

• Hands-on experience with malware debugging and reverse engineering using tools like IDA, x64dbg, or Ollydbg

• Strong understanding of TCP/IP, Application layer protocols, and vulnerabilities across OWASP and LLM Top 10

• Experience with automation scripting in Python, Ruby, Go, or Shell to synthesise threat intelligence

What Will Make You Stand Out (Preferred Qualifications)

• Professional security certifications such as OSCP or specialised degrees in Computer Science or Information Technology

• Proven ability to implement AI-powered automation and leverage GenAI models for threat research

• Advanced reverse engineering experience specifically related to file-less threats and complex exploit techniques

#LI-Hybrid

#LI-RG

Role

We are looking for an experienced Staff Machine Learning Engineer to join our Engineering team. This role is based in Hyderabad, reporting to the Senior Director, Engineering. You will be responsible for building and maintaining large-scale distributed systems that power our entire ML pipeline, from data collection to real-time serving. You’ll solve complex real-world business problems by partnering closely with data scientists and product teams to deliver impactful automation and intelligence. You will also help design and build Agentic AI systems—developing and orchestrating specialized agents to automate and scale ZPA segmentation workflows, from signal ingestion and reasoning to policy recommendations and enforcement validation.

What you’ll do (Role Expectations)

• Build and maintain large-scale distributed systems to support the whole pipeline including data collection, feature engineering, model training, model evaluation, model deployment, and real-time serving—including Agentic AI components (agent workflows, orchestration, tool integrations, and real-time agent serving).
• Develop functional specifications, assess task requirements and scheduling, and participate in the development, debug, and support—including designing agent behaviors, evaluation strategies (quality/safety/latency), and rollout/monitoring plans for agent-based systems.
• Solve complex real-world business problems like threat detection and business intelligence by working closely with stakeholders including data scientists, product management, and product engineering teams—including building multi-agent solutions that automate analysis and decisioning (e.g., recommendation, triage, and segmentation/policy workflows).

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.
• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.
• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.
• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

• 4+ years of experience as a AI-ML Engineer
• Experience with applying machine learning for improving key business metrics, optimized models for accuracy, latency
• Experience with researching newer techniques, and innovating for building ML based solutions
• Experience with algorithms in building out data collection/processing infrastructure, Machine Learning model training, and serving platforms
• Expertise in leveraging and augmenting LLM models for software development

What Will Make You Stand Out (Preferred Qualifications)

• Proven track record of designing, building and shipping end-end applications at scale
• Experience identifying and solving problems in data using machine learning systems
• Familiarity with multi-agent systems, agent architectures, prompt engineering and SOTA AI frameworks

#LI-Hybrid #LI-AN4

Role

We are looking for an experienced Escalation Engineer to join our Customer Success team.  This is a hybrid role based in Bangalore, you will report to the Escalation Manager. Our Customer Success Strategy & Operations team uses valuable data and market research to help our customers succeed and drive value. You'll be an integral part of solving challenges faced by our client-facing teams to help make Zscaler more efficient in meeting our customers' needs.

What you’ll do (Role Expectations)

• Own and resolve the highest-severity technical escalations through deep analysis, ensuring fast resolution and managing the on-call rotation for critical issues

• Troubleshoot and resolve complex issues across Zscaler cloud security services, configuration, policy engines, APIs, and AI-assisted capabilities

• Investigate and resolve scenarios related to the secure use of AI models, governance of AI agents, data protection, and inference security

• Perform detailed log, telemetry, and packet-level analysis to identify the root cause, reproducing complex defects, providing engineering-ready bug reports, and validating fixes

• Drive cross-functional collaboration with Engineering, Cloud Ops, and Product Management, while also creating advanced troubleshooting documentation and acting as a technical mentor to uplift support capability

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.

• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.

• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.

• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.

• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

• 4–10 years of deep technical support, cloud support engineering, or escalation engineering experience

• Strong understanding of AI model security, data governance, AI agent behavior, and safe enterprise deployment principles

• Proficiency with APIs, JSON, logging frameworks, Linux CLI, debugging tools, and cloud-based distributed systems

• Exposure to cloud platforms (AWS/GCP/Azure) and identity, policy, or proxy-based architectures

• Ability to reproduce complex issues, correlate across layers (client → edge → cloud), and articulate clear RCAs

What Will Make You Stand Out (Preferred Qualifications)

• Demonstrated experience with Zscaler products (ZIA, ZPA, ZDX) or similar cloud security platforms, including knowledge of enterprise networking, TLS/SSL inspection, and authentication flows

• Familiarity with LLM-based system behavior, data leakage prevention in AI, and establishing model access policy controls

• Proficiency in scripting for automation, efficient troubleshooting, and reproducing complex customer environments

#LI-RR

#LI-Hybrid

We're seeking a Head of Machine Learning to own and scale the ML function at Prodigal. This is the senior-most ML role in the company — partnering directly with the CTO as a peer technical leader, defining the multi-year ML vision, building and leading a world-class team, and translating cutting-edge research into production systems that move the needle for over 100 customers and millions of consumers. You'll set the bar for technical excellence, hire and develop the next generation of ML leaders, and shape what consumer finance intelligence looks like over the next decade. If you've operated at this level before — or are ready to step into it at a company where ML is the engine of the product — we want to talk.

Responsibilities:

• Own the ML function end-to-end — vision, roadmap, team, delivery, and measurable business impact across classical ML, NLP, GenAI, and Agentic AI
• Partner with the CTO as the senior ML leader to set company-wide technical direction and shape the long-term roadmap for Prodigal's Intelligence Engine
• Build and lead a high-performing ML organization — hire, mentor, and develop ML engineers, applied scientists, and tech leads across multiple pods
• Translate research into product — drive the application of LLMs, Agentic AI, the modern NLP stack, recommendation systems, and classical ML into production systems serving 100+ customers
• Set technical standards for model development, deployment, monitoring, evaluation, and experimentation that scale across the org
• Architect data and ML infrastructure in partnership with the platform and engineering teams to support large-scale training and reliable, low-latency inference
• Communicate strategy and outcomes clearly to the founders, board, customers, and broader engineering organization
• Represent Prodigal externally — at conferences, in research collaborations, and as a senior voice in the consumer finance AI community
• Stay at the frontier of ML and GenAI research, identifying where new techniques unlock product and business advantage
• Collaborate cross-functionally with product, engineering, GTM, and customer success leaders to ensure ML investment ties directly to revenue, retention, and customer outcomes

Requirements:

• 10+ years of experience in machine learning and software development at a tech or product company, with 4+ years leading ML teams (managing engineers and/or tech leads)
• Proven track record of shipping ML products in production at scale with measurable business impact
• Deep technical fluency across classical ML, deep learning, and the modern NLP/LLM stack — you can still go deep in design reviews, not just review at the surface
• Strong coding skills in Python. Hands-on with PyTorch, scikit-learn, Pandas, and Spark
• Demonstrated success hiring, mentoring, and growing ML talent — including team leads and senior engineers
• Strong executive communication and the ability to set technical direction with founders, peers, and the board
• A bias for outcomes — you connect model work to revenue, engagement, and operational metrics

Preferred Qualifications:

• Experience as a founding ML hire, ML lead, or applied science leader at a high-growth AI/ML product company
• Background in voice AI, conversational AI, speech, NLP on unstructured text, or fintech/lending domains
• Experience with cloud services (AWS), Databricks, and building scalable, distributed systems
• Track record of running A/B testing and experimentation programs at scale
• Patents, publications, or open-source contributions; strong institutional pedigree (IIT, BITS, NIT, IISc)
• Experience scaling an ML org through a hypergrowth phase

Job Benefits

• GenAI at the core – Lead the ML function at a company where AI isn't a feature, it's the product. Shape groundbreaking work that redefines consumer finance intelligence.
• World-class team - You'll get the chance to learn from (and teach) some of the brightest and most skilled people you'll ever meet. Our team members have been part of BCG, Deloitte, EY, Blackstone, Meta, Amazon and are IIT, IIM, BITS alumnus.
• Continuous education - As relentless seekers of knowledge, we sponsor and support any training materials, books, courses, and exam fees for upskilling yourself in areas related to your role - but that's not where it ends. If you make a good case for some extra learning, we're delighted to foot the tab.
• Food at the office – Meals are on us. We won't let your stomach grumble while you hustle.
• Health insurance - Health always comes first. The health of your family is as important to us as it is to you. We offer insurance coverage for both you and your family.
• Flexible schedule - We're not a "clock in, clock out" company. Morning person? Start work while the world's still sleeping. Night owl? Ramp things up while others are winding down. You're fully trusted to create the right conditions for your own personal peak productivity. We only ask that you be available to your teammates for seamless collaboration.
• Generous leave policy - Take all the time you need to recharge your batteries - no cap on vacation here. Because a rested, relaxed, and refreshed mind is a happy and effective mind.
• Recreation & team activities – We regularly indulge in friendly football, table tennis, cooking sessions, and challenge each other to do those extra push-ups or chug that 4th drink (of course, that's Nimbu Pani).

Meet Sangram (Cofounder and CTO) and hear his vision for Prodigal: https://www.youtube.com/embed/FTWlN9fwiIA?feature=shared

As a Senior AI/ML Engineer in our AdTech team, you will be a hands-on individual contributor building and deploying machine learning models and AI-driven features for our advertising platform. You will partner with engineering, product, and data science to deliver production-grade ML for campaign optimization, user personalization, and creative intelligence—operating at large scale and low latency across billions of ad events per day. You will contribute to modern ML/LLM capabilities and agentic workflows that automate and enhance campaign operations, with a strong focus on reliability, performance, and measurable business impact.

Key Responsibilities

• Machine Learning Delivery: Design, implement, and ship scalable ML solutions for core AdTech use cases (targeting, ranking, pacing, measurement). Own features end-to-end from experimentation to production rollout.
• ML System Design: Build and evolve the ML lifecycle—data preparation, training, evaluation, and real-time inference—ensuring models integrate cleanly with ad serving systems and meet low-latency, high-throughput requirements.
• Technical Contribution: Contribute to the AI/ML technical roadmap by evaluating tools and techniques (including deep learning, LLMs, and retrieval/feature systems). Make pragmatic trade-offs with an eye toward maintainability and operational excellence.
• AI & Agentic Applications: Develop and integrate LLM-powered features and agentic workflows that assist with campaign workflows such as audience insights, bid/budget recommendations, and creative generation—within well-defined guardrails.
• Cross-Functional Collaboration: Work closely with engineering, product, and data science partners to translate marketing objectives into ML-driven solutions, define success metrics, and deliver iterative improvements.
• Performance & Reliability: Operate ML services in a high-concurrency, latency-sensitive environment. Optimize inference paths, implement monitoring/alerting, manage model drift, and ensure safe deployment practices (A/B testing, canaries, rollbacks).
• Mentorship & Best Practices: Mentor and support other engineers through code/model reviews and knowledge sharing. Champion engineering rigor in testing, observability, documentation, and reproducible ML workflows.

Required Qualifications

• 5+ years of experience in software engineering and/or applied machine learning, with a track record of shipping ML systems to production.
• Experience designing and building high-throughput, low-latency services or data pipelines for large-scale applications.
• Working knowledge of the programmatic advertising ecosystem (DSP/SSP/RTB) is a plus; strong adjacent experience (recommendation, ranking, marketplaces) is also valued.
• Proficiency in at least one of Java, Go, or Python for backend services and ML tooling.
• Hands-on experience with ML frameworks (PyTorch or TensorFlow) and common modeling approaches (classification, ranking, embeddings, deep learning).
• Experience with big data and streaming frameworks (e.g., Spark, Kafka) for processing and analyzing large datasets.
• Experience deploying ML to cloud environments (preferably AWS) and operating services at scale.
• Familiarity with data stores (SQL/NoSQL) such as PostgreSQL/MySQL, Cassandra/DynamoDB, Redis, etc.
• Familiarity with containerization/orchestration (Docker, Kubernetes) and CI/CD practices.
• Strong communication skills and ability to collaborate across disciplines; comfort explaining technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications

• Experience with Large Language Models (LLMs) and generative AI applied to advertising (e.g., ad copy generation, creative optimization, or personalized messaging).
• Experience designing and implementing agentic workflows that support autonomous or semi-autonomous decision-making with strong safety/observability guardrails.
• Experience with model serving and optimization for real-time inference (latency-critical environments).
• Familiarity with modern data lake and table formats (e.g., Apache Iceberg, Apache Hudi) for managing large-scale analytical datasets.
• Knowledge of microservices architecture and event-driven design patterns in distributed systems.
• Contributions to open-source projects, publications, or speaking engagements that demonstrate thought leadership in AI/ML are a plus.

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

App Framework Team • 80% Backend / 20% Frontend • 8+ Years

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that unifies identity, intelligence, and omnichannel activation into a single platform – powered by trillions of consumer signals and one of the industry’s largest proprietary databases. Our enterprise clients use the Zeta Marketing Platform (ZMP) to personalize experiences at the individual level across every channel.

The App Framework team is building something foundational: an Agentic App Builder platform on top of ZMP that enables teams across Zeta to develop, deploy, and operationalize applications that integrate with ZMP’s core capabilities – identity, intelligence, activation, and measurement. Think of it as the platform that powers the next generation of applications at Zeta, with AI and agentic workflows built into the development experience itself.

As a Lead Full Stack Engineer, you’ll shape the architecture of this platform from the ground up. You’ll partner with product owners and engineering teams across the organization to understand what application builders need, design the backend services and APIs that make it possible, and build the frontend experiences that make it intuitive. You’ll own what you build end-to-end – from requirements through production operations – with a focus on architectural simplicity, developer experience, and operational excellence.

We develop using AI-assisted workflows (Cursor, Claude Code) and ship through continuous delivery. This is a rare opportunity to build a platform that fundamentally changes how applications are created at an enterprise scale.

What you’ll Do:

• Design and build the Agentic App Builder platform – the services, APIs, and developer tools that enable teams to create, deploy, and manage applications on top of ZMP fast and at scale.
• Build intuitive frontend experiences in React/TypeScript that make the platform accessible and productive for application builders.
• Ship continuously and confidently through CI/CD, with observability, resilience and reliability built in from the start.
• Embed AI/LLM capabilities into the platform to enable agentic application development and intelligent automation.
• Use AI-assisted development tools as a core part of your workflow to accelerate delivery while maintaining high quality.
• Collaborate with teams across Zeta to gather requirements, align on integration patterns, and ensure the platform meets real-world application needs.
• Mentor engineers, lead technical initiatives, and help establish the engineering practices and standards for the platform.

What We’re Looking For:

8+ years of software engineering with a track record of building and operating platform-level systems. You’re deeply proficient in at least two of Python, Java, Ruby, or Node.js, with solid React/TypeScript skills on the frontend. You understand what it takes to build developer-facing platforms in the age of AI.

You bring hands-on experience with AWS services and you’re comfortable operating in multi-tenant, compliant environments. Continuous delivery, test-driven development, and agile are disciplines you practice with conviction. You’re already using AI-assisted coding tools and you’re excited about building platforms that leverage agentic workflows.

You’re a strong communicator who thrives on cross-team collaboration. You enjoy working with product owners to define problems, proposing architectures, building alignment, and then delivering. You bring energy and curiosity to your work, and you elevate the people around you.

Nice to Have:

• Experience building agentic developer platforms, internal tooling, or app builder/low-code systems.
• MarTech or AdTech domain knowledge (DSPs, bid stream processing, data-intensive platforms).
• Familiarity with our data stores: MySQL, Snowflake, Aerospike, DynamoDB, S3.
• Experience designing plugin architectures, SDK/API frameworks, or extensible platform systems.

Tech Stack:

Why You’ll Love It Here:

• Build a foundational platform that shapes how every application at Zeta gets created – high-impact, high-visibility work from day one.
• AI-native engineering culture – agentic development is how we build, and you’ll be building the platform that brings it to others.
• Real ownership and autonomy. We trust our engineers to make great decisions and give them the space to do it.
• Collaborative, low-ego team that genuinely enjoys working together and learning from each other.
• Public company (NYSE: ZETA) with strong growth, competitive compensation, equity, and comprehensive benefits.

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

AI Foundations is Toast's internal platform team for AI. We build the infrastructure, governance, and developer tooling that makes AI a reliable, scalable force multiplier across the entire product development lifecycle. Our products include the LLM Proxy, AI Key Management, Observability pipelines, the Claude Plugin Marketplace, and autonomous agents that participate directly in the software development lifecycle.

As a Senior Software Engineer on this team, you'll be hands-on building the systems that other Toast engineers depend on every day: the LLM proxy, agentic workflows, and the plugin marketplace that brings AI-native development practices to teams across the company.

This is a hybrid role with 2 days per week in the Bengaluru office.

A day in the life (Responsibilities)

• Design, build, and ship features across AI platform infrastructure, including the LLM proxy, AI key management, and observability pipelines
• Develop and extend autonomous agents that participate in the SDLC, such as the AI Review GitHub App and Developer Platform MCP integrations
• Build on and contribute to the internal plugin marketplace, developing plugins that encode Toast's architectural standards and quality practices into AI assistant behavior
• Implement MCP (Model Context Protocol) services and service templates that make it faster and easier for teams across Toast to build AI-powered workflows
• Write high-quality, well-tested code and participate in design and code reviews
• Collaborate with engineers, product managers, and platform teams to understand developer needs and translate them into reliable platform solutions
• Contribute to the team's adoption of agentic development practices and tooling
• Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.

What you'll need to thrive (Requirements)

• Bachelor’s Degree with relevant experience of 5+ years in designing and implementing scalable backend services
• Demonstrated experience building, deploying, or operating LLM-powered agents or AI-assisted developer tooling
• Familiarity with AI coding assistants (e.g., Claude Code, Cursor, GitHub Copilot) and an interest in extending them through custom plugins, skills, or hooks
• Experience with MCP (Model Context Protocol), tool use patterns, or similar agentic integration frameworks
• Working knowledge of prompt engineering and how LLM behavior responds to context and instructions
• Strong foundation in Java, Kotlin, or another object-oriented language
• Experience with distributed systems, REST APIs, and cloud-native infrastructure
• Strong customer empathy and a drive to make developers' lives better through reliable, well-designed platform solutions

What will help you stand out

• Familiarity with A2A (Agent-to-Agent) protocols and multi-agent orchestration patterns
• Experience with machine learning concepts, model evaluation, or ML infrastructure
• Experience building developer experience platforms, internal tooling, or API gateways
• Familiarity with observability tooling for AI/LLM systems (e.g., Langfuse, DataDog)

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy 
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

#LI-HYBRID

Secure Every Identity, from AI to Human

Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

Okta seeks a skilled Staff Full Stack Engineer with expertise in NetSuite and/or  Oracle Fusion Cloud Applications. As part of our Business Technology team, you will be responsible for developing and optimizing full-stack solutions, including custom scripts, workflows, integrations, and system enhancements for both NetSuite and Oracle Fusion to improve business processes and scalability. This role will report to the Manager in Bangalore, India. We’d love to hear from you!

Job Duties and Responsibilities

• Design, develop, and maintain full-stack solutions for Finance Tech stack like NetSuite, Coupa and Oracle Fusion Cloud Applications etc., using any of the full-stack applications like Node Js/React
• Develop and maintain robust off-platform integration scripts using Python & LangChain to manage data transfer and interactions between NetSuite (via SuiteTalk or RESTlets) and AI Platforms
• Architect and implement scalable, secure, and cost-efficient cloud-native solutions on AWS for RAG, MCP, and Agentic AI (LangGraph) 
• Closely work with the BT Product Manager to design, develop, test, implement & support system solutions primarily in Finance Technology
• Provide technical consultation, best practices, and problem resolution for AI and Agentic AI for the Finance tech stack NetSuite, Oracle Fusion, and associated integrated systems
• Support & resolve production issues across the full application stack
• Develop and maintain integrations with third-party applications via REST/SOAP APIs
• Design and implement custom Generative AI solutions using the SuiteScript Generative AI API for practical NetSuite use cases and explore similar capabilities in Oracle Fusion

Required Skills:

• 9+ years in Python and its libraries (e.g., Pandas, Boto3) for data manipulation, ETL processes, and developing serverless functions to interact with foundational AI services on platforms like AWS Bedrock.
• Deep hands-on experience with AWS solutioning, including designing and deploying production applications using core services such as AWS EC2, AWS Lambda, Amazon S3, Amazon RDS, and API Gateway. Familiarity with Infrastructure as Code (IaC) tools like CloudFormation or Terraform is essential.
• Proficiency in NetSuite development experience (SuiteScript, SuiteFlow, SuiteTalk).
• Experience with SuiteCloud tools, REST/SOAP APIs, and third-party integrations.
• Experience with the SuiteScript Generative AI APIs to integrate LLM capabilities for advanced scripting solutions
• Strong understanding of Finance Business processes (Order Management, Billing, Vendor bill, etc.).
• Proficiency in JavaScript, SQL, and related web technologies
• Configure NetSuite modules to align with business needs, including leveraging Prompt Studio to customize and manage NetSuite AI functions like Text Enhance.
• Ability to drive and architect solutions with other developers, focusing on maximizing the value of embedded NetSuite AI capabilities
• Working Experience on the MCP and familiar with SaaS MCP connectors, like NetSuite MCP or similar
• Working experience with foundational AI services, with a desire to use a unified platform like AWS Bedrock for Generative AI development and deployment
• Nice to have some core Amazon Machine Learning (ML) services, specifically AWS SageMaker (for building, training, and deploying custom ML models), AWS Comprehend (for natural language processing and text analytics), and  Retrieval Augmented Generation (RAG)

Education and Certifications

• A Bachelor’s degree in Computer Science, Information Systems, or equivalent years of industry experience
• AWS cloud Certification or any ERP foundation certificate is a plus

#P16568_3435773
#LI_Hybrid

See yourself at Twilio

Join the team as Twilio’s next Senior Offensive Security Engineer

About the job

This position is needed to The Senior OffSec Engineer will be responsible for the day-to-day execution of penetration tests and contributing to larger Red Team campaigns. You move beyond simple scanning to manual exploitation and are beginning to automate your workflows.  

Responsibilities

In this role, you’ll:

• Full-Stack Penetration Testing: Perform manual and automated testing of web applications, APIs, and mobile apps (iOS/Android).
• Internal/External Network Audits: Conduct network and cloud level assessments with various tooling
• Vulnerability Validation: Triage and validate reports from automated scanners or bug bounty hunters to eliminate false positives and escalate true positives
• AI/LLM Probing: Perform initial prompt injection and jailbreak tests on AI prototypes, services, and applications using established checklists (OWASP Top 10 for LLMs).
• Technical Reporting: Draft high-quality reports that detail the "path to compromise" with clear, reproducible steps for developers.
• Tool Maintenance: Manage and update the team's testing infrastructure (e.g., Burp Suite, and basic C2 listeners).
• Remediation Support: Provide direct technical guidance to engineering teams on how to patch vulnerabilities like XSS, SQLi, and IDOR.
• Adversary Emulation: Design and lead multi-week Red Team operations that mimic specific threat actors (APTs) to test the SIRT detection capabilities.
• Custom Exploit Development: Build custom payloads, droppers, and obfuscated scripts to bypass EDR/AV and maintain stealth.
• AI Red Teaming Architecture: Build automated testing frameworks for AI systems (e.g., using PyRIT, Promptfoo, or Garak) to test for models related to sensitive data leakage.
• Cloud & Infrastructure Attacks: Execute sophisticated attacks against AWS/Azure/K8s, focusing on IAM misconfigurations and container escapes.
• Purple Teaming: Collaborate with SIRT and Detection Engineering to tune SIEM alerts based on the techniques used during an engagement.
• Strategic Bug Bounty Management: Oversee the organization's bug bounty program, identifying trends in submissions to suggest broad architectural security changes.

*Required:

• Experience: 3–5 years in offensive security, penetration testing, or a high-volume bug bounty background and track record of finding high/critical vulnerabilities in complex environments.
• Concepts: Expert Knowledge and  solid understanding of the MITRE ATT&CK matrix and the OWASP Top 10 for web applications and top 10 for LLMs, post exploitation (lateral movement, persistence, data exfiltration) and Adversarial ML.
• Tooling: Proficient in Burp Suite professional, Nmap, Metasploit, Wireshark etc... and AI security tools such as LangChain, TensorFlow for adversarial testing, as well as use of C2 frameworks (Cobalt Strike, Sliver, Havoc) or similar tools
• Scripting and Coding: Ability to write functional scripts in Python or Bash to automate repetitive testing tasks and proficiency in Python, C++, and scripting for creating custom offensive tooling that avoids signature-based detection.
• Certifications: Possession of advanced industry certifications such as OSCP, OSEP, OSWE, GXPN or similar
• Telecom expertise is preferred

Location

1. This role will be remote, and based in India. (Karnataka, Tamil Nadu, Telangana, Maharashtra, Delhi)

Travel 

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

This new team will architect the platform foundation and infrastructure that enables a "build once, run anywhere" model, ensuring our AI-powered modernisation suite operates seamlessly regardless of a client's security or network constraints. We are looking for engineers to join this high-visibility initiative, where you will solve unique distributed systems puzzles and help shape the future of how global enterprises leverage GenAI.

We are looking for an experienced software engineer who thrives on solving infrastructure constraints and building enterprise facing platforms. 

The ideal candidate is a hands-on technical leader who can architect complex distributed systems, mentor engineers, and collaborate with product teams to deliver a platform that minimizes deployment friction and meets customers’ compliance requirements.

This role can be based out of our Gurgaon office or Remotely in India.

The ideal candidate for this role will have

• 8+ years of software development and operations experience, with a focus on building platforms and distributable software infrastructure.
• 2+ years of experience leading, coaching, and mentoring a team of engineers to achieve high-impact results.
• Deep experience designing distributable applications that run in air-gapped or highly restricted network environments.
• Strong proficiency in containerization and orchestration, with the ability to design systems where the host executes containerized applications under strict security monitoring.
• Experience building Service Host architectures that provide shared routing, proxy layers, and API gateways for multiple underlying services.
• Experience managing persistent storage solutions (blob/file storage) within distributed systems.
• Understanding of security-first design, specifically regarding the execution of untrusted code, fine-grain access control, and rigorous input validation.
• Experience designing auto-update mechanisms for software that cannot directly access the public internet.
• Curiosity, a positive attitude, and a drive to continue learning.

Position Expectations

• Provide technical leadership and mentorship to a team of engineers, fostering a culture of innovation, quality, and continuous improvement.
• Drive the distributed infrastructure for the Application Modernisation Platform, ensuring it supports a self-service SaaS product model while operating within client-controlled environments.
• Lead the design and implementation of a sophisticated orchestration layer that manages authentication, telemetry, and the lifecycle of modernization tools.
• Architect a client-side application that manages developer workflows and communicates securely with hosted services.
• Solve complex "Day 2" operations challenges, such as designing interfaces to solve DevOps challenges to manage users, secrets, and updates.
• Collaborate with security and product teams to ensure the platform can execute code generation and LLM-based tasks securely, protecting both client data and MongoDB IP.
• Act as a hands-on leader, guiding the team through technical challenges related to container security, local vs. hosted logic distribution, and cross-service data sharing.

Success Measures

Within the first three months, you will have:

• Fully ramped up on our architecture, business domain, and the specific constraints of deploying software to large enterprise client environments.
• Established yourself as the technical leader within the team, actively driving technical decisions.
• Begun mentoring team members and collaborating with product counterparts to define the integrations between the platform and the tools it hosts.

Within six months, you will have:

• Successfully led the team to deliver a prototype or initial release of the Deployment Platform that supports the core modernization toolset.
• Designed and implemented a streamlined process for platform updates that works within client security constraints.
• Established a precise rhythm of execution and served as a role model for a high-performing team.

Within 12 months, you will have:

• Become recognized as the go-to technical expert for the deployment and operations domain at MongoDB.
• Delivered a stable, production-ready platform that allows our Field Engineering teams to deploy tools without significant delays or approvals.
• Played a crucial role in helping recruiting and growing the engineering team.

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

At Ensono, our Purpose is to be a relentless ally, disrupting the status quo and unleashing our clients to Do Great Things!  We enable our clients to achieve key business outcomes that reshape how our world runs. As an expert technology adviser and managed service provider with cross-platform certifications, Ensono empowers our clients to keep up with continuous change and embrace innovation.

We can Do Great Things because we have great Associates. The Ensono Core Values unify our diverse talents and are woven into how we do business. These five traits are the key to achieving our purpose:

Honesty, Reliability, Curiosity, Collaboration, and Passion.

About the role and what you'll be doing: 

Ensono’s Corporate Legal team has opened a position for a Corporate Counsel. This position is responsible for providing legal support and guidance to many of the function areas of the business. This position requires broad exposure to corporate legal matters and for maintaining operations required by law. This role reports to the Associate General Counsel – Corporate. We are looking for a talented individual with initiative and drive, with great attention to detail and ability to follow through.

Primary Responsibilities:

·       Work with the guidance of the Associate General Counsel – Corporate, providing legal counsel in support of tactical and strategic business initiatives.

·       Effectively handle assigned legal activities for various business units, functions or legal practice areas (including HR, Immigration, Finance, Tax, IT and other corporate functions).

·       Structure, draft, review and execute key corporate documents.

·       Assist in drafting, coordinating and managing all activities supporting Ensono’s Board of Directors.

·       Support and assist all corporate transactions (including mergers and acquisitions) and integrate activities.

·       Assist on trademark and patent related workstreams

·       Research, understand and evaluate different risk factors regarding business decisions and operations.

·       Develop and modify practices, policies and procedures to conform with business requirements and maintain compliance with applicable laws and regulations.

·       Remain current of laws and regulations and emerging legal risks. Work with legal counsel globally to remain abreast of regulatory requirements

·       Ensure adherence to all company policies and procedures.

·       Assist with planning and maintaining records relating to corporate matters

·       General support for the department including engaging legal counsels as appropriate and processing payments.

·       Perform other duties as assigned.

We want all new Associates to succeed in their roles at Ensono. That's why we've outlined the job requirements below. To be considered for this role, it's important that you meet all Required Qualifications. If you do not meet all of the Preferred Qualifications, we still encourage you to apply. 

What You Will Need:

•  Understanding of corporate legal principles, concepts, practices, and standards.

• Excellent interpersonal skills and ability to communicate effectively both orally and in writing with employees and external contacts (including outside counsel).

• Ability to work well under constantly changing deadlines and priorities in a fast-paced environment.

• Critical analysis skills related to identifying and solving problems in a busy corporate environment.

• Experience working with and training non-legal colleagues.

• Experience driving continuous improvement in processes and performance

• .Excellent attention to detail.

• Strong organizational and time-management skills.

• Ability to perform complex tasks with minimal direction and/or supervision.

• Self-starting and solutions-oriented team player.

• Maintains composure during tight deadlines.

• Ability to manage multiple tasks simultaneously.

Requirements:

• Law graduate (LLB/LLM)

• 2-3 years' proven experience in a related field (prior experience reviewing contracting, entity management work, mergers and acquisition/private equity experience in a corporate legal department a plus)

• Experience at a large law firm (plus) / or as in-house counsel required

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to caste, colour, creed, religion, gender, gender identity, sexual orientation, age, disability, HIV status, or any other status protected by law. Candidates with disabilities who require accommodations during the recruitment process are encouraged to contact our Talent Acquisition team to place a request.

Introduction:

Are you searching for an opportunity to play a key role in driving the dramatic growth of a highly successful software company? 

At Poppulo, we’re working on what’s next in communications and workplace technology. As a pioneer in this industry, we understand that meaningfully reaching every employee is hard. And so is managing office space in a hybrid world. And so is improving the customer and guest experience. We exist to make each of these things easier. We exist to bring harmony to our customers. 

And we do that at enterprise scale. Our omnichannel employee communications, customer communications, and workplace experience platform is trusted by over 6,000 organizations today, reaching more than 35M employees and delivering content to 500,000+ digital signs.

We know there’s no such thing as a “perfect" candidate - we’re all a work in progress and are growing new skills and capabilities all the time. We encourage you to apply for a position with Poppulo even if you don’t meet 100% of the requirements. We believe in fostering an environment where there is a diversity of perspectives, in hopes that we can all thrive. 

The Opportunity

We are looking for a Sr. Machine Learning (ML) Engineer with a strong sense of ownership. If you are an ML practitioner who thrives in an environment where innovation meets practical application to build disruptive products, this role is for you. 

At Poppulo, we intend to redefine boundaries and reshape Employee Communications and Digital Signage through the power of cutting-edge machine learning and AI. We are not just building products; we are disrupting the status-quo with transformative solutions that challenge conventional thinking, create competitive edge and create new market opportunities. 

This role is pivotal to the success of our AI team. It is the backbone of our ML initiatives. This role bridges the gap between research and production by leveraging cutting-edge AI technology into leading, world-class solutions.  

As a Sr. Full-Stack Machine Learning (ML) Engineer, you be the key driver for innovative problem solving by combining technical excellence with creative application of ML. Your expertise will be crucial in uncovering hidden opportunities within product ideas, including the design and deployment of agentic AI systems that can reason, plan, and act autonomously within real-world product constraints. Additionally, you will stay at the forefront of emerging technologies, continuously evaluating new AI/ML frameworks, tools, and best practices to help guide the evolution of our software solutions. 

Key Responsibilities

• Own end-to-end delivery of AI features across model, backend, APIs, UI integration, deployment, monitoring, and iteration in production
• Solve complex challenges with AI/ML: Design, develop new AI-powered products that deliver the product roadmap, including agentic AI solutions that orchestrate LLMs, tools, and workflows to solve multi-step problems autonomously.
• Implement ML lifecycle - from data engineering and model development to cloud-based deployment, integrations and operationalisation. Incl. MLOps 
• Productionise full-stack AI/ML solutions: Translate emerging techs like GenAI& agenticAI architectures into innovative, practical solutions that transform customer experiences. 
• Align with Product Strategy: Create proof of concepts at high cadence to demonstrate/validate potential solutions as per our product strategy. 
• Optimise Model and system performance: Fine-tune, optimise training and inference performances, including latency, cost, and reliability trade-offs in agent-based and LLM-driven systems.
• Wider collaboration: Partner with cross-functional teams to demonstrate and validate the impact of ML innovations before introducing them into the product ecosystem. 
• Research Savvy: Staying up-to-date with SOTA and industry trends in AI/ML, with a strong awareness of advances in agentic systems, autonomous workflows, and multi-agent architectures. 

Technical Skills / Competencies  

• Strong AI/ML background: Expertise in designing, building and deploying real-world ML applications (Computer Vision, Classification, etc.) 
• Strong foundation in GenAI: Deep understanding of generative models (LLMs, etc.), AI Agents, prompt engineering RAG, vector databases. 
• Technical Expertise: Proficiency in ML/GenAI frameworks, databases, shell scripts and programming languages, including frameworks and tools commonly used for building and orchestrating AI agents.
• MLOps expertise: Hands-on experience in setting up MLOps on AWS, Azure and GCP. 
• Full-stack expertise: Proficiency in data pipelines, distributed systems, APIs, web front-end, mobile apps, automated testing and cloud platforms (AWS, GCP, etc.). 
• Exceptional problem-solving skills: Ability to simplify and breakdown complex technical and business challenges to create innovative and practical solutions. 
• Team management: Experience in guiding teams to deliver high-impact solutions. 
• Continuous learning: Ability to learn quickly and apply new technologies to solve problems practically. 

Education & Experience

• Master’s or PhD in AI/ML or a related field
• At least 6+ years of experience building software or AI systems, including 1–3 years working with LLMs, generative AI, or AI agent architectures.

Why Us? 

• An excellent workplace culture 
• Competitive salary 
• Company performance-related bonus
• Medical insurance 
• Flexible working hours 
• Educational assistance 
• In-house soft skills training 

Who We Are

We are a values-driven organization that encourages our employees to bring their authentic selves to work every day and empowers everyone to make a tangible impact on our products, clients, and culture. We offer a dynamic environment with driven, fun, and flexible individuals who thrive on challenge and responsibility. This is an opportunity to contribute to our culture and join a company that’s on the move.

We live the Poppulo values each day, as they are key to everything we do.

• Bring Your Best Self
  We show up authentically, are self-aware and always strive to be better.
• See it. Own it. Solve it.
  We proactively innovate and solve for our customers and each other. We set an example with high standards for our work. We foster a culture of learning, acknowledging our successes and our failures.
• Together We’re Better
  We value and celebrate our diversity. We learn from others, respecting their expertise, and focus on building trust. That's what makes us a team.

Named a Great Place to Work in 2015, 2016, 2017, 2018, 2019, 2020, and 2021, we are a fast-growing global technology company, with offices in Ireland, the US, the UK and India.

Poppulo is an equal opportunity employer.

We are committed to protecting your privacy. For details on how we collect, use, and protect your personal information, please refer to our Job Applicant Privacy Policy.

Introduction:

Are you searching for an opportunity to play a key role in driving the dramatic growth of a highly successful software company? 

At Poppulo, we’re working on what’s next in communications and workplace technology. As a pioneer in this industry, we understand that meaningfully reaching every employee is hard. And so is managing office space in a hybrid world. And so is improving the customer and guest experience. We exist to make each of these things easier. We exist to bring harmony to our customers. 

And we do that at enterprise scale. Our omnichannel employee communications, customer communications, and workplace experience platform is trusted by over 6,000 organizations today, reaching more than 35M employees and delivering content to 500,000+ digital signs.

We know there’s no such thing as a “perfect" candidate - we’re all a work in progress and are growing new skills and capabilities all the time. We encourage you to apply for a position with Poppulo even if you don’t meet 100% of the requirements. We believe in fostering an environment where there is a diversity of perspectives, in hopes that we can all thrive. 

The Opportunity

We are looking for a Sr. Machine Learning (ML) Engineer with a strong sense of ownership. If you are an ML practitioner who thrives in an environment where innovation meets practical application to build disruptive products, this role is for you. 

At Poppulo, we intend to redefine boundaries and reshape Employee Communications and Digital Signage through the power of cutting-edge machine learning and AI. We are not just building products; we are disrupting the status-quo with transformative solutions that challenge conventional thinking, create competitive edge and create new market opportunities. 

This role is pivotal to the success of our AI team. It is the backbone of our ML initiatives. This role bridges the gap between research and production by leveraging cutting-edge AI technology into leading, world-class solutions.  

As a Sr. Full-Stack Machine Learning (ML) Engineer, you be the key driver for innovative problem solving by combining technical excellence with creative application of ML. Your expertise will be crucial in uncovering hidden opportunities within product ideas, including the design and deployment of agentic AI systems that can reason, plan, and act autonomously within real-world product constraints. Additionally, you will stay at the forefront of emerging technologies, continuously evaluating new AI/ML frameworks, tools, and best practices to help guide the evolution of our software solutions. 

Key Responsibilities

• Own end-to-end delivery of AI features across model, backend, APIs, UI integration, deployment, monitoring, and iteration in production
• Solve complex challenges with AI/ML: Design, develop new AI-powered products that deliver the product roadmap, including agentic AI solutions that orchestrate LLMs, tools, and workflows to solve multi-step problems autonomously.
• Implement ML lifecycle - from data engineering and model development to cloud-based deployment, integrations and operationalisation. Incl. MLOps 
• Productionise full-stack AI/ML solutions: Translate emerging techs like GenAI& agenticAI architectures into innovative, practical solutions that transform customer experiences. 
• Align with Product Strategy: Create proof of concepts at high cadence to demonstrate/validate potential solutions as per our product strategy. 
• Optimise Model and system performance: Fine-tune, optimise training and inference performances, including latency, cost, and reliability trade-offs in agent-based and LLM-driven systems.
• Wider collaboration: Partner with cross-functional teams to demonstrate and validate the impact of ML innovations before introducing them into the product ecosystem. 
• Research Savvy: Staying up-to-date with SOTA and industry trends in AI/ML, with a strong awareness of advances in agentic systems, autonomous workflows, and multi-agent architectures. 

Technical Skills / Competencies  

• Strong AI/ML background: Expertise in designing, building and deploying real-world ML applications (Computer Vision, Classification, etc.) 
• Strong foundation in GenAI: Deep understanding of generative models (LLMs, etc.), AI Agents, prompt engineering RAG, vector databases. 
• Technical Expertise: Proficiency in ML/GenAI frameworks, databases, shell scripts and programming languages, including frameworks and tools commonly used for building and orchestrating AI agents.
• MLOps expertise: Hands-on experience in setting up MLOps on AWS, Azure and GCP. 
• Full-stack expertise: Proficiency in data pipelines, distributed systems, APIs, web front-end, mobile apps, automated testing and cloud platforms (AWS, GCP, etc.). 
• Exceptional problem-solving skills: Ability to simplify and breakdown complex technical and business challenges to create innovative and practical solutions. 
• Team management: Experience in guiding teams to deliver high-impact solutions. 
• Continuous learning: Ability to learn quickly and apply new technologies to solve problems practically. 

Education & Experience

• Master’s or PhD in AI/ML or a related field
• At least 6+ years of experience building software or AI systems, including 1–3 years working with LLMs, generative AI, or AI agent architectures.

Why Us? 

• An excellent workplace culture 
• Competitive salary 
• Company performance-related bonus
• Medical insurance 
• Flexible working hours 
• Educational assistance 
• In-house soft skills training 

Who We Are

We are a values-driven organization that encourages our employees to bring their authentic selves to work every day and empowers everyone to make a tangible impact on our products, clients, and culture. We offer a dynamic environment with driven, fun, and flexible individuals who thrive on challenge and responsibility. This is an opportunity to contribute to our culture and join a company that’s on the move.

We live the Poppulo values each day, as they are key to everything we do.

• Bring Your Best Self
  We show up authentically, are self-aware and always strive to be better.
• See it. Own it. Solve it.
  We proactively innovate and solve for our customers and each other. We set an example with high standards for our work. We foster a culture of learning, acknowledging our successes and our failures.
• Together We’re Better
  We value and celebrate our diversity. We learn from others, respecting their expertise, and focus on building trust. That's what makes us a team.

Named a Great Place to Work in 2015, 2016, 2017, 2018, 2019, 2020, and 2021, we are a fast-growing global technology company, with offices in Ireland, the US, the UK and India.

Poppulo is an equal opportunity employer.

We are committed to protecting your privacy. For details on how we collect, use, and protect your personal information, please refer to our Job Applicant Privacy Policy.

The Role:

• As an Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

The work you’ll do:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Solution Engineer stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Solution Engineers specialize in domains (e.g. supply chain) and industries

The qualifications you need:

• 3-5 years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

Job Description

PayPay's rapid growth necessitates the expansion of its product teams and underscores the critical need for a resilient Data Engineering Platform. This platform is vital to support our increasing business demands. The Data Pipeline team is tasked with creating, deploying, and managing this platform, utilizing leading technologies like Databricks, Delta Lake, Spark, PySpark, Scala, and the AWS suite.

We are actively seeking skilled Data Engineers to join our team and contribute to scaling our platform across the organization.

Main Responsibilities

• Create and manage robust data ingestion pipelines leveraging Databricks, Airflow, Kafka, and Terraform.
• Ensure high performance, reliability, and efficiency by optimizing large-scale data pipelines.
• Develop data processing workflows using Databricks, Delta Lake, and Spark technologies.
• Maintain and improve the Data Lakehouse, utilizing Unity Catalog for efficient data management and discovery.
• Construct automation, frameworks, and enhanced tools to streamline data engineering workflows.
• Collaborate across teams to facilitate smooth data flow and integration.
• Enforce best practices in observability, data governance, security, and regulatory compliance

Qualifications

• Minimum 7 years as a Data Engineer or similar role.
• Hands-on experience with Databricks, Delta Lake, Spark, and Scala.
• Proven ability to design, build, and operate Data Lakes or Data Warehouses.
• Proficiency with Data Orchestration tools (Airflow, Dagster, Prefect).
• Familiarity with Change Data Capture tools (Canal, Debezium, Maxwell).
• Strong command of at least one primary language (Scala, Python, etc.) and SQL.
• Experience with data catalog and metadata management (Unity Catalog, Lakeformation).
• Experience in Infrastructure as Code (IaC) using Terraform.
• Excellent problem-solving and debugging abilities for complex data challenges.
• Strong communication and collaboration skills.
• Capability to make informed decisions, learn quickly, and consider complex technical contexts.

• Leverage AI/LLM-based tools in daily workflows (e.g., code development, reviews, testing, debugging, documentation), while ensuring human oversight, judgment, and accountability drive the final product.

Remarks

＊Please note that you cannot apply for PayPay (Japan-based jobs) or other positions in parallel or in duplicate.

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Working Conditions 

Employment Status

• Full Time

Office Location

• Gurugram (Wework)
  

  ＊The development center requires you to work in the Gurugram office to establish the strong core team.
     

A Career with Point72's Technology Team

As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity.

What you'll do

• Lead the design, development, and operation of scalable, enterprise-grade AI/ML architectures and systems with a strong emphasis on reliability, availability, and performance.
• Lead and mentor a team of engineers, driving technical direction, code quality, and iterative delivery of large-scale solutions.
• Partner closely with data scientists, engineers, product teams, and compliance to integrate AI/ML solutions into existing and new products.
• Own the end-to-end lifecycle of GenAI services, including LLM inference, model serving, and proxy/gateway layers that support multiple downstream applications.
• Define and uphold engineering best practices around observability, scalability, security, and cost efficiency for AI/ML platforms.
• Evaluate tools, technologies, and processes to ensure the highest quality and performance of AI/ML systems.
• Stay abreast of the latest advancements in AI/ML technologies and methodologies, and translate them into pragmatic solutions for the business.
• Ensure compliance with industry standards and best practices in AI/ML.

What's required

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 10+ years of experience in software/AI/ML engineering, with a proven track record of successful delivery of complex, production-grade systems.
• Demonstrated experience building large-scale enterprise-grade services with high reliability, availability, and observability (SLO/SLA-driven environments).
• Experience leading other engineers in delivering large-scale solutions iteratively, including setting technical vision, reviewing designs, and growing team capabilities.
• Proficiency in programming languages such as Python, Java, or C++.
• Strong understanding of distributed systems, cloud platforms (AWS/Azure/GCP), containerization (Docker/Kubernetes), and modern CI/CD practices.
• Excellent problem-solving skills and the ability to work independently and collaboratively.
• Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders and influence across teams.
• Commitment to highest ethical standards.

About Point72

Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit www.Point72.com/about.

About the role

The developer's job is shifting from writing code to directing AI agents, and hiring needs to catch up. HackerRank has shaped how 3000+ companies identify engineering talent, with 30M+ developers assessed on our platform. Chakra is our bet on what the next generation of that looks like: an AI interviewer built for a world where the interview itself has to be as intelligent as the candidates it is evaluating.

Open Problem
An interview that thinks, listens and gets it right every time.

Running an interview is easy. Running a good one is hard.

Chakra is an AI interviewer. It holds a conversation with a candidate, asks follow-up questions, evaluates how they think, and produces a report a hiring manager can actually act on. It is to conduct interviews that are more consistent, more probing, and more fair than most human interviewers manage in practice.

Here is the problem. A great human interviewer can do this. They read the candidate. They push on the right things. They know when an answer is shallow and when it just sounds shallow. Getting a model to do that reliably is genuinely difficult. Not because the technology cannot hold a conversation. It can. The gap is in judgment. Knowing what to probe. Knowing what the answer actually reveals about the candidate. Knowing when to move on.

Now do that 200,000 times. With candidates who speak differently, think differently, and approach problems differently. Without the model drifting. Without it being gamed. Without every report reading like it was written by the same template.

That is where the field currently falls short. Closing that gap is the work.

What you'll do

• Architect and develop Chakra end to end: the agent design, conversation management, real-time response evaluation, scoring methodology, and report generation.
• Build the systems that ensure interview consistency at scale. Not just model capability, but the infrastructure that makes the 200,000th interview as coherent as the first.
• Design evaluation and benchmarking pipelines that measure interview quality, candidate experience consistency, and report defensibility.
• Build fine-tuning and RLHF workflows to push model judgment past what off-the-shelf models deliver for this specific task.
• Own the quality bar. Define what a good interview looks like, instrument how well the system meets that bar, and close the gap systematically.
• Work across the full stack: data pipelines, model serving, latency constraints, and the product experience the candidate actually encounters.

Who you are

• You have built and shipped agentic or conversational AI systems in production, not just prototypes.
• You have a strong intuition for where LLM behavior breaks down under real-world conditions and how to address it systematically.
• You think in systems. The conversation architecture, the evaluation model, the serving infrastructure, and the candidate experience are one problem to you.
• You care about the quality bar at the level of a user who depends on the output, not just a researcher measuring aggregate metrics.

Even better if you have

• Experience building multi-turn conversational agents or interview-style AI systems.
• Worked with RLHF, Constitutional AI, or preference-based fine-tuning methods.
• Background in dialogue systems, conversational evaluation, or rubric-based scoring.
• Publications or contributions in agentic AI, LLM reliability, or evaluation of generative systems.

You will thrive in this role if

• You are energized by the full scope of a hard product problem, from model architecture through the conversation a candidate actually has. 
• You hold the product bar as high as the technical bar. You want to build something that works extraordinarily well for every single person who uses it.

About the role

How developers were evaluated previously was whether they can write functionally correct code. How developers are being evaluated now is whether they can orchestrate AI to accomplish the task while still having the fundamentals underneath. That shift, between what used to matter and what matters now, is exactly the problem this role is hired to solve.

Open Problem
How do you measure skill when AI is already in the room?

Software engineering has moved from writing code to using AI to solve problems. That shift sounds simple. The implications for assessment are not. This is not just a take-home assignment problem. It spans live interviews, async assessments, AI-assisted coding environments, pair programming with agents, and every other context in which someone is trying to figure out how good a developer actually is. The tools developers use are changing fast. The frameworks we use to evaluate them have not kept up.

For over a decade, skills-based hiring relied on deterministic evaluation: a candidate's code either passed test cases or it did not. The score was binary and reproducible. What replaces it is genuinely unsolved. Nobody has cracked how to fairly assess human skill in a world where AI assistance is ambient and invisible, where the question is no longer "can you write this function" but "how effectively do you use AI to solve a real problem."

We are moving from a deterministic evaluation to evaluation by a council of LLMs. But making that consistent, scalable, and defensible across hundreds of thousands of assessments is a hard research and engineering problem. How do you ensure the same rubric is applied the same way to the 200,000th candidate as to the first? How do you detect when your evaluation model is drifting? How do you explain a score to a candidate who believes they were assessed unfairly?

HackerRank sits at the center of this problem with a rare combination of scale, longitudinal data, and direct relationships with the companies making hiring decisions. The opportunity here is to define what rigorous, fair, and meaningful skill evaluation looks like in the agentic era. That methodology does not exist yet. This role exists to build it.

What you will do

• Build LLM-powered evaluation pipelines that assess AI usage skills consistently, fairly, and at production scale.
• Own the evaluation methodology end to end- what the rubric is, how the model applies it, how you measure whether it is being applied correctly, and how you audit for bias.
• Design and run experiments to determine what good evaluation actually looks like. The answer is not known. You will be finding it.
• Build RAG pipelines and fine-tuning workflows that make evaluation models adhere reliably to the rules we set for them.
• Define the benchmarking infrastructure: how we know when our evaluation quality has improved, and how we catch regressions before candidates do.
• Translate model behavior into outcomes that product managers, enterprise customers, and candidates can understand and trust.

Who you are

• You have shipped LLM-powered systems in production where consistency and reliability were hard constraints, not nice-to-haves.
• You think as rigorously about how you measure your model as about the model itself. A poorly constructed eval is a worse outcome than a weaker model.
• You have a research mindset. You are comfortable operating in a space where the right methodology does not exist yet and needs to be invented.
• You think in systems. The data pipeline, the model, the serving layer, and the rubric it enforces are one problem to you.
• You can defend ML judgment in plain language to people who are not ML engineers, because the translation layer is part of the job.

Even better if you have

• Experience building evaluation frameworks for generative or conversational AI systems.
• Background in educational assessment, psychometrics, or human-in-the-loop evaluation at scale.
• Publications or open-source contributions in LLM evaluation, benchmarking, or alignment.
• Prior work at the interface of research and product, where you had to ship science, not just publish it.

You will thrive here if

• You find the measurement problem as interesting as the model problem, maybe more interesting. 
• You hold evaluation methodology to the same standard as model performance, and you are uncomfortable shipping something you cannot explain. 
• You want your work to define what good looks like in a field that is just now figuring that out.

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

Now, more than ever, the Toast team is committed to our customers. We’re taking steps to help restaurants navigate these unprecedented times with technology, resources, and community. Our focus is on building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that we’ll deliver on their needs for today while investing in experiences that will power their restaurant of the future. 

Bready* to make a change?

Toast is looking for a Staff Machine Learning Engineer to serve as a technical linchpin for our AI Platform team. At the P4 level, you aren't just deploying models; you are designing the fundamental infrastructure that enables dozens of teams to build, deploy, and monitor AI at scale. You will act as a force multiplier, mentoring senior engineers and setting the architectural standards for our MLOps lifecycle—from feature stores and automated retraining to high-performance inference at the edge.

About this Roll*:

• Architectural Leadership: Design and lead the evolution of a unified MLOps platform that supports diverse needs across Toast, ensuring high availability, scalability, and security of ML services.
• Engineering Excellence: Champion and institutionalize best practices for CI/CD for ML (MLOps), automated testing, and infrastructure-as-code (Terraform).
• Cross-Functional Synergy: Lead collaborative efforts across Data Engineering, DevOps, and Product teams to bridge the gap between model prototyping and production-grade reliability.
• Strategic Roadmapping: Partner with leadership and Product Managers to define the 1-2 year technical vision for AI infrastructure, prioritizing long-term stability over short-term fixes.
• Operational Ownership: Set the standard for observability and incident response for ML systems, driving root-cause analysis for complex system failures.
• Mentorship: Actively mentor P2 and P3 engineers, fostering a culture of technical rigor and continuous learning.

Do you have the right ingredients*?

• Education: Bachelor’s or Master’s degree in Computer Science, AI, or a related technical field.
• Experience: A minimum of 10-12+ years of professional software engineering experience, with at least 6-7 years specifically focused on productionizing and scaling ML systems at the enterprise level.
• Core Tech Stack: Expert-level proficiency in Python, Scala, or Java/Kotlin. Extensive experience with PySpark and high-performance computing.
• Generative AI & LLMOps: Proven track record of taking LLM applications from research to production, including experience with Vector Databases, LangChain/LangGraph, and A2A protocols.
• System Design: Superior ability to design distributed systems that handle millions of requests with sub-second latency.
• Experience with microservice based architecture, preferably with AWS tooling (SageMaker, DynamoDB, Athena, Glue, etc.)
• Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration, MLflow
• Profound knowledge of model deployment, orchestration (Apache airflow, Prefect), scaling, and managing CPU/GPU resources efficiently. 
• Exceptional problem-solving, analytical skills and the ability to tackle complex problems with a critical thinking approach. 
• Outstanding communication and interpersonal skills, coupled with a demonstrated ability to work collaboratively within a team environment.
• Foundational knowledge in statistical concepts (e.g. classification, regression, etc) and deep learning algorithms (e.g. CNN, RNN) is desirable

Bonus Ingredients (The "Staff" Edge)

• Data Strategy: Experience implementing enterprise-grade Feature Stores (e.g., Tecton, Feast) and real-time streaming frameworks like Apache Flink or Ray.
• Full-Stack Visibility: Ability to dive into the UI/UX layer (React) or deep into the kernel/networking layer to debug performance bottlenecks.

Open Source/Community: Contributions to relevant open-source projects (MLflow, Kubeflow, etc.) or a history of speaking at industry conferences.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy 
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

Position Summary:

We are looking for a Staff Software Engineer – Full Stack & AI Innovation with strong hands-on experience in TypeScript (Node.js, JavaScript), and/or Python and a passion for leveraging AI-driven code generation tools to accelerate development. You will play a critical role in operationalizing GenAI-based code generation platform. This role involves translating product specifications into structured inputs for GenAI tools, reviewing the code generated by GenAI tool, and providing feedback to product engineering team to improve quality and performance of the GenAI tool.

You will work closely with product managers, software engineers, and AI specialists to ensure that the generated code aligns with business and technical requirements. The ideal candidate is curious, adaptable, critic and eager to evaluate AI-assisted code generation tool.

Key Responsibilities:

• Develop, Analyze and structure product specifications for input into GenAI programming tools.
• Operate GenAI systems to generate code based on structured inputs.
• Perform detailed code reviews of GenAI-generated programs to ensure correctness, performance, and maintainability.
• Utilize several other AI-powered code generation tools (Cursor.ai, Windsurf, etc.) to compare and optimize GenAI tool in subject.
• Provide feedback to improve GenAI model outputs and prompt engineering strategies.
• Review and validate generated code for correctness, efficiency, and adherence to coding standards.
• Maintain documentation of input formats, code review findings, and feedback cycles.
• Stay current with advancements in GenAI programming tools and code generation technologies.
• Participate in code reviews and mentor junior developers.

Basic Qualifications:

• Bachelor’s/master’s in computer science, Engineering, or equivalent experience.
• 8 to 10 years' experience with strong expertise in at least one of the following:
• TypeScript / JavaScript (Node.js, React, Next.js, Angular, Vue.js)
• Python (Django, Flask, FastAPI/ RestAPI)
• Person must have designed, developed, and maintained scalable front-end and back-end applications using TypeScript/JavaScript/Python.
• Solid understanding of front-end technologies (HTML5, CSS3, Tailwind, Material UI or similar).
• Familiarity with GenAI tools and LLM-based code generation platforms (e.g., GitHub Copilot, CodeWhisperer, etc.).
• Experience with databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB).
• Hands-on experience with Cursor.ai and/or Windsurf (plus other AI-assisted coding tools like GitHub Copilot, Tabnine, Codeium).
• Strong understanding of software development principles and code review practices.
• Familiar with Code review tools (e.g. GitHub, GitLab, Bitbucket etc)
• Strong grasp of software design principles (OOP, SOLID, microservices).
• Excellent problem-solving, debugging, and collaboration skills.
• Excellent analytical and communication skills.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications:

• Experience working with prompt engineering or structured input design for GenAI systems.
• Exposure to MLOps or AI model evaluation frameworks.
• Knowledge of software architecture and design patterns.
• Knowledge of containerization (Docker, Kubernetes).
• Exposure to serverless architecture and event-driven systems.
• Contribution to open-source or AI-driven development communities.

Opportunity Overview:

We are seeking a Technical, Hands-on Manager to lead a team in building AI-driven healthcare enterprise applications. In this role, you will combine strong people leadership with deep technical expertise to guide the development of scalable, data-intensive solutions that drive meaningful business impact.

As a leader who is still technically involved, you will mentor and manage data scientists and analysts while having the ability to guide the team through evaluating, selecting, and implementing the right models, paired with an understanding of end to end workflow and ensure the delivery of scalable AI solutions. 

This position requires excellent communication and collaboration skills as you partner closely with internal stakeholders and cross‑functional engineering, product, and clinical teams. In our fast-paced environment, adaptability is key—your ability to reprioritize quickly and lead your team through evolving business needs will ensure maximum impact

What you’ll do:

• Lead, mentor, and develop a high‑performing team of Data Scientists and ML Engineers, ensuring strong execution and continuous skill advancement.
• Contribute to event‑driven architecture design and implementation, enabling asynchronous processing and large‑scale system integration.
• Work seamlessly across functions—partnering with Data Scientists on model tuning, experimentation, and prompt design; collaborating with Product and Software Engineering to embed AI/ML into user-facing applications; engaging with DevOps/Platform Engineering on environment setup, CI/CD, monitoring, and reliability; and working with Data Engineering on pipeline design and ingestion strategies.
• Provide technical leadership in the effective use of AWS services such as Lambda, EC2, EMR, S3, Athena, Batch, Textract, Comprehend, Bedrock.
• Drive the implementation of project scope definition, effort estimation, and planning in close coordination with cross-functional teams.
• Conduct code reviews, provide architectural direction, and champion SDLC best practices, while balancing leadership responsibilities with hands‑on technical contributions to ensure timely, high‑quality delivery.

Required Qualifications:

• 7+ years of overall professional experience delivering data-driven AI/ML-focused solutions. 3+ years of direct team management experience, leading Data Scientists, ML Engineers, or similar technical roles.
• Hands-on experience in Python with strong proficiency in libraries such as Pandas, NumPy, SciPy, Matplotlib, and regular expressions. Advanced SQL querying and optimization for large datasets.
• Practical experience in training, tuning, and testing ML algorithms (e.g., SVM, CART, Bagging, Boosting) and text mining techniques; familiarity with modern ML/DL approaches.
• Experience with prompt engineering and leveraging GenAI for classification, data enrichment, semantic embeddings, and innovative AI-driven solutions.
• Experiment and rapidly prototype design frameworks, validate hypotheses efficiently, and iterate on AI/ML models to support fast-paced development.
• Strong knowledge of Object-Oriented Programming (OOP) and experience creating custom Python packages for serverless applications.
• Hands-on experience with AWS services including Lambda, EC2, EMR, S3, Athena, Batch, Textract, and Comprehend.
• Work seamlessly across Data Science, Engineering, Product, DevOps, and Data Engineering teams to align technical decisions with business goals, ensuring smooth integration of AI/ML capabilities into production systems
• Excellent communication and storytelling skills, capable of translating complex AI/ML concepts into clear, actionable insights for leadership, stakeholders, and non-technical partners.
• Ownership mindset with end‑to‑end accountability, ensuring delivery from concept to deployment to monitoring—while continuously identifying risks, blockers, and opportunities for improvement.

Good to have:

• Background in healthcare payment integrity, clinical data workflows, or payer/provider analytics.
• Strong thought leadership in AI/ML, including guiding stakeholders on feasibility, risk, architecture, and adoption strategy.
• Prior experience in deploying LLM‑powered production features,optimize prompting strategies, transforming experimental prototypes into robust, scalable services delivered through well‑defined APIs.
• Familiarity with compliance, governance, and security best practices for healthcare data (HIPAA, PHI handling, logging, auditing).

Ability to commute/relocate:

• Nacharam, Hyderabad, Telangana*: Reliably commute or planning to relocate before starting work (Preferred)

Interview Process*:

1. Connect with the Hiring Manager for a Preliminary Phone Screening
2. Behavioral Interview(s)
3. Case Study
4. Interview with Senior Leadership

*Subject to change

About Cohere Health:

Cohere Health’s clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members.

With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately.

Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. Backed by leading investors such as Deerfield Management, Define Ventures, Flare Capital Partners, Longitude Capital, and Polaris Partners, Cohere Health drives more transparent, streamlined healthcare processes, helping patients receive faster, more appropriate care and higher-quality outcomes.

The Coherenauts, as we call ourselves, who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.

We can’t wait to learn more about you and meet you at Cohere Health!

Equal Opportunity Statement: 

Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all.  To us, it’s personal.

At NICE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you

So, what’s the role all about?

We are seeking a visionary Software Architect to serve as a technical leader for our engineering teams. In this role, you will bridge the gap between high-level strategy and hands-on execution, managing architectural subdomains within a large-scale platform. You will be responsible for guiding engineers toward correct technical paths, making high-stakes decisions, and relentlessly driving innovation and AI-first transformation across the organization.

How will you make an impact?

• Technical Leadership: Lead and influence multiple engineering teams, ensuring architectural alignment and high-quality technical decisions across subdomains.
• System Design: Architect resilient, multi-tenant cloud solutions and distributed event-driven systems that scale.
• Stakeholder Management: Collaborate with product leaders, directors, and cross-functional teams to navigate complex requirements in a multi-domain environment.
• API & Integration Strategy: Define robust API management strategies and ensure system resiliency through modern integration patterns.
• AI Integration: Evangelize and implement AI productivity tools (GitHub Copilot, Agents) and oversee the lifecycle of AI-driven applications utilizing LLMs.

Have you got what it takes?

• Total 14+ years and relevant 8+ years’ experience as Software Architect .
• Cloud Expertise: Proven track record of designing and deploying production-grade systems on AWS using a broad range of AWS native services.
• Architectural Depth: Deep experience in Multi-tenant Cloud Architecture, Event-Driven Systems, and Resiliency Patterns  
• Polyglot Mindset: A "right tool for the job" approach, with a willingness to work across various languages and frameworks in an AI-first environment.
• Communication: Exceptional ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• AI/LLM Proficiency: It will be good to have a person with practical understanding of AI project lifecycle specifically using LLMs and the use of AI agents to accelerate development

• Backend: Advanced proficiency in Java and Springboot Framework. Exposure to Node.js will be a significant plus.
• Infrastructure: Hands-on experience with AWS CloudFormation (YAML) and Infrastructure as Code.
• Data: Strong mastery of SQL required
• Big Data exposure to Apache Spark or Big Data processing will be a bonus.
• Frontend: Solid understanding of modern UI frameworks and frontend development principles.
• Tooling: Expert-level use of Jira, GitHub, GitHub Copilot, and Claude Code/other AI agents for productivity
• Testing : good exposure to automation testing and frameworks for unit testing , integration testing , e2e testing, performance testing.

What’s in it for you?

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr.

Enjoy NICE-FLEX!

At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID:  10835
Reporting into: Director, Engineering, CX
Role Type: Individual Contributor

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

AI Foundations is Toast's internal platform team for AI. We build the infrastructure, governance, and developer tooling that makes AI a reliable, scalable force multiplier across the entire product development lifecycle. Our products include the LLM Proxy, AI Key Management, Observability pipelines, the Claude Plugin Marketplace, and autonomous agents that participate directly in the software development lifecycle.

As a Staff Software Engineer on this team, you'll shape the foundation others build on: from the LLM Proxy that routes all internal AI traffic, to autonomous agents that participate directly in the software development lifecycle. If you want to work at the frontier of AI infrastructure and see your work amplify hundreds of engineers across a fast-growing company, this is the role.

A day in the life (Responsibilities)

• Design, build, and ship core AI platform infrastructure, including the LLM proxy, AI key management, and observability pipelines powering Toast's internal AI ecosystem
• Architect and deliver autonomous agents that participate in the SDLC, including the AI Review GitHub App and Developer Platform MCP integrations
• Build on and help maintain the internal plugin marketplace, developing plugins that encode Toast's architectural standards, PR patterns, and quality practices directly into AI assistant behavior
• Lead technical design and implementation of MCP (Model Context Protocol) services and no-code service templates that accelerate AI-powered development across Toast
• Drive adoption of agentic development practices through tooling, internal evangelism, and hands-on enablement across engineering teams
• Mentor engineers through code reviews, architecture discussions, and pairing sessions
• Partner with product and platform teams to define and expand the AI Foundations roadmap

What you'll need to thrive (Requirements)

• 8+ years of experience designing and implementing scalable backend services
• Strong foundation in Java, Kotlin, or another object-oriented language, with experience building scalable backend services
• Demonstrated experience building, deploying, or operating LLM-powered agents or AI-assisted developer tooling
• Deep familiarity with AI coding assistants (e.g., Claude Code, Cursor, GitHub Copilot) and the ability to extend them through custom plugins, skills, or hooks
• Hands-on experience with MCP (Model Context Protocol), tool use patterns, or agentic frameworks
• Strong prompt engineering skills and intuition for how LLM behavior changes with context, instructions, and tool definitions
• Proven track record of technical leadership: influencing architecture decisions, setting quality standards, and mentoring peers
• Experience with distributed systems, API design, and cloud-native infrastructure
• Strong customer empathy and the ability to translate developer pain points into platform solutions

What will help you stand out

• Familiarity with A2A (Agent-to-Agent) protocols and multi-agent orchestration patterns
• Experience with machine learning concepts, model evaluation, or ML infrastructure
• Experience building developer experience platforms, internal tooling, or API gateways
• Familiarity with observability tooling for AI/LLM systems (e.g., Langfuse, DataDog)

This is a hybrid role with 2 days per week in the Bengaluru office

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy 
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

Job summary: 

• We are looking for a talented Enterprise Account Executive / Business Development Manager to join our fast-growing Brandwatch Sales organisation. You will be responsible for driving new enterprise revenue in India with a strong focus on Trajaan, while also growing strategic accounts across the broader Brandwatch portfolio.
• This is a hybrid AE/AM role suited to a highly commercial, enterprise seller who can both self-generate pipeline and expand existing customer relationships. The ideal candidate will have a strong track record in enterprise SaaS sales with a skill-set including, but not limited to, prospecting, pipeline generation, complex deal management, executive stakeholder engagement, renewal negotiation, upselling and especially cross-selling. A key part of this role will be leading with Trajaan as a strategic growth priority, while identifying opportunities to expand into other Brandwatch solutions where relevant.
• You will drive growth by engaging some of India’s largest organisations, challenging the way customers think about search intelligence, consumer intelligence and digital strategy, and positioning how Trajaan and Brandwatch can support those evolving priorities. You would be a great fit if you are comfortable building from the ground up, owning the full commercial cycle, and balancing a hunter mindset with strong account growth instincts.

What you will do:

• Drive new enterprise business growth in India, with a primary focus on Trajaan and a secondary focus on the wider Brandwatch portfolio;
• Build and manage a robust pipeline through proactive outbound prospecting, self-generated opportunities, partner collaboration and internal support functions;
• Own the full sales cycle from initial outreach and discovery through solutioning, commercial negotiation and contract execution;
• Lead land-and-expand motions across strategic accounts, identifying upsell and cross-sell opportunities;
• Build long-term relationships with senior stakeholders across Marketing, Insights, Digital, Strategy, Communications and related enterprise functions;
• Act as a trusted advisor to customers by challenging the status quo and promoting how Trajaan and Brandwatch can support growth, visibility and competitive advantage;
• Maintain constant engagement with accounts post-sale, partnering with Customer Success and internal stakeholders to drive adoption, value realisation, retention and expansion;
• Identify commercial risk and collaborate with internal teams to clear blockers, protect revenue and support successful renewals where relevant;
• Be the primary point of contact for the customer on all commercial and contractual matters within your portfolio;
• Partner with internal Brandwatch and Cision stakeholders to align account plans with the customer’s business priorities and strategic goals;
• Develop strong market knowledge across enterprise sectors in India and stay informed on trends across search, LLM visibility, digital intelligence, consumer behaviour and competitive landscape;
• Possess excellent product knowledge across Trajaan and Brandwatch solutions and lead tailored product demonstrations aligned to customer needs.
• Maintain accurate forecasting, pipeline hygiene and account activity within CRM and reporting systems.

What you will have:

• A strong background in enterprise sales and business development, with SaaS experience strongly preferred;
• 6+ years of experience in a quota-carrying sales role, ideally across a mix of new business acquisition and account growth;
• Proven ability to self-generate pipeline and win new enterprise logos in a competitive market;
• Drive and ambition to achieve and exceed sales quotas;
• Commercial acumen and comfort working towards ambitious growth targets in a highly accountable environment;
• Experience managing complex, multi-stakeholder sales cycles and negotiating commercial agreements with enterprise customers;
• Experience in growing existing client relationships through upsell, cross-sell and renewal ownership where required;
• A results-oriented, highly motivated and enthusiastic attitude, with the ability to work independently in a fast-paced environment;
• Familiarity operating in a high-growth, high-velocity sales environment;
• Outstanding consultative selling skills, including objection handling, negotiation, influencing and value-based solution selling;
• Ability to build strong relationships with internal and external stakeholders;
• Excellent English communication skills; additional Indian regional language capability would be an advantage;
• Deep interest in or knowledge of search intelligence, digital intelligence, consumer insights, social media, marketing technology or customer experience.

Soft skills:

• Top-class presentation and communication skills.
• Excellent analytical, problem-solving and decision-making skills.
• Detail-oriented and persuasive.
• Strong sense of ownership;
• Strong commercial curiosity and a proactive mindset;
• Proficiency with tools such as Salesforce, Salesloft, 6Sense or similar;
• Use of, implementation and understanding of sales processes and methodologies.

Nice to have:

• Experience selling search intelligence, consumer intelligence, marcom or insights-focused solutions;
• Experience selling into enterprise accounts in India;
• Familiarity with Sandler, BANT, MEDDPICC or other similar sales methodologies.
• Experience working with partner or reseller ecosystems.

Truveta provides unprecedented real-world data and real-time intelligence, powered by a dataset built with and owned by US health systems united in a mission of Saving Lives with Data. Together, we power breakthrough medical discoveries, accelerate regulatory-grade evidence, and improve patient care. Today, Truveta enables research on more than 130 million de-identified patients across the US.  

Achieving Truveta’s ambitious mission requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values. 

Role Overview

We are hiring a Prompt Engineer with a strong clinical informatics background to build and optimize AI prompts for healthcare and clinical data applications. This role requires hands-on clinical understanding, experience working with real clinical data, experience writing prompts for AI models, and the ability to align LLM prompts with underlying clinical data models.

You will work closely with clinicians, data engineers, and AI teams to translate clinical questions and workflows into accurate, safe, and scalable AI interactions.

Key Responsibilities

• Design, test, and optimize prompts for LLM-based clinical use cases such as:
• Cohort identification
• Clinical question answering
• Concept extraction
• Clinical code mapping
• Translate clinical requirements into structured prompts aligned with clinical data schemas
• Collaborate with data engineers to understand how diagnoses, labs, medications, encounters, and outcomes are modeled
• Evaluate AI outputs for clinical accuracy, relevance, bias, and safety
• Apply healthcare data standards (FHIR, SNOMED CT, LOINC, RxNorm, ICD-10-CM) within prompt logic and validation
• Create prompt evaluation criteria and quality benchmarks
• Document reusable prompt patterns and best practices
• Continuously improve prompts based on model behavior and user feedback.

Required Qualifications

• 2–5 years of experience in clinical informatics, healthcare analytics, or health IT
• Clinical background required, such as:
• Nursing, pharmacy, medicine, public health, or clinical informatics
• OR hands-on experience working with clinical workflows or EHR data
• Strong understanding of clinical data modeling, including representation of:
• Diagnoses, procedures, medications
• Laboratory results and vitals
• Encounters and outcomes
• Practical experience with healthcare data standards:
• FHIR
• SNOMED CT
• LOINC
• RxNorm
• ICD-10-CM
• Hands-on experience with LLMs and prompt engineering for applied or production use cases
• Ability to critically evaluate AI outputs for correctness and clinical safety
• Strong analytical, documentation, and communication skills

Preferred

• Experience with clinical NLP or unstructured clinical text
• Familiarity with EHR systems or clinical data repositories
• Working knowledge of Python for prompt testing or evaluation
• Working knowledge of SQL for exploring clinical datasets
• Experience combining structured and unstructured healthcare data
• Prior work on healthcare AI, decision support, or analytics platforms

Key Responsibilities

• Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence.
• Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy.
• Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP).
• Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance.
• Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions.
• Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities.
• Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions.

Required Qualifications

• Strong understanding or experience leading AI/ML teams in a SaaS or enterprise software environment.
• Deep expertise in time series forecasting and machine learning.
• Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP).
• Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures.
• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
• Experience with agentic frameworks and autonomous agent architectures.
• Proficiency in Python and modern software development practices (testing, code review, CI/CD).
• Proven track record of delivering complex technical projects on time with high quality.
• Excellent communication, collaboration, and stakeholder management skills.
• Track record of delivering impactful AI solutions in a fast-paced, agile environment.

Preferred Qualifications

• Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
• Experience with large-scale data processing frameworks like Spark.
• Familiarity with the challenges of applying AI in enterprise planning or financial domains.
• A portfolio of published research or contributions to open-source AI projects.

What Makes This Role Exciting

You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry.

What's the Role All About?

The Tech Manager is a senior technical leadership role responsible for driving the design, delivery, and quality of AI-driven and Conversational AI solutions across the NICE CXone ecosystem. With 15+ years of experience, you will lead and mentor a high-performing engineering team, bring deep expertise in AI models, AWS Knowledge Hub, and AWS Cloud, and serve as a key technical authority across cross-functional delivery teams. This role blends hands-on technical depth with strong people management, ensuring both engineering excellence and team growth.

How Will You Make an Impact?

Technical Leadership:

• Define and govern technical standards and best practices for AI and Conversational AI solution delivery.
• Provide hands-on guidance on the design and implementation of integrations using APIs, modern web technologies, and authentication standards.
• Lead the development of proofs of concept (PoCs) and production-ready solution components leveraging AWS Cloud, AWS Knowledge Hub, and AI/ML models.
• Drive prompt engineering, conversational design, and AI orchestration best practices across the team.
• Oversee testing, validation, and go-live activities to ensure solutions meet quality, performance, security, and usability standards.

People Management & Team Development:

• Lead, mentor, and develop a team of engineers — conducting performance reviews, supporting career growth, and fostering a culture of continuous learning.
• Define and uphold engineering standards, coding guidelines, and delivery frameworks across the team.
• Identify skill gaps and build team capability in emerging areas such as Generative AI, AWS services, and enterprise conversational platforms.
• Drive a collaborative, inclusive, and high-accountability team culture.

Technical Problem Solving & Quality:

• Diagnose and resolve complex technical challenges across SaaS applications, cloud environments, AI integrations, and data flows.
• Ensure all implementations meet enterprise-grade standards for quality, scalability, security, and performance.
• Produce and review key documentation including architecture specifications, test strategies, and deployment materials.

Delivery & Process Excellence:

• Drive Agile/Scrum delivery practices including sprint planning, retrospectives, and release management.
• Define and continuously improve engineering processes, documentation standards, and delivery frameworks.
• Align technical roadmap planning with business priorities and stakeholder expectations.
• Manage escalations effectively and maintain strong cross-functional collaboration with Implementation Engineers, Consultants, Project Managers, and Customer Success teams.

Collaboration & Stakeholder Engagement:

• Partner with senior stakeholders, customers, and cross-functional teams to translate business requirements into technical solutions.
• Participate in customer workshops, design reviews, and technical discussions — communicating architecture decisions and implementation strategies with clarity and confidence.
• Maintain transparent and consistent communication across all delivery teams.

Have You Got What It Takes?

Experience & Education:

• Bachelor's degree in Computer Science, Information Systems, Electrical Engineering, or equivalent work experience.
• 15+ years of professional experience in software engineering or technical delivery roles, with a focus on AI, digital channels, or bot/conversational applications preferred.
• 5+ years in a technical leadership or people management role (Engineering Manager, Tech Lead, or similar).

Technical & Architecture Skills:

• 7+ years of hands-on software development experience, with at least 2–3 years in a tech lead or architect capacity.
• Strong proficiency in modern programming languages such as Java, Python, C#, or JavaScript/TypeScript.
• Deep knowledge of AWS Cloud services and AWS Knowledge Hub; familiarity with Azure or GCP is a plus.
• Proven experience working with AI/ML models, Generative AI frameworks, and enterprise AI orchestration patterns.
• Strong expertise in:
• Web APIs, SOAP, and REST implementations
• Modern authentication standards (OAuth2, OIDC, SAML)
• Browser and web security (CORS, X-Frame Options)
• HTML/CSS and front-end fundamentals
• Prompt engineering and AI integration patterns
• Solid understanding of CI/CD pipelines, DevOps practices, and software architecture principles.
• Proficiency in databases (SQL/NoSQL) and data integration patterns.
• Strong understanding of conversational UX, AI-driven interfaces, and enterprise AI platforms.

Leadership & People Management:

• Demonstrated experience managing and growing engineering teams, including performance management and career development planning.
• Ability to define technical vision, establish engineering standards, and align team deliverables with organisational goals.
• Strong stakeholder management skills, including handling escalations and influencing at senior levels.
• Experience driving technical roadmap planning across multi-disciplinary teams.

Communication & Collaboration:

• Clear, confident written and verbal communication skills.
• Comfortable engaging with customers and senior stakeholders to articulate technical decisions, solution architecture, and delivery strategy.
• Effective leader in design reviews, sprint planning, technical discussions, and delivery execution.

Delivery & Process:

• Experience defining and improving engineering processes, documentation standards, and delivery governance.
• Strong track record of authoring and reviewing design documents, functional requirements, test strategies, and deployment guides.
• Experienced in Agile/Scrum environments with a focus on predictable, high-quality delivery.
• Willingness to work in US shift hours (5 PM – 2 AM IST).

You Will Have an Advantage If You Also Have:

• Hands-on experience with NICE CXone products or other cloud-based contact centre platforms.
• Experience with enterprise conversational AI platforms such as NICE CXone, Kore.ai, Amelia, Dialogflow, or similar.
• Exposure to Generative AI tools, LLM fine-tuning, or RAG-based architectures.

What's in It for You?

Join an ever-growing, market-disrupting, global company where the teams — comprised of the best of the best — work in a fast-paced, collaborative, and creative environment. As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

Enjoy NiCE-FLEX! At NICE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility — 2 days working from the office and 3 days of remote work each week. Office days focus on face-to-face collaboration, where teamwork and creative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10786

Reporting Into: Director , Engineering 

Role Type: People Management

So, What's the Role All About?

We are looking for a Specialist Software Architect to lead the architectural vision, design, and evolution of our AI-driven and Conversational Solutions platform. This role demands deep hands-on expertise in Python, AWS Cloud services, AWS Knowledge Hub, and multiple Knowledge Base technologies, along with proven experience designing simplified, scalable, and resilient architectures using microservices and AWS-native services.

You will play a critical role in shaping the technical foundation of our Conversational AI platform — one that handles millions of interactions per day, meets strict SLAs (99.99%), and supports zero-downtime deployments, robust disaster recovery, and enterprise-grade AI orchestration. You will be the go-to architect for proposing pragmatic, simplified designs that balance innovation with operational excellence.

How Will You Make an Impact?

Architecture & System Design:

• Own and define the end-to-end architecture of the Conversational AI and Knowledge platform, covering AI model integration layers, data stores, knowledge bases, and external integrations.
• Design enterprise-scale, cloud-native, microservices-based architectures capable of handling high concurrency, burst traffic, and real-time conversational workloads.
• Propose simplified, cost-effective architectural designs leveraging AWS-native services — avoiding over-engineering while ensuring scalability and resilience.
• Define reference architectures, architectural blueprints, and non-functional requirements (NFRs) for performance, reliability, security, and maintainability.
• Drive event-driven and asynchronous architectures using AWS-native services such as SQS, SNS, EventBridge, and Step Functions.
• Define best practices for microservices design, domain-driven design (DDD), API design (REST, async/event APIs), and AI integration patterns.
• Review and guide complex application-level designs, critical code paths, and AI pipeline architectures.

AI & Conversational Solution Architecture:

• Architect and evolve AI-driven Conversational solutions integrating large language models (LLMs), prompt engineering patterns, and enterprise AI orchestration frameworks.
• Design and implement Knowledge Base solutions using AWS Knowledge Hub, vector databases, RAG (Retrieval-Augmented Generation) architectures, and other knowledge management technologies.
• Define AI model integration strategies — including model selection, fine-tuning approaches, embedding pipelines, and response quality frameworks.
• Drive conversational UX architecture, ensuring seamless, context-aware, and low-latency interaction flows.
• Evaluate and recommend AI tooling, platforms, and frameworks aligned with business needs (e.g., AWS Bedrock, LangChain, OpenAI, Anthropic, Kore.ai, Dialogflow).
• Lead the design of multi-turn conversation management, intent resolution, and fallback handling architectures.

AWS Cloud & Microservices Architecture:

• Architect and optimise solutions using AWS services including but not limited to Lambda, API Gateway, SQS, SNS, Step Functions, DynamoDB, Aurora Serverless, S3, Bedrock, and Kendra.
• Design cost-efficient, elastic scaling strategies aligned with unpredictable conversational AI workloads.
• Lead cloud governance, environment isolation, multi-account strategy, and infrastructure-as-code (IaC) practices.
• Define CI/CD pipeline standards, DevOps practices, and containerisation approaches (Docker, Kubernetes) for AI workload deployments.
• Drive microservices decomposition strategies — identifying service boundaries, inter-service communication patterns, and data ownership models.

Scalability, Resilience & Disaster Recovery:

• Design for extreme scale — high concurrent users, high TPS, and real-time AI inferencing demands.
• Own resilience strategies including multi-AZ and multi-region architectures, active-active or active-passive DR setups, and graceful degradation mechanisms.
• Define and validate RPO/RTO goals, conduct chaos testing, and lead DR drills.
• Ensure zero-downtime deployment capabilities through blue/green, canary, and rolling deployment strategies.

Security, Compliance & Reliability:

• Embed security by design across all AI and data architecture layers — covering authentication, authorisation, data privacy, encryption, and model safety guardrails.
• Support compliance requirements (SOC2, ISO, GDPR) from an architectural standpoint, particularly around AI data handling and knowledge base access controls.
• Partner with SRE and DevOps teams on observability, logging, distributed tracing, and alerting for AI workloads.
• Define SLIs, SLOs, and capacity planning models for conversational AI services.

Technical Leadership & Collaboration:

• Act as a technical mentor and trusted advisor to senior engineers, tech leads, and implementation teams.
• Lead architecture reviews, design councils, and technical decision forums — championing simplicity, pragmatism, and long-term maintainability.
• Partner closely with Product Management, AI/ML teams, and delivery teams to balance innovation with execution feasibility.
• Drive the long-term AI architecture roadmap and proactively reduce technical debt.

Have You Got What It Takes?

Experience & Education:

• Bachelor's degree in Computer Science, Information Systems, Electrical Engineering, or equivalent work experience.
• 10+ years of professional software engineering experience, with at least 4–5 years in a software architect or principal engineer role.
• Demonstrated experience designing and delivering AI-driven or Conversational AI platforms at enterprise scale.

Technical Expertise:

• Deep hands-on experience with Python — including AI/ML libraries, API development, and automation scripting.
• Strong expertise in AWS Cloud services — particularly those relevant to AI workloads: Bedrock, Kendra, Lambda, API Gateway, SQS, SNS, Step Functions, DynamoDB, S3, and Aurora Serverless.
• Hands-on experience with AWS Knowledge Hub and multiple Knowledge Base technologies including vector databases, document stores, and semantic search platforms.
• Proven experience designing microservices architectures — including service decomposition, inter-service communication (REST, gRPC, event-driven), and distributed data management.
• Strong understanding of:
• RAG (Retrieval-Augmented Generation) architectures and embedding pipelines
• Prompt engineering and LLM integration patterns
• Modern authentication standards (OAuth2, OIDC, SAML)
• Web APIs — REST and async/event API design
• Databases (SQL/NoSQL) and data integration patterns
• Experience with CI/CD pipelines, DevOps practices, and containerisation (Docker, Kubernetes).
• Familiarity with AI tooling and platforms such as AWS Bedrock, LangChain, OpenAI, Anthropic, Dialogflow, or Kore.ai.
• Experience with GenAI and Agentic AI application development.

Architecture & Scale:

• Demonstrated success designing systems for high traffic, low latency, and high availability at global scale.
• Deep experience with resilience, disaster recovery, and failover design in cloud-native environments.
• Strong track record of proposing simplified, pragmatic architectural solutions that avoid unnecessary complexity.
• Experience with event-driven systems, message queues, and streaming architectures.
• Strong understanding of cloud networking, caching strategies, and data modelling for AI workloads.

Good to Have:

• Experience with CCaaS or real-time communication platforms (e.g., NICE CXone).
• Exposure to multi-region SaaS deployments and hybrid serverless/container architectures.
• Familiarity with OpenSearch or Elasticsearch for conversational data search and analytics.
• Experience with cost optimisation strategies at scale on AWS.
• Knowledge of frontend technologies (JavaScript/TypeScript, React) for full-stack architecture awareness.

What's in It for You?

Join an ever-growing, market-disrupting, global company where the teams — comprised of the best of the best — work in a fast-paced, collaborative, and creative environment. As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

Enjoy NiCE-FLEX! At NICE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility — 2 days working from the office and 3 days of remote work each week. Office days focus on face-to-face collaboration where teamwork and creative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. 

Requisition ID: 10787

Reporting Into: Director , Engineering

Role Type: Individual Contributor 

Smartsheet is establishing a new Enterprise Insights & Intelligence team to centralize ownership of corporate metrics, analytics governance, and self-serve data enablement. This is a foundational hire — you will help build this function from the ground up, with direct visibility to senior leadership and the opportunity to shape how the entire organisation consumes and trusts its data.

We are looking for a Senior Business Intelligence Engineer who can operate across three strategic pillars: automating and governing corporate executive reporting, standardising metrics and reporting practices at scale, and enabling self-serve and AI-powered data solutions. Day to day, this means you could be building an automated executive scorecard, codifying metric definitions into a governed semantic layer, standing up an AI agent that lets business users query trusted data in natural language, or leading enablement sessions on our analytics platforms. The thread connecting all of it is ensuring that Smartsheet's data is trusted, consistent, accessible, and ready for both human and AI consumption.

This is not a traditional reporting or data science role. You will work across dbt, MetricFlow, Snowflake, and Databricks to build the governed data layer that underpins everything — from board-level scorecards to LLM-powered insights to self-serve dashboards.

You Will

• Design, build, and maintain governed metric models — standardised, reusable definitions of business KPIs that dashboards, reports, and AI agents all query from a single source of truth
• Own the automation and maintenance of corporate scorecards and executive reporting (SLT/XLT), ensuring trusted, timely data with AI-powered anomaly detection and alerting
• Conduct deep dives on key KPIs and company goals, surfacing actionable insights and translating short- and long-term business priorities into data-driven recommendations shared via reviews and async updates
• Lead metric certification and governance — maintain a centralised KPI glossary, standardise dashboards, and retire stale reporting assets
• Build AI agent integrations (MCP servers, skills, subagents) that allow tools like Claude and Snowflake Cortex to query enterprise data through the semantic layer with metric-correct SQL
• Drive self-serve analytics enablement — documentation, training, dashboard quality checks, and experimentation governance across Amplitude, Tableau, and other platforms
• Partner with Product, Engineering, Finance, GTM, and Customer Success to align metric definitions and data sources cross-functionally
• Translate qualitative UX signals and customer feedback into measurable data pipelines

You Have

• Bachelor's degree (B.Tech / B.E. / B.Sc.) in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field
• 5+ years of experience in analytics engineering, BI engineering, data engineering, or a closely related role
• Experience with KPI design and insight generation — ability to define meaningful metrics, analyse trends, identify anomalies, and communicate findings that drive business decisions
• Familiarity with dbt (dbt Core or dbt Cloud) and concepts like YAML-based metric definitions and reusable data models; hands-on experience is a plus but not required
• Deep SQL expertise with experience working in cloud data platforms such as Snowflake and/or Databricks
• Experience building semantic layers, governed data models, or canonical metric definitions for downstream consumption
• Working familiarity with AI/LLM tooling — concepts such as MCP (Model Context Protocol), agentic frameworks, or tool-use patterns for large language models
• Proficiency with one or more BI/visualisation tools (Tableau, Amplitude, or similar)
• Strong cross-functional collaboration skills and excellent async communication across time zones (IST / US Pacific overlap expected)
• A proactive, ownership-driven mindset — comfortable building new processes and standards in a greenfield environment

Preferred Qualifications

• Experience building AI agent skills, subagents, or MCP server integrations for LLMs
• Hands-on experience using agentic coding platforms (Claude Code, Cursor, Windsurf, etc.) to streamline and automate analytics workflows
• Software engineering experience (Python, JavaScript/TypeScript) with the ability to contribute to application-level instrumentation code
• Experience with event taxonomy design, behavioural analytics pipelines, or product instrumentation (Amplitude, Segment, etc.)
• Familiarity with metric governance frameworks, data catalogues, or data quality tooling
• Prior experience working in a SaaS or enterprise software environment

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI & Data Governance Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Develop and enforce AI&Data governance frameworks, including bias detection, explainability, and model lifecycle management
• Ensure adherence to data privacy laws and security regulations, managing risks in AI and data pipelines
• Implement data lineage, metadata, data management, and quality frameworks
• Implementing tools to track data from its source to the final AI output. If a model breaks, you need to know exactly which data point caused the drift
• Define roles for data custodians, users, and AI developers, promoting transparency and fairness.
• Partner with Legal, Data Engineering, and Security teams to embed security and privacy into AI workflows and data products
• Implement governance tools (e.g., Collibra, Informatica) and automate audit procedure
• Oversee data stewardship to ensure data accuracy, integrity, and privacy throughout its lifecycle
• Designing and enforcing the rules for how data is collected, stored, and used—specifically focusing on data privacy (GDPR, CCPA) and AI regulations (like the EU AI Act).
• AI Ethics & Bias Mitigation: Establishing "Responsible AI" standards. This involves auditing models for algorithmic bias, ensuring transparency (Explainable AI), and managing the ethical implications of automated decision-making
• Risk Management through Identification of Shadow AI (unauthorized use of AI tools) and managing the risks associated with third-party LLM providers
  
  

You Have:

• Experience in AI Governance across foundational pillars like AI Organization, Legal, Regulatory Compliance, Ethics, Transparency, Interoperability, Data/AIOps Infrastructure, AI protection and Security
• AI Risk Assessment & Management, Auditability & Transparency, AI Policy Development
• Databricks AI Governance Framework (DAGF), Databricks Security Framework (DASF), MLFlow, Unity Catalog, RAG Governance
• Programming languages like Python and SQL
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• In-depth understanding of AI, GenAI, LLMs, data quality assessment, and metadata management.
• Regulatory Knowledge in GDPR, EU AI Act, and industry-specific regulations (e.g., HIPAA, Financial Services)
• Lineage Tracking with automatic capture of end-to-end data flow (from ETL to BI/AI) to understand dependencies.
• Auditability with centralized logs to allow compliance teams to monitor access and usage of data and AI models
• Knowledge of tools for Model Auditing towards Bias detection,, monitoring, and mitigating bias
• Understanding of data masking, encryption, and SOC2
• Certifications like CIPP (Privacy), CDMP (Data Management), or specialized AI ethics certifications is preferable
• Enterprise SaaS software solutions with high availability and scalability
• Legally eligible to work in India on an ongoing basis

We are hiring a Senior Offensive Security Engineer to build, run, and mature BitGo's offensive security program end-to-end across AI, Web2, and Web3. This is not a point-in-time pentesting role. You will own program strategy, assessment execution, tooling and automation (including AI-powered offensive agents), reporting, remediation validation, retesting, and continuous improvement — moving BitGo from periodic external tests to an always-penetration-testing posture.

What You'll Do

• Own the offensive security program across BitGo's applications, APIs, cloud infrastructure, signing services, wallet-adjacent systems, identity pathways, and AI-enabled workflows.
• Run deep, hands-on assessments of Web3 and digital asset systems — transaction signing pipelines, MPC/TSS implementations, HSM integrations, multi-party approval workflows, smart-contract-connected services, and chain-facing infrastructure.
• Lead offensive testing of AI and agentic systems — prompt injection, unsafe tool use, data leakage, agentic identity/credential abuse, LLM routing flaws, and the OWASP Top 10 for LLM Applications.
• Build continuous automated validation pipelines that run 24/7, leveraging autonomous AI agents for breadth while you focus on depth, creative adversary simulation, and novel attack chains.
• Integrate offensive testing into CI/CD so every significant deployment to critical systems is validated before it reaches production.
• Run purple-team exercises simulating nation-state TTPs and insider-threat scenarios, and progress from transparent to semi-stealth to full red team operations as the program matures.
• Drive remediation and retesting with Engineering, AppSec, Cloud Security, Detection Engineering, and SecOps — and translate recurring patterns into durable architectural improvements.
• Serve as the internal expert on offensive risk in launch reviews, design reviews, and strategic initiatives, with authority to hold launches pending security validation of critical systems.

What We're Looking For

• 5+ years in offensive security, red teaming, advanced penetration testing, adversary simulation, or security research in modern production environments. We will consider less with an exceptional track record (published CVEs, top bug bounty results, CTF rankings, Code4rena/Sherlock audit placements, Black Hat / DEF CON / DARPA research).
• Proven experience building or materially maturing an internal offensive security program — defining methodology, building tooling, and driving strategy — not just executing assessments.
• Digital asset security depth or strong demonstrated aptitude — custody infrastructure, transaction signing systems, wallet security, key management, MPC/TSS, or blockchain security research.
• Strong software engineering capability in Python, Go, TypeScript, or similar, including building custom offensive tooling.
• Cloud-native fluency across AWS, containers, Kubernetes, IAM, secrets management, and CI/CD security.
• Clear, credible written and verbal communication with engineers and senior leadership, with high judgment and a bias toward reducing real-world risk.

Strongly Preferred

• OSCP, OSWE, OSEP, GPEN, CPTS, or equivalent practical capability.
• Experience assessing AI / agentic systems; proficiency with PyRIT, Garak, Promptfoo, or similar.
• Experience building or deploying autonomous AI agents for offensive testing.
• Browser security, modern web exploitation, exploit development, or reverse engineering background.
• Open-source security contributions, published research, or conference talks (Black Hat, DEF CON, blockchain security venues).
• Background in high-assurance financial, fintech, or regulated environments.

Why This Role

This is a career-defining opportunity. You will build an offensive security program from scratch at one of the most critical infrastructure providers in digital assets — with a direct line to the Deputy CISO, visibility to the CEO, and a path to leading a growing team during the most significant security transformation this industry has seen in a decade.

Why Join BitGo?

Disrupting an industry takes vision, innovation, passion, technical chops, drive to deliver, collaboration, and execution. Join a team of great people who strive for excellence and personify our corporate values of open communication, collaboration, accountability, craftsmanship, and a client first approach. We are looking for new colleagues who bring innovative ways of thinking and problem solving, and who want to be part of the team that changes the world’s financial markets.

Here are some of the benefits of working at BitGo:

• Competitive salary
• IT equipment support for work
• Meal & Commute allowance
• Medical Insurance
• Attractive Well-being allowance (comprises of medical, wellness and fitness aspects)
• Snacks: on-the-house in the Bangalore office
• Great/Talented workforce to learn and grow with

Note: This role requires working onsite (Monday to Friday) at the Bangalore office.

Cryptocurrencies are the most disruptive change the financial services industry has seen in years. Join us and you’ll be able to look back and say you were part of the team that transformed finance.

As a Staff Data Scientist, you will act as a senior technical leader and trusted advisor across multiple teams. You’ll guide stakeholders through the complexity of modern AI systems, with a particular focus on agentic AI architectures (including LangGraph, LangFuse, and related tooling), as well as broader machine‑learning strategy. This role blends deep technical expertise, consultative problem‑solving, and cross‑functional leadership. 

You will often support several initiatives simultaneously, helping teams understand feasibility, scope, and risk while shaping high‑impact AI solutions that align with business needs. You’ll also mentor junior colleagues, elevate data‑science practices, and contribute hands‑on to the development of production‑grade AI systems. 

What you'll do:

AI Consulting & Advisory 

• Partner with product, engineering, and business teams to translate ambiguous problems into clear AI opportunities. 

• Provide expert guidance on agentic AI, including workflow orchestration, evaluation, observability, and safety. 

• Assess the complexity, feasibility, and expected value of proposed AI initiatives, helping teams prioritise effectively. 

• Communicate trade‑offs, risks, and solution paths to both technical and non‑technical audiences. 

AI & ML Solution Design 

• Architect end‑to‑end AI systems that solve real business problems, from early discovery through deployment. 

• Design agent‑based workflows, retrieval‑augmented pipelines, and ML‑powered automation. 

• Define evaluation strategies, data requirements, and success metrics for AI features and products. 

• Collaborate with engineering teams to ensure solutions are scalable, maintainable, and aligned with platform strategy. 

Hands‑On Technical Work 

• Build prototypes, proof‑of‑concepts, and production‑ready components using Python, modern AI frameworks, and cloud tooling. 

• Develop and refine agentic AI workflows using LangGraph, LangChain, LangFuse, or similar frameworks. 

• Implement machine‑learning models, retrieval systems, and data pipelines where needed. 

• Contribute to internal libraries, tooling, and best practices for AI development. 

Leadership & Mentorship 

• Mentor junior and mid‑level data scientists, providing guidance on modelling, experimentation, and system design. 

• Lead technical discussions, design reviews, and cross‑team collaboration sessions. 

• Champion high standards for code quality, documentation, and reproducibility. 

• Help shape the long‑term AI strategy and technical roadmap, through your technical knowledge on the art of the possible, and the business problems our clients face. 

What you'll bring:

• Extensive experience in data science, machine learning, or applied AI, including hands‑on coding in Python and common data science libraries, such as Numpy, Scipy, Pandas, SKlearn, Spacy. 

• Ability with prototyping frameworks such as Dash. 

• Good working understanding of code version control with Git. 

• Experience with big data tools, such as: Spark, Dask, or alternatives. 

• Strong understanding of agentic AI, orchestration frameworks, and LLM‑based system design. 

• Ability to evaluate project complexity, identify risks, and guide teams toward pragmatic solutions. 

• Experience designing and delivering AI systems in production environments. 

• Excellent communication skills and the ability to influence beyond your immediate team. 

• Great mentoring skills. 
• Comfort working across multiple projects and shifting priorities. 

Nice to Have 

• Experience with observability and evaluation tools such as LangFuse, Weights & Biases, or similar. 

• Familiarity with agentic evals and prompt‑engineering patterns. 

• Background in consulting, technical advisory, or cross‑functional leadership roles. 

• Experience with cloud platforms (AWS, GCP, Azure) and modern MLOps practices. 

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.
 

As Senior Analyst in our Model Risk Management team, you will help manage the Model Risk Program including completing model validation reviews, maintaining the model risk inventory, and monitoring model performance particularly for Fraud and Gen AI Models. You will work closely with the Data Science Team, architects, engineers and product managers to assess the risk of model design, implementation, and use across product lines.

A day in the life (Responsibilities) 

• Support the implementation and day-to-day execution of the Second Line of Defense (2LOD) Model Risk Management (MRM) program for high-risk models, with particular focus on Fraud detection models (Transaction Fraud & Merchant Fraud) and Generative AI / LLM-based systems deployed across Toast.
• Assist in maintaining and enhancing the Model Risk Management framework, including policies, procedures, validation standards, governance documentation, templates, and best practices aligned with evolving regulatory and industry expectations.
• Enforce model lifecycle standards across development, implementation, use, monitoring, recalibration, change management, governance, and decommissioning, ensuring appropriate controls for traditional ML models as well as GenAI systems (e.g., RAG architectures, copilots, AI-assisted decision tools).
• Contribute to the development, risk-tiering, and ongoing maintenance of a comprehensive model inventory, including assessment of model impact, intrinsic risk (complexity and methodology), reliance on model outputs, and emerging AI-specific risks.
• Perform independent model validation reviews under the guidance of senior leadership, covering conceptual soundness, data integrity, model methodology, performance metrics (e.g., AUC, precision/recall, calibration), stability, bias/fairness risk, explainability, and monitoring frameworks. Produce validation reports and track issue remediation plans through closure.
• For Fraud models, evaluate class imbalance handling, threshold optimization, cost-sensitive performance metrics, operational overlays, rule-based controls, and portfolio-level impact analyses.
• For Generative AI systems, validate systems and evaluate risks related to hallucination, prompt injection, adversarial vulnerabilities, data privacy and leakage, model explainability limitations, bias, guardrails, output monitoring, jailbreak testing, regression testing, and human-in-the-loop controls.
• Partner with Data Science, Data Engineering, Product/Engineering, Information Security, Legal/Compliance, Finance, Credit Risk and Business teams to obtain documentation, perform effective challenge, conduct validation and oversee performance monitoring
• Prepare reports and executive materials summarizing model risk issues, validation findings, monitoring insights, and remediation status for leadership review, risk committees, audit committees, and internal audit engagements.
• Research and stay informed on industry developments in fraud analytics, machine learning, Generative AI governance, and regulatory guidance (e.g., SR 11-7, OCC 2011-12, NIST AI RMF). Propose enhancements to strengthen Toast’s Model Risk and AI Governance framework.
• Contribute to the development of model risk training materials and support delivery of training sessions to key stakeholders to enhance awareness of fraud model risk and AI-related risks.
• Support ad-hoc initiatives related to model risk governance, AI oversight, regulatory compliance, and enterprise risk management enhancements.

What you'll need to thrive (Requirements)

• Advanced degree in Data Science, Statistics, Applied Mathematics, Computer Science, Engineering, or a related quantitative discipline
• 5+ years of relevant industry experience in Model Risk Management, Model Validation, Data Science, or Machine Learning within fintech, banking, payments, technology, or consulting environments, with exposure to fraud analytics, credit risk, or AI/ML model governance.
• Strong understanding of machine learning methodologies and statistical foundations, including model development, validation techniques, performance evaluation, calibration, and stability analysis.
• Hands-on experience with fraud detection models (e.g., transaction monitoring, chargeback prediction, merchant risk scoring) and familiarity with concepts such as class imbalance handling, threshold optimization, precision/recall trade-offs, and cost-sensitive evaluation.
• Familiarity with Generative AI and LLM-based systems (e.g., RAG architectures, embeddings, prompt engineering, AI copilots) and awareness of associated risks such as hallucination, bias, prompt injection, and data leakage.
• Strong proficiency in Python and SQL; experience with data science and ML tools such as Spark, scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Familiarity with software engineering best practices (version control, CI/CD, testing frameworks, Airflow, AWS or cloud platforms) is a plus.
• Knowledge of model risk management frameworks and regulatory guidance (e.g., SR 11-7, OCC 2011-12) and familiarity with emerging AI governance frameworks (e.g., NIST AI RMF) is highly desirable.
• Ability to translate complex quantitative methodologies into clear business insights and effectively challenge first-line model development teams while maintaining strong cross-functional partnerships.
• Demonstrated critical thinking, analytical rigor, and structured problem-solving skills, with the ability to manage multiple priorities and deliver high-quality outputs under tight deadlines.
• Excellent written and verbal communication skills, including experience drafting formal validation reports, executive summaries, and committee-level materials.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy

We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

About the role 

The Senior Integration, API & Automation Engineer is a hands-on technical lead role responsible for shaping and executing Rubrik’s enterprise API, integration, and AI‑driven automation strategy.

Broadly, the role will focus on designing, building, and governing secure, scalable APIs and integrations between our core business platforms and third‑party systems (e.g., ERP, HCM, CRM, data platforms), while mentoring engineers and driving best practices across the organization. In addition, this role will help us embed AI capabilities (LLMs, Claude, decisioning services, intelligent workflows) into APIs and business processes to improve reliability, productivity, and insight.

You will work closely with senior business stakeholders, application owners, security, data, and IT teams to define API‑first, AI‑aware integration patterns and standards that deliver robust, secure, real‑time and batch integrations using REST APIs, webhooks, messaging, file‑based interfaces, and AI services.

This role will primarily leverage MuleSoft Anypoint Platform (or similar iPaaS) for API‑led connectivity and sits within the Enterprise Integrations & Intelligent Automations team as a key technical authority.

What you'll do

• Own the API and integration architecture and strategy for assigned domains, defining API‑led patterns (Experience, Process, and System APIs), reference architectures, and standards for how systems integrate across the enterprise.
• Design, build, and evolve RESTful APIs that expose well‑designed resources and operations to internal and external consumers, with clear contracts, documentation, and SLAs.
• Lead implementation of integrations between SaaS and on‑prem applications (e.g., NetSuite, Workday, Salesforce, Snowflake, ServiceNow), Finance, HR, Security, and GTM platforms, ensuring solutions are scalable, secure, resilient, and observable.
• Create data integration strategies for high volumes of data in transit, optimizing for performance, reliability, and cost (e.g., streaming vs. batch, push vs. pull APIs, caching, backoff strategies).
• Define and enforce API governance, including:
• Provide technical leadership to integration and API engineers, including solutioning, design reviews, code reviews, and mentoring of junior and contract engineers.
• Implement and manage REST/SOAP APIs, webhooks, and messaging interfaces from conceptual design through development, performance testing, deployment, and lifecycle management via an API gateway or iPaaS (e.g., MuleSoft Anypoint Platform).
• Architect robust data integrations for both real‑time and scheduled (batch) workloads using APIs, messaging, sFTP, and file‑based exchanges (JSON, XML, CSV), with well‑defined contracts, SLAs, and monitoring.
• Define non‑functional requirements (NFRs) and SLAs for APIs and integrations—availability, latency, throughput, error budgets, RTO/RPO—and ensure designs and implementations meet or exceed them.
• Drive observability and reliability for APIs and integrations by standardizing logging, tracing, metrics, dashboards, and alerting, and by creating operational runbooks for incident response and post‑incident reviews.

AI & Intelligent Automation Responsibilities

• Identify and prioritize AI opportunities within API and integration flows (e.g., data enrichment, anomaly detection, routing, summarization, classification, intent extraction).
• Define safe and governed AI usage within APIs and integrations, including:
• Clear input/output contracts for AI services
• Guardrails (prompt design, validation, constraints)
• Handling of sensitive data (PII/financial/HR data) in prompts and responses
• Monitoring for model performance and drift in production.
• Integrate with AI platforms and services (internal or external), including model APIs, vector stores, and feature stores, using strong API design and security practices.

Stakeholder, Security, and Platform Responsibilities

• Partner with security, compliance, and audit teams to ensure integrations, APIs, and AI services meet security, privacy, and regulatory requirements (e.g., SOX‑sensitive data flows, access control, encryption, audit trails).
• Lead technical discovery and solution design for new API, integration, and AI‑automation initiatives, working with product managers, application owners, and business stakeholders to shape requirements and translate them into well‑defined technical designs.
• Own vendor and platform technical relationships for integration technologies and key SaaS systems; understand vendor APIs and change roadmaps, anticipate the impact of deprecations, and coordinate upgrades and migrations.
• Oversee CI/CD practices for APIs, integrations, and AI services, including branching and release strategies, automated testing (unit, integration, regression), and environment configuration management for Dev/QA/UAT/Prod.
• Champion reuse and standardization by building and curating shared assets such as:
• Generic APIs (e.g., email, JIRA, logging, AI utility services)
• Common connectors and API client libraries
• Templates and integration catalogs
  and ensuring they are adopted broadly.
• Participate in and improve KTLO/on‑call rotations for critical APIs, integrations, and AI services, using incident data to drive structural improvements, technical debt reduction, and increased reliability.
• Communicate clearly with technical and non‑technical audiences, producing architecture diagrams, decision records, and documentation that make complex API, integration, and AI solutions easy to understand, operate, and evolve.

Experience you'll need

• Education & Experience

  • Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or equivalent practical experience.
  • 10+ years of overall software/integration engineering experience, with 8+ years focused on API and enterprise integrations.
  • 4+ years in a senior/lead/architect capacity, owning API and integration designs, patterns, and technical decisions for complex cross‑system and enterprise application solutions.
  • Experience designing and delivering AI‑enabled features or workflows as part of production systems (e.g., integrating with LLM or ML APIs, AI‑based decisioning, or intelligent automation).

Technical Skills – API Engineering

• Deep expertise in RESTful API design and implementation, including:
• Resource modeling, URI design, and standard HTTP methods
• API‑first/contract‑first design (RAML/OpenAPI)
• Pagination, filtering, sorting, and partial responses
• Versioning strategies (URL, header, content negotiation)
• Idempotency and robust error handling patterns.
• Strong experience building secure, resilient, and scalable APIs, including:
• API gateways (e.g., MuleSoft, Apigee, Kong, AWS API Gateway)
• Rate limiting, throttling, caching, and circuit‑breaker patterns
• Timeout, retry, and backoff strategies.
• Solid understanding of webhooks and event‑driven APIs, including subscription management, signature validation, replay protection, and idempotent consumers.
• Hands-on experience with API client development and integration patterns (SDKs, service‑to‑service communication, backend‑for‑frontend, composite APIs).

Technical Skills – Integration & Platforms

• Strong experience with MuleSoft Anypoint Platform (or equivalent iPaaS), including API Manager, Runtime Manager/CloudHub, Anypoint Exchange, and design/deployment best practices.
• Solid understanding of SOAP services, messaging patterns (pub/sub, event‑driven integrations), and when to apply each.
• Proficiency with integration data formats and transformation (JSON, XML, CSV, mapping, enrichment, aggregation, canonical models).
• Strong database and data modeling skills, including SQL and working with relational databases (e.g., Postgres, SQL Server, Oracle) in integration scenarios.
• Experience designing and implementing secure integrations, including:
• OAuth 2.0/OpenID Connect
• API keys and mutual TLS
• Role/permission models and fine‑grained authorization
• Secrets management (e.g., HashiCorp Vault, cloud KMS).
• Hands‑on experience with CI/CD pipelines and Git‑based workflows, including automated testing, static analysis, deployment automation, and environment configuration for API and integration services.
• Demonstrated experience integrating with several of the following: NetSuite, Workday, Salesforce, Snowflake, ServiceNow, Coupa, DocuSign, ChromeRiver, Marketo, identity/IAM platforms, external APIs, and internal APIs.
• Practical experience working with AI/ML or LLM APIs (e.g., OpenAI, Azure OpenAI, Vertex AI, Bedrock, or internal model APIs), including:
• Designing API requests and responses for AI‑backed features
• Prompt engineering and response validation
• Handling rate limits, retries, timeouts, and partial failures within integration flows.
• Familiarity with event‑driven and streaming architectures (e.g., Kafka, EventBridge, Event Hubs) and how to combine them with AI services for near real‑time decisioning and automation.

Soft Skills

• Proven ability to lead without direct authority, influencing cross‑functional teams and driving technical decisions through clarity and data rather than hierarchy.
• Strong architectural thinking and problem‑solving skills, including the ability to decompose complex business processes into robust API, integration, and AI‑enabled designs.
• Excellent communication and documentation skills, comfortable presenting solutions and trade‑offs to engineers, managers, and senior business stakeholders.
• Experience working in agile environments, collaborating closely with product owners, scrum teams, and distributed stakeholders across time zones.
• Bias toward automation, standardization, and continuous improvement, with a pragmatic approach to balancing speed, risk, and long‑term maintainability.

Preferred Qualifications

• Professional MuleSoft certifications (e.g., MuleSoft Certified Integration Architect, MuleSoft Certified Developer) or equivalent certifications from other integration platforms.
• Experience designing and operating public or partner-facing APIs with clear productization (API lifecycle, developer experience, SLAs, and commercial considerations).
• Experience designing and operating integrations in regulated or security‑sensitive environments (e.g., SOX, FedRAMP, customer‑facing APIs) with a strong emphasis on auditability and change control.
• Experience with event‑driven and streaming platforms (e.g., Kafka, AWS EventBridge, Azure Event Hubs) and their role in modern API and integration architectures.
• Exposure to automation/workflow platforms (e.g., Zapier, Workato, low‑code tools) and how they complement enterprise integration layers and AI‑based automation.
• Experience building and maintaining API and integration runbooks, catalogs, and governance processes, and contributing to enterprise architecture forums or design reviews.
• Experience with observability stacks (e.g., Datadog, Splunk, New Relic, OpenTelemetry) for monitoring APIs, integrations, and AI services in production.
• Familiarity with data and AI governance concepts (e.g., data classification, lineage, model governance, responsible AI practices) and how they apply within API, integration, and automation patterns.

Overview:

We are building the next generation of our SaaS platform, and we need someone to own the quality architecture that makes it all trustworthy. As a Principal Technology Architect - QA, you will design the systems, standards, and governance that raise the bar for quality across every product segment we ship.

We are an AI-first organization. You will put that into practice by bringing AI-driven testing, intelligent automation, and modern quality tooling into the way our teams work every day. This is a hands-on architecture role, not a policy desk. You will build test frameworks, design quality gates, set reliability targets, and create the shared infrastructure that teams actually adopt because it makes their lives easier.  You will work closely with engineering leadership to connect quality strategy to business outcomes. When you recommend a change, people across the org will listen, because your technical credibility and track record back it up.  You will also mentor engineers, shape how we hire for quality mindset, and help grow the next generation of technical leaders on our teams.  If you get excited about solving hard problems at scale, rethinking how quality works in a modern SaaS org, and leaving things better than you found them, we would love to talk.

What you will do:

• Set the quality architecture direction for the org: design quality gates, define reliability targets, and choose the testing infrastructure that all product segments build on.
• Build and maintain a governance model for quality practices so that standards, processes, and tooling are adopted consistently across engineering teams.
• Design and deliver scalable test automation frameworks that teams can adopt and extend to improve coverage, speed, and confidence in every release.
• Bring AI into quality engineering: evaluate and roll out AI-driven test generation, intelligent test selection, defect prediction, and automated monitoring.
• Own the performance and resilience strategy: set performance budgets, define monitoring standards, and create disaster recovery and incident response frameworks.
• Partner with product and engineering leaders to balance release velocity with system health, making sure teams can ship fast without cutting corners on quality.
• Evaluate and introduce new tools, patterns, and practices that keep our quality approach current as the platform and industry evolve.
• Mentor engineers across teams, raise the bar on how we hire for quality mindset, and contribute to engineering maturity across the organization.
• Represent Precisely externally as a thought leader in quality engineering through talks, writing, or industry engagement.

What we are looking for:

Required:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Equivalent work experience is accepted in place of a degree. An advanced degree is a plus.
• Experience: 15+ years of progressive experience in software quality engineering, test architecture, or related technical leadership roles, with demonstrated org-wide architecture leadership
• Quality architecture: Deep expertise in test automation frameworks, CI/CD pipeline design, quality gate implementation, and testing strategies for large-scale SaaS platforms.
• AI: Hands-on experience applying AI to quality workflows (e.g. AI-driven test generation, intelligent test selection, or automated defect detection)
• Leadership: Track record of driving adoption of technical standards across multiple teams or product areas, including working with leaders who do not report to you
• Travel is required: Yes – Approximately 10%

AI Skills/Knowledge:

• Comfortable using generative AI tools (e.g. GitHub Copilot, Claude Code, or custom LLM integrations) to accelerate day-to-day quality workflows such as test generation, defect triage, and root-cause analysis.
• Able to critically evaluate AI-generated outputs and set guardrails so that AI-produced test artifacts meet reliability, security, and compliance standards.
• Experience evaluating and integrating AI-powered quality tools (e.g. autonomous testing platforms, AI-based test maintenance, predictive analytics for defect detection) into org-wide workflows.
• Open to continuously adopting new AI capabilities as they emerge and excited to shape how the org integrates them into quality practices.

Preferred Skills:

• Experience defining and scaling quality practices across multiple product segments in a large SaaS or cloud-native organization.
• Familiarity with contract testing, chaos engineering, or advanced reliability practices (SLOs/SLIs, error budgets).
• Bonus points for experience establishing quality centers of excellence or community-of-practice models across engineering organizations.
• Exposure to security testing practices, compliance frameworks, or regulated industry quality standards.
• Experience with observability and monitoring platforms (Datadog, Splunk, Grafana, PagerDuty) at an architectural level.
• Track record of representing an organization externally through conference talks, published writing, or industry working groups in quality engineering.

#LI-SR1

As an AI Workflow Specialist on the Trust & Safety Operations team, you will be the bridge between product, operations, and other relevant teams. You will be required to create workflows, using AI to design, prototype, and scale high‑impact automations. You will translate operational pain points into well‑designed AI workflows, partner closely with product and engineering, and build the evaluation frameworks that ensure these automations are safe, reliable, and measurable.

You Will:

• Partner with the Subject matter experts across the Support Ops and Shared service teams to understand the current gap and brainstorm on the desired solution. 
• Map and document existing workflows to identify high‑leverage automation opportunities and clearly define “current vs. future state.”
• Design AI‑augmented workflows that combine LLM agents, existing rules engines, and human review to improve speed, quality, and consistency 
• Prototype and iterate AI solutions using internal and external (accepted) tooling (e.g., Claude and other LLMs, internal agentic/AI workflow platforms, and Builder AI code intelligence) to turn workflow designs into working agents or automations.
• Define success metrics and evaluation plans (e.g., automation rate, handle time reduction, error/rollback rate, reviewer satisfaction) and build or integrate with eval pipelines to measure agent performance over time.
• Partner with product, engineering, and operations to prioritize use cases, scope requirements, and align AI workflows with product roadmaps and control/compliance expectations.
• Operationalize launches: contribute to playbooks, runbooks, and training so that operations teams can use AI agents confidently and understand when and how to intervene or escalate.
• Continuously improve workflows by monitoring performance, surfacing insights, and iterating on prompts, policies, routing, and UX to keep systems robust as volumes, abuse patterns, and regulations evolve.
• Champion safe and secure AI usage, partnering with security and compliance stakeholders to ensure AI workflows respect data handling, access controls, and regulatory constraints, especially as AI workloads increase.

You Have:

• 5+ years of experience in technical operations, data science/analytics, or product/engineering roles, with at least 2+ years working directly with workflow automation, rules engines, or tooling for operations teams.
• Demonstrated experience designing, implementing, or maintaining complex business workflows 
• Strong technical fluency: comfortable reading and writing simple scripts or code (Python or similar), working with APIs, and collaborating closely with engineers to ship workflow changes and integrations.
• Hands‑on experience with LLM‑based tools (e.g., Claude) or other AI platforms, including prompt design, evaluation, and iteration to improve quality and reliability.
• Strong analytical skills, with experience defining metrics, building dashboards or analyses, and using data to make prioritization and design decisions.
• Excellent cross‑functional communication skills; able to translate between operations, product, engineering, and finance, and to write clear specs, runbooks, and status updates.

Good To Have: 

• Experience in Trust & Safety, compliance, or risk‑sensitive workflows (e.g., safety queues, fraud, government or law enforcement requests, regulatory reporting).
• Prior work evaluating AI agents or automation quality (e.g., building eval suites, gold‑label sets, or reviewer workflows to monitor agent decisions).

Position Summary:

Precision AQ’s Product Solutions team is expanding its AI and machine learning engineering capabilities in India. This role is responsible for designing, developing, deploying, and scaling production-grade AI/ML solutions that directly support Precision AQ products and productized services across oncology access, analytics, and AI-enabled offerings.

The AI/ML Engineer operates as a hands-on technical contributor, working closely with product management, engineering, data science, and research teams to translate business problems into robust, scalable AI systems. The role spans model development, optimization, deployment, and operationalization, with a strong emphasis on Generative AI, Large Language Models (LLMs), and applied machine learning in real-world production environments.

The successful candidate is technically rigorous, execution-oriented, and comfortable operating in fast-paced, multi-product environments with evolving requirements.

Essential functions of the job include but are not limited to: (This is NOT meant to be an exhaustive task list)

1. AI / ML Model Development & Optimization

• Design, develop, fine-tune, and evaluate machine learning, deep learning, and Generative AI models, including Large Language Models (LLMs).
• Apply appropriate modeling techniques (supervised, unsupervised, NLP, deep learning) based on problem context and data constraints.
• Optimize model performance across accuracy, latency, scalability, and cost dimensions.
• Conduct rigorous model evaluation, validation, and benchmarking using large-scale datasets.
• Apply data preprocessing, feature engineering, augmentation, and synthetic data generation techniques to improve model robustness.

1. Production Deployment & MLOps

• Design and implement scalable, production-ready AI solutions integrated into existing platforms and workflows.
• Build, maintain, and improve MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
• Deploy and manage AI applications in cloud environments (Azure, AWS, or GCP), including containerization and orchestration where applicable.
• Monitor model performance in production; identify drift, degradation, or failures and implement remediation strategies.
• Troubleshoot and resolve AI/ML engineering issues across development and production environments.

1. Cross-Functional Collaboration & Integration

• Partner with Product Managers, Product Owners, Software Engineers, Data Scientists, and Research teams to align AI solutions with business and product objectives.
• Translate product requirements and use cases into technical architectures and model designs.
• Support integration of AI capabilities into customer-facing products and internal platforms.
• Communicate technical concepts, tradeoffs, and limitations clearly to non-technical stakeholders.

1. Data & Domain Application

• Work with structured and unstructured datasets, including healthcare, claims, and life sciences data, to build high-performance AI systems.
• Ensure responsible handling, transformation, and validation of data used for model training and inference.
• Collaborate with data engineering and QA teams to ensure data pipelines and AI workflows are production-ready and auditable.

1. Technical Excellence & Continuous Improvement

• Stay current with advances in Generative AI, LLM architectures, model fine-tuning techniques, and applied machine learning.
• Contribute to internal best practices, standards, and reusable components for AI/ML development.
• Document AI/ML workflows, architectures, methodologies, and lessons learned for internal knowledge sharing.
• Proactively identify opportunities to improve scalability, reliability, and efficiency of existing AI systems.

Qualifications:

BA Degree in Computer Science, Software Engineering, Operations Engineering, Business Management or other related field

Minimum Required:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• Minimum 3+ years of hands-on experience in an AI/ML or data science role delivering production-deployed solutions.
• Strong proficiency in Python and SQL; experience building scalable ML/NLP workflows.
• Deep hands-on experience with machine learning, deep learning, and natural language processing.
• Experience working with Generative AI and Large Language Models, including fine-tuning and evaluation techniques.
• Working knowledge of data preprocessing, feature engineering, and model validation practices.
• Experience deploying AI solutions in cloud environments (Azure, AWS, or GCP).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

Preferred:

• Experience building AI solutions in healthcare, life sciences, analytics, or regulated data
• Hands-on experience with MLOps frameworks and monitoring strategies.
• Experience integrating AI models into SaaS products or productized services.
• Familiarity with distributed systems, APIs, and modern software engineering practices.
• Exposure to enterprise AI governance, security, or compliance considerations.

Competencies:

• Communication Skills: Written, Verbal, and Presentation: The successful candidate must have the ability to read, analyze, and interpret production data, financial reports, and legal documents. Excellent verbal, written, presentation, interpersonal skills including ability to clearly respond to common inquiries or complaints from customers, employees, and members of the business community. Must possess a rapid agility to reply to emails, provide instructions of work stream necessities or issues encountered, business and report writings in a succinct and informative manner.
• Business Judgment and Strategic Thinking: Ability to think, act, and deliver value in the best interest of our clients with respect to common practices of the healthcare consulting field. Ability to extrapolate from the specific to the general and interpret from the general to the specific.
• Analytic Skills: Framing macro problems into action steps or work plans for resolutions. Structuring a persuasive client presentation based on in-depth or expansive excel spreadsheets. Demonstrable interpretive and solution identification skills with the ability to understand multiple types of quantitative and qualitative data heightened with strong resolution skills.
• Collaboration and Teamwork: Ability to give and receive constructive feedback and work effectively across the organization to accomplish team goals is critical. The successful candidate must possess excellent judgment, management, and conflict resolution skills. Ability to work with team members to convey results, incorporate enhancements and productionize processes across projects. Must be able to understand the dynamics of how a team interconnects and relies upon every member.
• Strategic Thinking: Conceptualize outside of the aspects of a project at hand, with an ability to visualize how the work contributes to and drives forward the overall project.
• Solutions oriented: must be able to display resourcefulness and confidence under pressure
• Resilience: must be able to look past obstacles and roadblocks, ask questions and for support, and find their way around any obstacle.

Position Summary:

Precision AQ’s Product Solutions team is expanding its AI and machine learning engineering capabilities in India. This role is responsible for designing, developing, deploying, and scaling production-grade AI/ML solutions that directly support Precision AQ products and productized services across oncology access, analytics, and AI-enabled offerings.

The AI/ML Engineer operates as a hands-on technical contributor, working closely with product management, engineering, data science, and research teams to translate business problems into robust, scalable AI systems. The role spans model development, optimization, deployment, and operationalization, with a strong emphasis on Generative AI, Large Language Models (LLMs), and applied machine learning in real-world production environments.

The successful candidate is technically rigorous, execution-oriented, and comfortable operating in fast-paced, multi-product environments with evolving requirements.

Essential functions of the job include but are not limited to: (This is NOT meant to be an exhaustive task list)

1. AI / ML Model Development & Optimization

• Design, develop, fine-tune, and evaluate machine learning, deep learning, and Generative AI models, including Large Language Models (LLMs).
• Apply appropriate modeling techniques (supervised, unsupervised, NLP, deep learning) based on problem context and data constraints.
• Optimize model performance across accuracy, latency, scalability, and cost dimensions.
• Conduct rigorous model evaluation, validation, and benchmarking using large-scale datasets.
• Apply data preprocessing, feature engineering, augmentation, and synthetic data generation techniques to improve model robustness.

1. Production Deployment & MLOps

• Design and implement scalable, production-ready AI solutions integrated into existing platforms and workflows.
• Build, maintain, and improve MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
• Deploy and manage AI applications in cloud environments (Azure, AWS, or GCP), including containerization and orchestration where applicable.
• Monitor model performance in production; identify drift, degradation, or failures and implement remediation strategies.
• Troubleshoot and resolve AI/ML engineering issues across development and production environments.

1. Cross-Functional Collaboration & Integration

• Partner with Product Managers, Product Owners, Software Engineers, Data Scientists, and Research teams to align AI solutions with business and product objectives.
• Translate product requirements and use cases into technical architectures and model designs.
• Support integration of AI capabilities into customer-facing products and internal platforms.
• Communicate technical concepts, tradeoffs, and limitations clearly to non-technical stakeholders.

1. Data & Domain Application

• Work with structured and unstructured datasets, including healthcare, claims, and life sciences data, to build high-performance AI systems.
• Ensure responsible handling, transformation, and validation of data used for model training and inference.
• Collaborate with data engineering and QA teams to ensure data pipelines and AI workflows are production-ready and auditable.

1. Technical Excellence & Continuous Improvement

• Stay current with advances in Generative AI, LLM architectures, model fine-tuning techniques, and applied machine learning.
• Contribute to internal best practices, standards, and reusable components for AI/ML development.
• Document AI/ML workflows, architectures, methodologies, and lessons learned for internal knowledge sharing.
• Proactively identify opportunities to improve scalability, reliability, and efficiency of existing AI systems.

Qualifications:

BA Degree in Computer Science, Software Engineering, Operations Engineering, Business Management or other related field

Minimum Required:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• Minimum 3+ years of hands-on experience in an AI/ML or data science role delivering production-deployed solutions.
• Strong proficiency in Python and SQL; experience building scalable ML/NLP workflows.
• Deep hands-on experience with machine learning, deep learning, and natural language processing.
• Experience working with Generative AI and Large Language Models, including fine-tuning and evaluation techniques.
• Working knowledge of data preprocessing, feature engineering, and model validation practices.
• Experience deploying AI solutions in cloud environments (Azure, AWS, or GCP).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

Preferred:

• Experience building AI solutions in healthcare, life sciences, analytics, or regulated data
• Hands-on experience with MLOps frameworks and monitoring strategies.
• Experience integrating AI models into SaaS products or productized services.
• Familiarity with distributed systems, APIs, and modern software engineering practices.
• Exposure to enterprise AI governance, security, or compliance considerations.

Competencies:

• Communication Skills: Written, Verbal, and Presentation: The successful candidate must have the ability to read, analyze, and interpret production data, financial reports, and legal documents. Excellent verbal, written, presentation, interpersonal skills including ability to clearly respond to common inquiries or complaints from customers, employees, and members of the business community. Must possess a rapid agility to reply to emails, provide instructions of work stream necessities or issues encountered, business and report writings in a succinct and informative manner.
• Business Judgment and Strategic Thinking: Ability to think, act, and deliver value in the best interest of our clients with respect to common practices of the healthcare consulting field. Ability to extrapolate from the specific to the general and interpret from the general to the specific.
• Analytic Skills: Framing macro problems into action steps or work plans for resolutions. Structuring a persuasive client presentation based on in-depth or expansive excel spreadsheets. Demonstrable interpretive and solution identification skills with the ability to understand multiple types of quantitative and qualitative data heightened with strong resolution skills.
• Collaboration and Teamwork: Ability to give and receive constructive feedback and work effectively across the organization to accomplish team goals is critical. The successful candidate must possess excellent judgment, management, and conflict resolution skills. Ability to work with team members to convey results, incorporate enhancements and productionize processes across projects. Must be able to understand the dynamics of how a team interconnects and relies upon every member.
• Strategic Thinking: Conceptualize outside of the aspects of a project at hand, with an ability to visualize how the work contributes to and drives forward the overall project.
• Solutions oriented: must be able to display resourcefulness and confidence under pressure
• Resilience: must be able to look past obstacles and roadblocks, ask questions and for support, and find their way around any obstacle.