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

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 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

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

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)

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.

Role Overview

At JazzX, we are building a modern cloud-native platform ecosystem focused on scalability, reliability, automation, security, and developer self-service. Our platform leverages Microsoft Azure, Cloudflare, AI/LLM-driven operations, and Agentic workflows to automate infrastructure management, deployment operations, incident response, platform intelligence, and customer instance lifecycle management.

We are looking for a highly experienced Staff Platform Engineer to lead the architecture, automation, scalability, and operational maturity of our platform infrastructure and engineering ecosystem. This role requires deep expertise across cloud infrastructure, distributed systems, networking, DevOps, platform engineering, security, and intelligent automation.

As a senior technical leader, you will drive platform strategy, define engineering standards, mentor engineers, and build highly scalable and resilient systems that improve developer productivity, operational efficiency, security, and customer experience.

Platform Architecture, Engineering & Reliability

• Architect and build scalable, secure, and highly available cloud-native platforms on Microsoft Azure
• Design and manage infrastructure automation using Terraform, GitOps, and Infrastructure as Code (IaC)
• Build and improve CI/CD systems, deployment orchestration, environment provisioning, and self-service developer platforms
• Design secure networking and authentication systems using Cloudflare, API gateways, private networking, and Zero Trust principles
• Drive platform reliability, scalability, observability, security, and operational excellence across production environments
• Lead incident management, root cause analysis, operational governance, deployment reliability, and resiliency improvements
• Build AI/LLM and Agentic operational workflows for troubleshooting, automation, operational insights, and intelligent platform management
• Improve operational efficiency through automation, intelligent tooling, anomaly detection, and cloud cost optimization
• Strong hands-on coding experience in Python, Go, or modern programming languages with strong system design and problem-solving fundamentals
• Deep understanding of cloud-native architectures, distributed systems, networking, CI/CD, infrastructure automation, and platform engineering principles
• Experience building internal developer platforms, self-service systems, operational tooling, and AI-assisted engineering workflows
• Strong understanding of SDLC, DevOps practices, Agile methodologies, release governance, and production operational models
• Strong troubleshooting and debugging skills across infrastructure, cloud, deployment, networking, and application layers

Technical Leadership & Collaboration

• Partner with engineering, architecture, security, and product teams to define platform standards and long-term technical strategy
• Improve developer experience, platform adoption, deployment reliability, and operational maturity across teams
• Lead architecture discussions, operational reviews, and production readiness initiatives
• Mentor engineers and drive engineering best practices across platform and infrastructure domains
• Drive engineering culture around automation, scalability, reliability, operational excellence, and platform standardization
• Strong communication, collaboration, stakeholder management, and technical leadership skills

Experience

• 10+ years of experience in Platform Engineering, Infrastructure Engineering, DevOps, SRE, or Cloud Engineering
• Extensive experience managing large-scale production environments on Microsoft Azure
• Experience with Kubernetes, container platforms, GitOps, Terraform, and cloud-native systems
• Experience building enterprise-grade CI/CD and deployment automation platforms
• Experience driving operational excellence, observability, reliability engineering, and infrastructure automation initiatives
• Experience leading cross-functional technical initiatives and mentoring engineers
• Experience with AI/LLM workflows, coding agents, and intelligent automation systems is a strong plus

Technical Skills

Cloud & Infrastructure

• Microsoft Azure, Azure Networking, VNet, NSG, Load Balancer, Private Endpoints, Azure Kubernetes Service (AKS), Azure Container Apps, Azure API Management, Azure Entra ID, Azure Monitor and Log Analytics

Infra, DevOps, Automation and Building Platform

• Terraform,GitHub Actions / Azure DevOps, CI/CD Pipeline Design, Infrastructure as Code (IaC), GitOps, Python / Go any programming language

Networking & Security

• Cloudflare Gateway / WAF, API Security, Authentication & Authorization, SSO Integration (Okta, Entra ID), Network Security and Zero Trust concepts

Observability & Operations

• Monitoring and Alerting, Logging and Tracing, Incident Management, Root Cause Analysis, Reliability Engineering

AI & Platform Intelligence

• LLM-based operational workflows, Agentic automation systems, AI-assisted incident analysis and remediation, Intelligent anomaly detection and operational insights

Nice To Have

• Kubernetes ecosystem tools, Service Mesh, Vector databases, MCP/Agentic orchestration frameworks, FinOps and cloud cost optimization tools

Role Overview

At JazzX, we are building a modern cloud-native platform ecosystem focused on scalability, reliability, automation, security, and developer self-service. We leverage Microsoft Azure, Cloudflare, AI/LLM-driven operations, and Agentic workflows to simplify infrastructure management, deployment automation, incident response, and platform operations across multiple environments and customer instances.

We are looking for a highly skilled Senior Platform Engineer who can design, build, automate, and operate large-scale cloud platforms while driving engineering excellence across infrastructure, networking, security, CI/CD, observability, and platform automation.

This role requires strong hands-on technical expertise, ownership mindset, system thinking, and the ability to collaborate across engineering, DevOps, security, and product teams.

Platform Engineering & Operational Excellence

• Design, build, and operate scalable, secure, and highly available cloud infrastructure on Microsoft Azure
• Build and manage platform services including networking, authentication, CI/CD, observability, deployment automation, and self-service systems
• Develop reusable Infrastructure as Code (IaC) frameworks using Terraform, GitOps, and modern automation practices
• Design secure network architectures including VNets, private networking, routing, WAF, API gateways, and Zero Trust principles
• Build automated deployment, environment provisioning, and multi-instance platform management workflows
• Improve platform reliability, operational stability, monitoring, alerting, logging, tracing, and incident response processes
• Drive operational automation, platform resilience, release governance, rollback strategies, and deployment reliability
• Build developer productivity tooling and self-service workflows for platform operations and environment management
• Contribute hands-on using Python, Go, or modern programming languages to build scalable systems, internal platforms, and automation frameworks
• Apply strong system design, distributed systems, troubleshooting, and problem-solving skills across cloud, network, deployment, and infrastructure layers
• Leverage AI/LLM-driven workflows, coding agents, and Agentic systems to improve operational efficiency, automation, incident management, and platform intelligence
• Drive cloud cost optimization, usage visibility, anomaly detection, and operational efficiency initiatives
• Strong understanding of SDLC, DevOps, Agile methodologies, release governance, production operations, and Site Reliability Engineering (SRE) practices
• Strong ownership mindset with focus on scalability, automation, reliability, operational excellence, and developer productivity

Collaboration & Leadership

• Partner with engineering, security, architecture, and product teams to define platform standards, operational processes, and long-term technical strategy
• Work closely with application teams to improve platform adoption, deployment reliability, and developer experience
• Collaborate with security teams to implement authentication, authorization, governance, compliance, and operational security standards
• Participate in architecture reviews, production readiness reviews, operational planning, and incident management discussions
• Mentor engineers and contribute to platform engineering best practices, technical standards, and documentation
• Drive technical discussions and contribute to platform modernization and intelligent automation initiatives

Experience

• 6+ years of experience in Platform Engineering, DevOps, SRE, or Cloud Infrastructure Engineering
• Hands-on experience managing production-scale Azure environments and enterprise-grade CI/CD systems
• Experience working with Kubernetes, cloud-native platforms, infrastructure automation, observability, and distributed systems
• Experience supporting multi-environment and multi-tenant platform operations at scale
• Experience with AI-assisted engineering workflows, operational tooling, or intelligent automation systems is a strong plus
• Strong communication, collaboration, and technical leadership capabilities

 Technical Skills

Cloud & Infrastructure

• Microsoft Azure, Azure Networking, VNet, NSG, Load Balancer, Private Endpoints, Azure Kubernetes Service (AKS), Azure Container Apps, Azure API Management, Azure Entra ID, Azure Monitor and Log Analytics

Infra, DevOps, Automation and Building Platform

• Terraform,GitHub Actions / Azure DevOps, CI/CD Pipeline Design, Infrastructure as Code (IaC), GitOps, Python / Go any programming language

Networking & Security

• Cloudflare Gateway / WAF, API Security, Authentication & Authorization, SSO Integration (Okta, Entra ID), Network Security and Zero Trust concepts

Observability & Operations

• Monitoring and Alerting, Logging and Tracing, Incident Management, Root Cause Analysis, Reliability Engineering

AI & Platform Intelligence

• LLM-based operational workflows, Agentic automation systems, AI-assisted incident analysis and remediation, Intelligent anomaly detection and operational insights

Nice To Have

• Kubernetes ecosystem tools, Service Mesh, Vector databases, MCP/Agentic orchestration frameworks, FinOps and cloud cost optimization tools

Why Join Us

At JazzX AI, you have the opportunity to become an integral part of a pioneering team that is pushing the envelope of AI capabilities to create an autonomous intelligence driven future. We champion bold innovation, continuous learning, and embrace the challenges and rewards of crafting something genuinely groundbreaking.

Your work will directly contribute to pioneering solutions that have the potential to transform industries and redefine how we interact with technology. As an early member of our team, your voice will be pivotal in steering the direction of our projects and culture, offering a unique chance to leave your mark on the future of AI.

We offer a competitive salary, equity options, and an attractive benefits package, including health, dental, and vision insurance, flexible working arrangements, and more.

We are an equal opportunity employer and celebrate diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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.

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.

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

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.

Why This Role Matters 

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.  

What Makes This Opportunity Unique 

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.  You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models . 

Responsibilities 

• Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking. 

• Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics). 

• Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction. 

• Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning. 

• Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval. 

• Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows. 

• Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging. 

• Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance. 

• Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems. 

• Evolve the domain graph and entity resolution; build reliable data ingestion pipelines. 

• Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage. 

• Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost. 

• Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity. 

• Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls. 

• Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed. 

• Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices. 

Desired Skills & Experience 

• 12–15+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems). 

• Production experience with Python plus one of Java/Scala/Go; microservices and API design. 

• MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka). 

• Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS. 

• Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows. 

• Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting. 

• Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry. 

• Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns. 

Preferred Mindset 

• Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs. 

• Thinks in systems - observability, fallback, access control are core, not afterthoughts. 

• Passionate about AI - enjoys enabling real-world LLM and agentic use cases. 

• Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation. 

• Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience. 

• Documentation and teaching: you make complex systems understandable; you uplevel teams. 

Narvar is Growing! We are looking for a high-potential B.Tech graduate with a strong foundation in Artificial Intelligence and process automation to join our team as an AI Consultant for a 12-month engagement. You will work directly on high-impact projects that use AI to automate and transform our HR and Finance functions.

This is a senior internship role with real ownership and accountability. You will be expected to independently drive projects end-to-end — from understanding the problem, designing the solution, building and testing it, and handing it over to business teams. You will work closely with senior HR and Finance leaders, and your output will directly affect how hundreds of employees experience these functions.

Given the compensation and duration, we expect candidates who can demonstrate either strong academic performance in AI/ML, prior projects, or hands-on experience with AI tools. Fresh thinking combined with technical seriousness is what we are looking for.

Day-to-day

HR Projects

Chatbot & Knowledge Management

• Build and maintain an AI-powered HR chatbot that answers employee questions about policies, leave, payroll, and benefits
• Design and test conversation flows for the chatbot — writing instructions, testing responses, and continuously improving accuracy
• Help digitise and organise HR policy documents so the AI can read and reference them correctly
• Analyse common employee queries to identify gaps in HR documentation and recommend content updates

HR Operations Automation

• Automate repetitive HR tasks such as leave tracking, onboarding checklists, exit checklists, and document collection using appropriate tools
• Build AI agents that monitor, update, and distribute HR dashboards to Executives and Managers — reducing manual reporting effort
• Design automated workflows that surface key HR metrics (headcount, attrition, leave utilisation) to the right stakeholders at the right time

Performance Management Automation

• Automate performance review cycle processes — reminder workflows, form collection, status tracking, and escalation nudges
• Build tools to aggregate and visualise performance data for managers, removing manual consolidation from spreadsheets
• Design AI-assisted pipelines to flag review completion rates, identify bottlenecks, and generate summary reports for HR leadership

Talent Acquisition & Recruitment

• Build dashboards and automated reports tracking talent acquisition metrics — pipeline volume, source effectiveness, time-to-offer, and offer acceptance rates
• Design AI-assisted application review workflows to help the recruitment team prioritise and triage high volumes of applications faster
• Automate candidate communication touchpoints such as acknowledgement emails, status updates, and interview scheduling reminders
• Create tools that surface hiring funnel analytics to Hiring Managers and HR leadership in real time

Finance Projects

• Automate routine finance workflows such as invoice processing, expense categorisation, and reimbursement tracking
• Build simple AI-assisted tools to flag anomalies or inconsistencies in financial data
• Create automated reports and dashboards using Google Sheets or similar tools, reducing manual data entry
• Assist in mapping existing manual finance processes and proposing AI-based alternatives
• Test and document automation tools before they are rolled out to the finance team

What we’re looking for

• B.Tech degree in Computer Science, AI/ML, Data Science, Electronics, or related branch — 2024 or 2025 pass-out
• Demonstrable hands-on experience with AI tools — projects, hackathons, internships, or self-built tools all count
• Working knowledge of Python — able to write scripts, use libraries, and debug independently
• Strong understanding of at least one AI/ML concept: LLMs, NLP, classification, automation pipelines, or similar
• Comfortable working with Google Workspace (Docs, Sheets, Drive) and cloud-based tools
• Excellent written communication in English — you will be writing specifications, documentation, and chatbot content
• Ability to manage your own work, meet deadlines, and proactively communicate blockers

Bonus points

• Experience with LLM APIs — OpenAI, Anthropic Claude, or Google Gemini
• Prior internship or freelance project involving AI, automation, or data — even if short
• Familiarity with no-code/low-code tools: Zapier, Make, Botpress, Flowise, or similar
• Basic understanding of HR or Finance workflows from coursework, projects, or prior exposure
• A GitHub profile, portfolio, or any public evidence of what you have built
• Experience with prompt engineering, RAG pipelines, or building chatbots

What you will earn

• By the end of this internship, you will have hands-on experience that most fresh graduates do not get from classroom learning alone:
• How to build and deploy a working AI chatbot using real enterprise tools
• How to design automated workflows that replace manual, repetitive tasks
• How to work with HR and Finance stakeholders to understand their pain points and translate them into technical solutions
• Practical exposure to AI tools, APIs, and no-code platforms used in Indian companies
• How to document, test, and hand over a technical project to a non-technical team
• Real experience you can put on your resume and explain confidently in interviews

Why Narvar?

We're on a mission to simplify the everyday lives of consumers. Post-purchase is a critical phase of the customer journey. That's why we created Narvar - a platform focused on driving customer loyalty through seamless post-purchase experiences that allow retailers to retain, engage, and delight customers. If you've ever bought something online, there's a good chance you've used our platform!

From the hottest new direct-to-consumer companies to retail’s most renowned brands, Narvar works with GameStop, Neiman Marcus, Sonos, Nike, and 1300+ other brands. With hubs in San Francisco, Atlanta, London, and Bangalore, we've served over 125 million consumers worldwide across 10+ billion interactions, 38 countries, and 55 languages.

Pioneering the post-purchase movement means navigating into the unknown. Our team thrives on this sense of adventure while nurturing a mindset of innovation. We're a home for big hearts and we leave our egos at the door. We work hard but we always make time to celebrate professional wins, baby showers, birthday parties, and everything in between.

We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

#LI-PR1

#LI-Remote

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

• Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
• You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
• Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

• Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
• Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
• Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
• Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
• Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
• Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
• Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
• Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
• Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

• 8+ years of software engineering experience with 4+ years focused on AI/ML systems in production
• Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
• Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
• Background in computer vision, image processing, or visual transformer architectures
• Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
• Experience working with massive datasets (50TB+) and building scalable data pipelines
• Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
• Familiarity with RLHF-style preference tuning and model alignment techniques
• Experience with observability and monitoring stacks including metrics, logging, and tracing
• Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

THE ROLE

The Data & Analytics team at Ever Pure is looking for a Senior Manager for designing and building an AI-ready data infrastructure powering conversational AI and chatbot experiences for Finance.
This role will lead the end-to-end build, defining the target state, identifying capability gaps, and delivering a phased roadmap with measurable outcomes. A core focus is enabling a conversational, AI-driven Finance experience, allowing stakeholders to access insights through natural language and copilots.

WHAT YOU'LL DO

Finance Control Tower & Data Foundation

• Lead the design and build of the Finance Control Tower
• Establish a scalable, AI-ready data platform for reporting, analytics, and AI
• Deliver unified, trusted views across Finance (revenue, billing, forecasting)

Data Architecture, Semantic Layer & Observability

• Define data architecture and unified models across systems (Salesforce, SAP, NetSuite, Zuora)
• Build a semantic / metrics layer to standardize business definitions
• Implement data management and observability (quality, lineage, reliability)

Conversational AI & AI Enablement

• Enable natural language access to Finance data via chatbots and copilots
• Build RAG-based architectures using structured and unstructured data
• Develop embeddings and semantic context layers for business-aware insights
• Leverage platforms like Snowflake Cortex (or similar) for search, summarization, and classification

Data Engineering & AI Integration

• Build and scale data pipelines and AI-ready datasets in Snowflake (or similar)
• Integrate enterprise data sources (SFDC, NetSuite, Zuora)
• Enable LLM-driven use cases (forecasting, anomaly detection, variance analysis)
• Ensure outputs are accurate, explainable, and traceable

We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

• 15+ years in data engineering, analytics, or related roles
• Experience building modern data platforms / data products at scale
• Strong expertise in:
• SQL, data modeling, ETL/ELT
• Semantic / metrics layer design
• Data governance, quality, and observability
• Experience with Snowflake (or similar) and Python
• Exposure to:
• Conversational AI / chatbot systems
• RAG, embeddings, vector search
• LLM frameworks and prompt design
• Understanding of Finance data (ARR, MRR, revenue) preferred
• Strong execution, stakeholder management, and communication skills

#LI-ONSITE

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-BRAZIL
#LI-INDIA

About the Role

The AI Integrations team builds the tools that bring AI into Telnyx's core products — think voice agents, intelligent messaging, and real-time AI features that improve our customer experience. We need a strong fullstack engineer to help us move faster.

This is a mid-level IC role. You'll own features end-to-end: building React interfaces, writing Node.js services, wiring up databases, and shipping things that work. AI experience isn't required — you'll pick that up here. What matters is that you can build solid fullstack products and want to learn.

What You'll Work On

• Fullstack features across our AI product suite — frontend to database
• Integrating LLMs and AI capabilities into real world applications (with support from the team)
• Building interfaces that make complex AI tools feel simple
• Shipping iteratively — we value working software over perfect plans

Tech Stack

Core (you should know this well):
React 18+, TypeScript, Tailwind CSS, Node.js, PostgreSQL, Prisma, TanStack Query, Docker, Kubernetes

Bonus (nice to have, happy to teach):
Next.js 15+, LLM integration, LangChain/LangGraph RAG/Embeddings, Vector Databases, MCP, WebSockets, WebRTC, Radix UI, Shadcn UI, Framer Motion

What We're Looking For

You're genuinely comfortable across the stack — not a frontend dev who can "do backend" or vice versa. You've built and shipped real features. You take ownership, communicate clearly, and don't need hand-holding.

AI interest is a plus, but we'd rather have a strong fullstack engineer who's curious than an "AI enthusiast" who can't ship.

We move fast on modern web tooling (React/Next, TypeScript, Tailwind). Expect frequent upgrades.

Values

• Ownership — you see things through
• Collaboration — you work well with others and communicate proactively
• Adaptability — comfortable with ambiguity and changing requirements
• Growth mindset — eager to learn, takes feedback well


#LI-KG1 #LI-VIETNAM
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems
  
  
  

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

About the Team & Role

Rubrik (RBRK), the Security and AI Operations Company, leads at the intersection of data protection, cyber resilience, and enterprise AI acceleration. Our Global Benefits team is dedicated to ensuring Rubrikans are supported through every stage of their journey.

As our India Benefits & AI Operations Intern, you will play a pivotal role in our own AI transformation. Reporting to the Manager of India Benefits, you will bridge the gap between human-centric support and cutting-edge technology. Your mission is to audit, structure, and modernize our benefits data so it can be seamlessly leveraged by AI tools, ensuring our employees get the right answers at the right time.

What You’ll Do

• Build the Foundation: Develop a fully functioning, AI-ready knowledge base for all India benefits (employee-facing) to provide instant, clear support.
• Market Benchmarking: Research and benchmark India benefit trends and competitive offerings to ensure Rubrik’s programs remain market-leading, inclusive, and aligned with our EVP.
• Optimize Internal Ops: Create internal-facing documentation for India and APAC benefits processing to streamline workflows for the Global Benefits team.
• AI Data Auditing: Review and refine existing policy documents to ensure they are structured for high-performance AI tools like NotebookLM or similar LLM platforms.
• Enhance Jira Service Management: Build out and refine knowledge articles within the Jira help desk to improve self-service capabilities.
• Process Automation: Identify and propose opportunities to leverage AI to automate manual benefit administration tasks.
• Cross-Functional Collaboration: Partner with HR Operations and IT to ensure benefits data is accessible, inclusive, and accurate across all internal platforms.

What You’ll Bring

• Academic Focus: Currently pursuing a degree in Human Resources, Business Administration, Data Science, or a related field.
• Technical Curiosity: High tech-fluency with a deep interest in how Generative AI and automation can transform People Operations.
• Communication Excellence: Ability to translate complex benefit policies into simple, accessible, and inclusive language.
• Analytical Mindset: Strong attention to detail with the ability to audit large sets of information and conduct market research.
• Problem-Solving: A proactive approach to identifying manual gaps and proposing digital-first solutions.
• Collaborative Spirit: Comfortable working in a fast-paced, global environment with a focus on team-oriented outcomes.

Nice to Have

• Familiarity with Jira Service Management or similar help desk ticketing systems.
• Basic understanding of India statutory benefits (EPF, ESI, Gratuity).
• Experience with data structuring or competitive research projects.

What You’ll Gain

• Impact: You won't just be "learning"—you will be building the actual infrastructure Rubrik uses to support its employees.
• Growth: Direct mentorship from seasoned benefits leaders with over 15 years of experience in the India market.

Empowerment: The autonomy to experiment with AI tools and shape how we deliver benefits in the AI era.

Senior Product Manager, Data Discovery and Classification

Location: Bangalore,India

About the Team:

The Product Management team at Rubrik drives Rubrik’s vision forward, ensuring we continue to secure the world’s data by delivering on our market-leading platform to address our customers’ most challenging data management & security needs. Our Product Managers are responsible for guiding multidisciplinary teams towards the goal of shipping high-quality products on time. We wear multiple hats throughout the different stages in the product lifecycle and set the vision for our growing family of products. As advocates for both our users and our business, Product Managers balance varied perspectives and empower their teams to do great work.

About the Role:

Rubrik is building the future of Identity & Data Security, and we are looking for a Product Manager to lead our Data Discovery & Classification portfolio. This role sits at the intersection of identity, data, and AI-driven security, and is core to our mission to help organizations achieve true cyber resilience.

You will define and execute the strategy for how Rubrik discovers, classifies, and interprets sensitive data across cloud and on-prem environments - powering our critical product lines. 

This is a high-visibility, high-impact role where you’ll work closely with engineering, design, GTM, and senior leadership team to define the next generation of our products to build the foundation of Rubrik’s next major product line.

What You’ll Own:

Product Strategy & Vision

• Build the long-term strategy for Data Discovery & Classification across structured and unstructured data.
• Partner with Identity, Rubrik Agent Cloud, and Data Resilience teams to define how data context connects to identity, access, posture, and recovery workflows.

Customer Discovery & Problem Definition

• Talk directly with CISOs, security architects, cloud leaders, data governance teams, and IR specialists to identify high-value problems.
• Translate customer use cases into clear requirements, and prioritized roadmaps. Also, drive feedback loops with design partners to validate features and iterate.

Execution & Delivery

• Write PRDs, define acceptance criteria, and work day-to-day with engineering on tradeoffs and scope.
• Own beta programs, and cross-functional alignment by partnering on positioning, competitive differentiation, and GTM strategy.

Cross-Functional Leadership

• Influence without authority across engineering, research, security, and sales engineering.
• Collaborate closely with the Data Science team on classification engines, labeling, and LLM-based classifiers. 

What We’re Looking For:

• 9+ years of product management experience (security, data, or AI preferred).
• Experience with DSPM, DLP, data governance, sensitivity labeling, or identity security.
• Customer-obsessed and experienced in running customer interviews or design partner programs.
• Familiarity with cloud data stores (S3, BigQuery, Snowflake, Azure Blob, OneDrive/SharePoint).
• Strong technical depth; able to work hands-on with engineering, ML teams, and UX. 
• Strong written communication — PRDs, strategy docs, exec updates, roadmap presentations.
• Ability to navigate ambiguity, prioritize ruthlessly, and influence senior stakeholders.

If you are passionate about shaping what's next for data security, we’d love to hear from you.

#LI-AS2

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

About the Role

We are seeking a Senior AI Engineer with a strong foundation in Python capabilities, and hands-on experience building Agentic AI applications that integrate with Large Language Models (LLMs) Large Language Models (LLMs). We are also looking for him to be a full-stack Engineer with hands-on experience with mobile front-end hands-on experience with mobile front-end Flutter, React-native. This role blends traditional backend engineering expertise with next-generation AI agentic systems development, requiring not just system design skills, but also creativity in prompt engineering, AI product development and working with data-rich environments.

You will contribute to the design and implementation of intelligent backend services that coordinate LLMs, agents, and data workflows to support enterprise-grade agentic systems.

Key Responsibilities

• Develop robust, scalable Java/Python based backend systems that enable the orchestration of Agentic AI workflows.
• Develop state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection.
• Integrate LLMs (e.g., OpenAI, Mistral, Claude, LLaMA) into backend pipelines to power autonomous or semi-autonomous decision-making.
• Hands on experience with mobile front-end Flutter, React-native etc.
• Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems.
• Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models.
• Work closely with various stakeholders to design agent architectures and LLM toolchains (using frameworks like LangGraph, Crew AI, AutoGen, etc.).
• Implement services and APIs that manage prompt chaining, tool invocation, and contextual memory for agents.
• Collaborate with data engineers to ensure clean, efficient, and real-time access to structured and semi-structured data.
• Apply prompt engineering best practices to improve agent behavior, task accuracy, and adaptability.
• Monitor and optimize service performance, reliability, and scalability in production environments.
• Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies.
• Contribute to code reviews, mentoring, and best practices for hybrid backend/AI development.

Required Qualifications

• 5+ years of overall experience mobile front-end Flutter, React-native etc
• 2+ years of experience in developing and deploying machine learning models and AI products in production environments.
• Experience in Agentic AI systems development using tools such as LangGraph, Crew AI, AutoGen, or similar.
• Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow).
• Experience integrating or orchestrating LLMs within business workflows or intelligent assistants.
• Solid understanding of prompt engineering techniques (e.g., system messages, chaining, tool invocation prompts).
• Familiarity with data engineering concepts, including pipelines, data models, and ETL workflows.
• Strong grasp of object-oriented design, data structures, and algorithms.

Preferred Qualifications

• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, RAG pipelines).
• Background in building microservices or backend systems for data-rich AI/ML platforms.
• Experience with vector databases, embedding services, or semantic search integration.
• Knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and DevOps best practices.
• Experience in developing LLM-powered agents, copilots, or task bots.

What We Offer

• Opportunity to work on cutting-edge backend and AI systems, including agentic automation and LLM innovation.
• A flexible hybrid work model in our Bangalore office.
• Competitive compensation with performance-based rewards.
• A culture that promotes engineering excellence, experimentation, and growth.Access to learning platforms, technical workshops, and industry-leading AI research.

Why Join Reltio?*

• Health & Wellness:
  • Comprehensive Group medical insurance including your parents with additional top-up options.
  • Accidental Insurance
  • Life insurance
  • Free online unlimited doctor consultations
  • An Employee Assistance Program (EAP)
• Work-Life Balance:
  • 36 annual leaves, which includes Sick leaves – 18, Earned Leaves - 18
  • 26 weeks of maternity leave, 15 days of paternity leave
  • Very unique to Reltio - 01 week of additional off as recharge week every year globally
• Support for home office setup:
  • Home office setup allowance.
• Stay Connected, Work Flexibly: Mobile & Internet Reimbursement
• No need to pack a lunch—we’ve got you covered with a free meal.And many more…..

Role Description

• As a Senior 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.

Key Responsibilities:

• 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: Senior Applied Value Engineer stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Senior Applied Value Engineer specialize in domains (e.g. supply chain) and industries

Requirements:

• 6+ 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)

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

• Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
• You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
• Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

• Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
• Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
• Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
• Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
• Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
• Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
• Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
• Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
• Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

• 8+ years of software engineering experience with 4+ years focused on AI/ML systems in production
• Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
• Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
• Background in computer vision, image processing, or visual transformer architectures
• Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
• Experience working with massive datasets (50TB+) and building scalable data pipelines
• Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
• Familiarity with RLHF-style preference tuning and model alignment techniques
• Experience with observability and monitoring stacks including metrics, logging, and tracing
• Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

Role Description

• As a Senior 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.

Key Responsibilities:

• 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: Senior Applied Value Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 6+ 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)

The Team:

The Celonis Value Engineering (VE) team is focused on managing the entire customer value lifecycle, from sales through value realization, renewal and expansion. As a Value Engineer - India, your primary focus will be supporting our GCC's (Global Competency Centers) across the Adopt and Expand phases of our customer value journey. This team will be a part of the Global VE CoE spearheading our mission of data-driven business transformation with our customers.You will blend deep process and industry expertise with a proven consulting skill set with strong analytical skills at the forefront of one of the fastest-growing tech companies worldwide.

The Role:

As an Applied AI Value Engineer you are pushing the envelope in solving mission-critical problems for our customers. You will be working with our most strategic customers, understanding their strategy and key challenges, and building Celonis solutions using cutting edge AI technologies of market leaders such as Microsoft and OpenAI. With Celonis’ market leading Process Intelligence (PI) Platform we feed operational context to AI so it understands our customers’ businesses 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: 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 Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

The qualifications you need:

Requirements:

• 4+ 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)

We are seeking a deeply curious, technically strong People Analytics professional to transform Human Resources, Talent Acquisition, and labor market data into a unified strategic engine within Power BI. In this role, you will operate as an equal parts data engineer, analyst, and storyteller, building scalable data pipelines and translating complex datasets into executive-ready insights that guide the global workforce and hiring decisions.  You will own the data narrative for workforce and talent strategy, helping leaders move beyond reporting what happened to understand why it happened and what to do next. By connecting insights across HR systems, recruiting platforms, and labor market intelligence, your work will ensure hiring. Workforce planning and talent investment decisions are guided by clear, reliable, and actionable data. 

Roles & Responsibilities 

• Integrated Strategic Storytelling. Deliver unified workforce and recruiting insights by synthesizing data from Oracle HCM, Greenhouse, and external sources, translating HR metrics into executive-ready narratives through trend analysis, root-cause insights, and clear links to business outcomes. 
• Analytics Transformation. Drive the shift from reactive reporting to proactive analytics by building automated pipelines, predictive models, and self-service reporting that improve decision speed and reduce manual data pulls. 
• Cross-Functional Data Partnership. Partner across HR, Talent Acquisition, Finance, and Data Engineering to ensure workforce and recruiting data is accurate, consistent, and translated into insights that improve hiring outcomes and workforce planning. 
• Data Architecture & Engineering Collaboration. Work with Data Engineering to design and maintain Snowflake pipelines, ensuring seamless integration between Oracle HCM, Greenhouse, and reporting layers that support executive decision-making. 
• Advanced Power BI Development. Build and maintain Power BI dashboards and semantic models that provide real-time visibility into workforce, recruiting, and labor market trends while enabling scalable self-service reporting. 
• Oracle HCM Reporting Expertise. Develop scalable enterprise reporting and complex data extracts, ensuring the accuracy, reliability, and scalability of workforce and recruiting datasets. 
• Data Advocacy & Insight Culture. Champion a data-driven culture by enabling HR and Talent Acquisition teams to interpret analytics confidently, ask better questions, and use insights to build compelling quarterly and annual workforce narratives. 
• Labor Market Intelligence. Analyze talent supply, competitive hiring dynamics, and compensation benchmarks to provide market-informed recommendations that guide global hiring strategy, workforce location decisions, and talent competitiveness. 

Required Qualifications 

• Bachelor's degree in human resources, Information Systems, Business, Data Science, or related fields
• 5+ years of experience in HR analytics, Talent Acquisition analytics, or people data environments within complex or global organizations that include experience translating complex multi-source data into clear narratives and insights that influence leadership decisions and workforce strategy. 
• 4+ years of experience developing advanced dashboards in Power BI, including star-schema data modeling, advanced DAX calculations, and row-level security for executive reporting environments. 
• 2+ years of SQL experience with querying and transforming complex datasets while bridging backend data structures and front-end analytics tools. 
• 2+ years of experience with Microsoft Excel including PivotTables, complex formulas, and lookup functions for analyzing and reporting large datasets. 
• 1+ years of hands-on experience with Oracle HCM including building, developing and publishing reports and/or dashboards. 

Preferred Qualifications 

• Strong understanding of HR metrics and recruiting KPIs, such as headcount, turnover, recruiting funnels, hiring plan attainment, diversity hiring progress, and workforce movement. 
• Hands-on experience with Greenhouse or similar ATS platforms, including building sourcing attribution models, recruiting funnel benchmarks, and full-lifecycle hiring analytics. 
• Experience with LinkedIn Talent Insights or similar platforms to interpret external talent market signals and convert them into actionable recommendations. 
• Experience using Python or R for predictive modeling and workflow automation, along with an interest in applying Generative AI or LLM-based tools to accelerate insight development. 
• Strong SQL capabilities with experience querying and transforming complex datasets while bridging backend data structures and front-end analytics tools. 
• Familiarity with modern data pipeline tools and experience modeling HR and recruiting data within Snowflake. 
• Understanding of global data privacy frameworks such as GDPR and CCPA, and their application within HR data governance, payroll reporting, and employee data management

The Role:

As an Applied Value Engineer for the Japan Market, you will solve business-critical problems for our most strategic Japanese customers. You will bridge the gap between cutting-edge AI technology and the unique business requirements of Japanese enterprises.
Working with the world’s leading Process Intelligence (PI) platform and partners like Microsoft, OpenAI, and Databricks, you will feed operational context to AI to help Japanese organizations industrialize AI and unlock real ROI. You will prototype solutions, demonstrate value to executives, and ensure successful implementation and adoption within the Japanese business ecosystem

The work you’ll do:

• AI Discovery & Solutioning (Japan Focus): Understand the specific AI strategies and challenges of Japanese customers. Translate their requirements into innovative solutions that align with local business practices.
• Hackathons & Prototyping: Rapidly build creative prototypes (LLM/Agent-based) to solve business-critical problems during customer hackathons.
• Agentic Process Transformation: Enable a fundamental shift for our customers from traditional automation to autonomous AI agents empowered by the Celonis PI Platform.
• Proof Projects: Execute end-to-end Proof-of-Value (PoV) projects, including architecture, RAG, and guardrails, ensuring compliance with enterprise data and identity frameworks.
• Cross-Border Collaboration: Work closely with the Japan-based account teams and executives to ensure project outcomes reach agreed value and adoption thresholds.
• Domain Specialization: Specialize in domains (e.g., Supply Chain, Finance) to scale knowledge across the Japan and global organizations.

The qualifications you need:

• Market Alignment: Strong willingness and commitment to work specifically for the Japan market. This includes flexibility to align with Japan Standard Time (JST) for key meetings and workshops.
• Professional Experience: 3-5 years of experience in technical pre-sales, defining AI roadmaps, and building ROI/TCO business cases.
• Technical Expertise: Deep understanding of Generative AI techniques (RAG, multi-agent orchestration, prompt engineering) and Python (LangChain, pandas, PyTorch, etc.).
• Process Knowledge: Understanding of business processes (Supply Chain, Finance, etc.) and the ability to translate high-level needs into AI use cases.
• Communication: Strong presentation skills to engage with both internal stakeholders and external Japanese enterprise executives.
• Education: Bachelor’s Degree required (Master’s in CS, Engineering, or Math preferred).

• Japan Market Experience: Previous experience working with Japanese companies as clients or partners is highly valued.
• Cultural Competency: Familiarity with Japanese business etiquette and communication styles.
• Hands-on AI implementation: Experience building agentic systems and deploying models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).
• LLM Ecosystem: Working knowledge of LangChain, LlamaIndex, or other OSS packages.

What is the InMobi family like?   

We are an infectious bunch. Be it the way we rise to challenges, the innovative products we create, the dreams we chase or the fun we have at work. We are sure that if you meet us, you will be infected too. Today, we are proud to be the leaders in Mobile advertising and are on an accelerated path of being a leader in enterprise software for marketers. We invite you to free yourself, dream big and chase your passion. We are here today because a few of us did just that.   

What can we promise?   

We offer you an opportunity to work on building enterprise platforms that require you to acquire, hone and demonstrate your ML and AI skills in designing and solving for complex problems, thereby creating software that creates value for our customers in a reliable, scalable, secure, and AI-first manner. At InMobi, you get to work on innovative technologies, work closely with business teams and grow as an overall technology leader.  

Modern work environment, flexible schedule, and smart, creative, down-to-earth people. Internal opportunities to move roles and try out bridge assignments with different teams.  Food for your soul – free meals all days of the week, gym, or yoga class to flex those biceps, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work.  

What is the team like?  

At InMobi Enterprise team, we are transforming the way finance, sales, marketing, people, and legal functions operate. We’re driving transformative work across Sales, Marketing, People, and Finance with ML and Agentic AI—and we’re looking for passionate innovators to join us!

What you will be doing

We are looking for a Data Scientist who can operate at the intersection of classical machine learning, GenAI and modern agentic AI systems with a strong engineering appetite. You will build and deploy intelligent AI/ML systems that will help transform the business process across the core. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.

Your responsibilities will include:

• Lead the experimentation, design and build of agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
• Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling.
• Design intelligent agents that can automate repetitive decision-making tasks—e.g., candidate generation tuning, feature selection, or context-aware content curation.
• Support POCs/ Pilots projects to explore and validate innovative technologies and solutions in ML/AI space.

• Build and operate machine learning models on diverse, high-volume data sources for forecasting, classification and prediction.
• Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
• Design pipelines for data preparation, model training, evaluation, and deployment in collaboration with engineering counterparts.
• Define best practices for monitoring ML model performance using statistical techniques; identifying drifts, failure modes, and improvement opportunities.
• Contribute to ML/AI thought leadership—blogs, case studies, internal tech talks, and industry conferences.
• Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
• Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.
• Document designs, development processes, and best practices to promote knowledge sharing and operational efficiency.

What do we expect from you?

We are seeking candidates with deep expertise in ML and hands-on experience building GenAI and Agentic AI systems.

Skillset: AI/ML Engineering, Python, LLM, RAG, Agentic AI, MCP, REST API

You should have experience with:

• Design, build, and deploy building LLM-powered applications, chatbots, and multi-agent systems to improve efficiency, accuracy, and decision-making.
• Implement and customize GenAI and multi-agent systems using AI frameworks such as LangChain, LangGraph, CrewAI, or similar.
• Create, refine, and maintain prompt templates, chains, and workflows.
• Integrate vector databases (MilvusDB, FAISS, Pinecone, Chroma, etc.) for semantic search and memory.
• Classical ML and deep learning techniques across NLP, clustering, and time series.
• Proficient in deploying ML workflows/models in production system. Continuous monitoring, evaluation, and retraining of models to ensure sustained performance. Ensuring model explainability, accuracy, compliance.
• Big data processing (Spark, distributed data systems) and cloud computing.
• Designing end-to-end ML solutions—from prototype to production.
• Stay updated with emerging AI/ML technologies and recommend relevant innovations for the finance domain.
• Drive in design reviews, sprint planning, and technical discussions.
• Collaborating effectively with diverse stakeholders, including technical teams and business leaders.
• Adapting to fast-paced environments and evolving priorities with high energy and autonomy.

We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.

 Qualifications

• Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
• 8+ years of industry experience in ML/Data Science, with deep proficiency in Python and one or more frameworks: PyTorch, TensorFlow, Scikit-learn.
• Solid understanding of ML fundamentals, regression, tree-based models, clustering, and time series.
• Hands-on experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
• Experience building Agentic frameworks such as LangGraph, AutoGen, CrewAI, n8n or ReACT-style agents.
• Expertise with algorithms in NLP, Time Series, and Deep Learning, applied on real-world datasets.
• Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
• Experience with Model Context Protocols (MCPs) — building or integrating MCP tools, servers, or capabilities.
• Comfortable working in cross-functional teams.
• Strong problem-solving and analytical skills with the ability to work in agile environments.
• Good understanding of data pipelines, APIs, and cloud platforms (Azure/GCP/AWS).
• Excellent communication skills with the ability to simplify complex technical concepts.

What You Will Be Doing

- Design and implement production-ready generative AI applications that serve millions of users, from initial architecture through deployment and monitoring
- Build advanced RAG (Retrieval-Augmented Generation) pipelines that combine vector databases, hybrid search, and intelligent caching to deliver sub-second response times
- Develop multimodal AI systems that seamlessly integrate text, vision, and audio capabilities using state-of-the-art models
- Architect scalable microservices that handle thousands of concurrent AI requests while optimizing for cost, latency, and reliability
- Lead code reviews and technical design sessions, establishing best practices and architectural patterns that elevate the entire team's capabilities
- Optimize large language models through fine-tuning techniques to achieve domain-specific performance improvements
- Implement comprehensive MLOps practices including automated testing, model versioning, A/B testing frameworks, and real-time monitoring dashboards
- Collaborate with product managers and stakeholders to translate complex business requirements into innovative AI solutions
- Deploy AI models across multiple cloud platforms (GCP) using containerization and orchestration technologies
- Create and maintain technical documentation, runbooks, and architectural decision records that enable knowledge sharing across teams
- Mentor junior engineers through pair programming, technical talks, and hands-on guidance to accelerate their growth
- Research and prototype emerging AI technologies to identify opportunities for competitive advantage

Gen AI Responsibilities

- Fine-tune and optimize state-of-the-art language models for specific business use cases, achieving significant improvements in accuracy and relevance
- Design multi-agent AI systems using frameworks to orchestrate complex workflows and decision-making processes
- Implement advanced prompt engineering strategies including Tree of Thoughts, ReAct patterns, and automatic prompt optimization to maximize model performance
- Build production-grade embedding systems that handle billions of vectors, implementing efficient indexing strategies and hybrid search capabilities
- Develop computer vision pipelines using models for tasks ranging from object detection to visual question answering
- Create secure AI applications with robust safeguards against prompt injection, jailbreaking, and data leakage while maintaining compliance with AI governance standards
- Optimize token usage and implement intelligent caching strategies to reduce costs by 50-70% while maintaining quality
- Design and implement evaluation frameworks that go beyond traditional metrics, incorporating human feedback loops and domain-specific quality measures
- Build real-time AI inference systems capable of processing streaming data with sub-100ms latency requirements
- Integrate multiple foundation models into unified applications, implementing fallback mechanisms and load balancing for high availability
- Develop custom tools and functions that extend LLM capabilities, enabling models to interact with databases, APIs, and external systems
- Implement advanced RAG techniques including contextual embeddings, cross-encoder reranking, and Graph RAG for complex reasoning tasks
- Create multimodal search systems that enable users to query across text, images, and documents using natural language
- Build AI-powered data processing pipelines that automatically extract, transform, and enrich unstructured data at scale
- Deploy edge AI solutions using frameworks like ONNX and TensorRT, optimizing models for resource-constrained environments

What We're Looking For

- 5+ years of hands-on experience building and deploying ML/AI systems, with at least 2+ years focused on generative AI and LLMs
- Expert-level Python programming skills with deep knowledge of async programming, multiprocessing, and performance optimization
- Strong experience with modern AI frameworks including PyTorch, Transformers, LangChain, and vector databases
- Proven track record of deploying AI applications to production environments serving real users at scale
- Deep understanding of transformer architectures, attention mechanisms, and the latest advances in generative AI
- Experience with cloud platforms (GCP) and containerization technologies (Docker, Kubernetes)
- Excellent communication skills with the ability to explain complex AI concepts to both technical and non-technical audiences
- Proven experience improving large-scale product search and discovery — including dense retrieval with bi-encoders, cross-encoder reranking, query understanding, and hybrid BM25 + vector search across catalogs of tens of millions of SKUs
- Hands-on experience building and deploying production multi-agent systems using orchestration frameworks such as LangGraph and Google ADK — designing stateful, tool-augmented agents for complex, real-world workflows
- Bachelor's degree in Computer Science, Mathematics, or related field (Master's preferred but not required with relevant experience)

Nice to Have

- Published research papers or significant contributions to open-source AI projects
- Experience with multimodal AI systems combining vision, language, and audio
- Domain expertise in specific verticals (healthcare, finance, legal, e-commerce)
- Knowledge of AI safety, alignment, and constitutional AI principles
- Experience building AI infrastructure and platforms used by other engineers
- Familiarity with emerging technologies like neural architecture search, mixture of experts, or neuromorphic computing

About the Role:

Glean is seeking a CA Industrial Trainee to support core finance and compliance functions while gaining hands-on exposure in a fast-paced, high-growth environment. In this role, you will work closely with the finance team on financial reporting, month-end close activities, payroll verification, audits, and regulatory compliance. You will assist with preparing financial statements, maintaining fixed asset registers, performing GL reconciliations, and supporting internal and statutory audits.This opportunity is ideal for a Chartered Accountancy student eligible for an Industrial Trainee position, with a strong foundation in accounting principles, attention to detail, and the ability to manage multiple priorities under tight deadlines.

You will: 

• Assist in the preparation and analysis of financial statements (Profit & Loss, Balance Sheet, Cash Flow) in compliance with accounting standards.
• Participate in month-end and year-end financial closing activities.
• Help prepare variance analysis and management reports.
• Assist in internal and statutory audits by providing necessary documents and information.
• Help review internal controls and suggest improvements for compliance and efficiency.
• Participate in the evaluation of operational risks and recommend risk mitigation strategies.
• Support Fixed Asset Register (FAR) maintenance, including tagging additions, disposals, transfers
• assisting with monthly depreciation runs and reconciliations between FAR and GL
• Assist with prepaid and insurance amortization schedules and related month‑end entries for India.
• Help with selected GL reconciliations and schedules (e.g., employee benefits, wellness reimbursements, other payroll‑related costs) using detailed GL/ FAR exports.
• Verify payroll master data, including employee names, designations, salary structures, and statutory deductions.
• Review of employee records for accurate start dates, termination dates, and any payroll adjustments such as bonuses, overtime, or deductions.
• Reconcile payroll accounts, ensuring accuracy and resolving any discrepancies.
• Assist in the preparation of payroll-related reports for internal and external stakeholders.
• Ensure compliance with corporate laws and regulations, payroll regulations, and other applicable financial laws.
• Stay updated with changes in accounting standards, tax laws, and payroll regulations.
• Participate in special projects or assignments as requested by the finance leadership team.
• Provide support in business process improvements and automation initiatives.

About you:

• Pursuing Chartered Accountancy and eligible for an Industrial Trainee position with 12 months+ of articleship remaining.
• Prior exposure to financial reporting, payroll management, auditing, and taxation during articleship would be an added advantage.
• Good understanding of accounting principles, payroll processes, and financial concepts.
• Basic knowledge of payroll regulations, direct and indirect taxes (Income Tax, GST).
• Proficiency in MS office and  accounting. Knowledge of ERP would be an added advantage.
• Analytical skills with attention to detail.
• Good communication and interpersonal skills.
• Ability to work under tight deadlines and manage multiple tasks.

Location: 

• This role is hybrid (4 days a week in our Bangalore office)

Compensation & Benefits:

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience.

We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

#LI-HYBRID

Purpose of the Job :

As members of 6sense’s Security department, the Security Engineering team protects the platform across application, infrastructure, and cloud domains. The Vulnerability Operations function ensures that vulnerabilities are identified, triaged, validated, and remediated in a consistent, timely, and risk‑based manner. Senior Security Engineers work closely with Engineering, CloudOps, Product, and GRC teams to operationalize vulnerability management processes, build automation, standardize workflows, and ensure secure-by-default practices. 

Responsibilities & Accountabilities :

• Ensure vulnerability management tools (e.g., Wiz, Invicti, Rapid7, GHAS, Ox) are correctly configured for appropriate coverage and accurate detection. 
• Perform hands-on triage, validation, and root cause analysis of vulnerabilities across AppSec, InfraSec, and CloudSec. 
• Track and report vulnerability status against SLAs, escalating to engineering owners as needed. 
• Build and maintain dashboards, filters, reports, and triage scripts to support visibility and automation. 
• Assist engineering teams in reproducing and remediating vulnerabilities, providing actionable guidance. 
• Support the bug bounty program operations (not ownership), including validation and coordination with engineering teams. 
• Conduct security reviews and threat modeling for high-risk systems or changes. 
• Participate in initiatives that holistically address systemic or multi‑domain vulnerabilities. 
• Contribute to development of automated security testing pipelines for validation of fixes. 
• Participate in on-call or off‑hours incident response related to critical vulnerabilities and time‑sensitive patches. 
• Contribute to quarterly OKRs and security engineering roadmap initiatives. 

Performance Measurement :

• Understands 6sense’s product, architecture, cloud footprint, and environment in depth. 
• Takes ownership of vulnerability triage and prioritization while escalating where required. 
• Proactively identifies and escalates AI/ML‑related vulnerabilities or misconfigurations in systems integrating LLMs or automated decisioning. 
• Meets tight deadlines and SLAs for vulnerability response and validation. 
• Maintains accurate and up-to-date triage scripts, documentation, dashboards, and workflows. 
• Participates in weekly 1:1s and skip levels; provides clear progress updates. 
• Supports security engineers and development teams with accurate, actionable analysis. 
• Effectively participates in incident response and post‑incident remediation. 

Educational and Experience Requirements :

• 5+ years of experience in security engineering across vulnerability management, AppSec, CloudSec, or InfraSec. 
• Experience with vulnerability tools (e.g., Wiz, Rapid7, Invicti, GHAS, SAST/DAST) and triage workflows. 
• Understanding of cloud security (AWS preferred) and modern microservices architectures. 
• Experience identifying and mitigating AI/ML‑related security risks, including model abuse, prompt‑injection vulnerabilities, and risks introduced by LLM‑based features. 
• Experience with scripting/automation (Python, Bash, JavaScript, etc.). 
• Experience working directly with engineering teams to address vulnerabilities. 
• Familiarity with frameworks such as OWASP, NIST, CIS Benchmarks, MITRE ATT&CK. 
• Experience with IaC security (Terraform, CloudFormation, Pulumi) preferred but not required. 

Preferred Qualifications :

• Bachelor's degree in a related field 
• Relevant industry certifications, such as AWS, CNCF, and GIAC are highly desirable 

Competencies and Behaviors :

• Establishes strong credibility with engineering partners. 
• Maintains a professional, outcome-focused demeanor. 
• Advocates for vulnerability and security best practices. 
• Works independently on complex triage and analysis tasks. 
• Manages competing priorities effectively, escalating when appropriate. 
• Communicates clearly across technical and non-technical audiences. 
• Maintains accuracy, attention to detail, and documentation hygiene. 

Role Description

• 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.

Key Responsibilities:

• 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 Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 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.
• Experience in Oil & Gas industry is must.
• 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)