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. 

Job Summary

The Principal Applied AI Engineer will lead the development of internal AI capabilities that empower teams across Poppulo to work faster, smarter, and securely. This role partners with business leaders, engineers, and IT teams to identify high-value opportunities for AI and translate them into practical solutions including GPT assistants, AI agents, and automated workflows while protecting company data, customer trust, and regulatory compliance.

Reporting to the Chief Information Security Officer, this position focuses on driving internal AI innovation effectively and safely across the organization.

The ideal candidate combines strong AI skills & security engineering with a passion for turning cutting-edge AI capabilities into real outcomes.

Primary Responsibilities

• Define the technical direction and implementation standards for internal AI solutions, ensuring consistent, secure, and scalable adoption across teams.
• Provide technical leadership across internal AI initiatives by evaluating solution approaches, guiding technical decisions, and balancing business value, feasibility, and risk.
• Lead the design and deployment of internal AI solutions such as GPT assistants, AI agents, integrations, and automated workflows.
• Implement technical controls, monitoring, and safeguards for AI-enabled systems.
• Develop integrations between AI systems and enterprise platforms including internal tools, knowledge bases, and business applications.
• Partner with business teams to identify and deliver AI solutions that improve productivity and operational efficiency.
• Work with Security, Privacy, and Legal teams to ensure AI solutions align with internal policies, compliance requirements, and regulatory standards.
• Collaborate with IT, Engineering, and DevOps teams to ensure AI solutions are reliable, secure, and scalable.

Leadership Responsibilities

Although this role is an individual contributor, the Principal Applied AI Engineer will:

• Be a technical advisor to the CISO and business leaders on AI capabilities and risks.
• Encourage experimentation and innovation while ensuring AI solutions are deployed with appropriate safeguards.
• Foster cross-functional collaboration between IT, Security, Engineering, Product Development, and business units.

Qualifications

• 8+ years of experience in AI engineering, or machine learning engineering.
• Hands-on experience designing and implementing AI security controls and guardrails, including mitigation of prompt injection, data exfiltration risks, output validation, monitoring and access control for AI systems.
• Experience designing and deploying AI assistants, GPT-based tools, or agent-driven workflows integrated with enterprise systems or internal data.
• Strong experience securing and integrating APIs, MCP, automation frameworks, and enterprise systems.
• Experience working with AI model platforms or APIs such as OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, or similar technologies.
• Experience building systems within cloud environments (AWS, Azure, or GCP).
• Ability to translate business requirements into scalable AI solutions while considering speed, security, reliability, and enterprise operational needs.

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.

Platform Manager QE – SaaS Platform 

Location: Coimbatore / Bangalore
Experience: 10 to 14 Years

Who we are and What we do?

AppViewX is trusted by the world’s leading global organizations to reduce risk, ensure compliance, and increase visibility through machine identity management and application infrastructure security and orchestration. At AppViewX, you will get to work with our bleeding edge Automation Platform that facilitates digital transformation through streamlined workflows to prevent outages, reduce security incidents and protect both an enterprise’s reputation and bottom line. AppViewX has also been certified as a Great Place to Work in India, cementing us as an employer of choice.

Glimpse of our Team

The core of AppViewX quality lies in building predictable releases through strong engineering discipline, automation-first practices, and measurable quality outcomes. Our Platform Quality Engineering team partners closely with Platform Engineering, SRE, and Product Engineering to ensure platform reliability, scalability, and resilience under real-world workloads.

As a Platform Manager QE, you will focus on validating how the platform behaves at scale, ensuring multi-tenant SaaS stability, upgrade safety, and non-functional excellence as the platform evolves.

What will you be responsible for?

• Own end-to-end platform quality outcomes, ensuring reliability, scalability, and stability across SaaS and customer-hosted deployments
• Define and execute a platform quality strategy aligned to SaaS scale, multi-tenancy, and infrastructure evolution
• Drive non-functional quality leadership, including:
  • Performance (P95/P99 latency, throughput)
  • Scalability (load, stress, capacity limits)
  • Reliability (failover, recovery, resilience)
  • Chaos testing (node, network, dependency failures)
• Validate platform behavior across:
  • Kubernetes-based deployments
  • Service mesh (Istio) and API gateway
  • Core platform services (auth, async jobs, notifications, logging)
• Ensure tenant isolation and noisy-neighbor impact validation in multi-tenant SaaS environments
• Own platform upgrade and deployment quality, including:
  • Backward compatibility
  • Data migration integrity
  • Configuration drift across environments
• Establish and govern continuous testing and QAOps practices for platform validation, including:
  • Production-like environments
  • CI/CD quality gates
  • Observability-driven validation (logs, metrics, traces)
• Drive platform-level automation strategy across API, performance, and resilience testing
• Provide platform readiness inputs to release certification, ensuring production-safe releases
• Analyze production incidents, performance degradations, and instability patterns, and drive preventive quality improvements
• Track and publish platform quality metrics (latency, stability, failure rates, incident trends) to guide engineering and leadership decisions
• Partner with Platform Engineering, SRE, and Product teams to identify and resolve systemic platform issues without impacting delivery velocity
• Lead, mentor, and grow a team of QE engineers focused on distributed systems, performance engineering, and reliability validation
• Influence architecture and design decisions to improve testability, scalability, and resilience outcomes
• Drive AI-assisted QE initiatives for performance analysis, anomaly detection, and intelligent regression optimization

What do we require? (Must Have)

• 10–14 years of experience in Quality Engineering with strong exposure to SaaS platforms and distributed systems
• Proven experience in non-functional testing:
  performance, scalability, reliability, chaos engineering
• Strong expertise in API and service-level automation (Python-based frameworks preferred)
• Hands-on experience with performance testing tools (JMeter, k6, Gatling, or similar)
• Experience with Kubernetes, containerized environments, and service mesh (Istio)
• Strong understanding of multi-tenant SaaS architectures and platform behavior under load
• Experience integrating quality practices into CI/CD pipelines and QA Ops workflows
• Strong debugging and root-cause analysis skills for production-scale issues
• Experience working with observability tools (Prometheus, Grafana, ELK, tracing systems)
• Strong Linux systems knowledge and environment troubleshooting skills
• Understanding of networking, security, and infrastructure concepts (TLS, DNS, load balancing)
• Strong stakeholder communication and ability to translate platform quality risks into business impact

What do we desire?

• Experience in cloud platforms (AWS / Azure / GCP) and hyperscaler environments
• Exposure to chaos engineering frameworks and reliability validation tools
• Experience with contract testing and service-level validation strategies
• Familiarity with AI-driven test optimization, anomaly detection, or quality intelligence
• Strong understanding of high-availability systems and distributed system failure modes

What You Bring as a Platform QE Manager at AppViewX

• You think in systems, scale, and failure modes, not just test cases
• You ensure platform reliability under real workloads, not just functional correctness
• You drive non-functional quality as a release gate, not a post-release activity
• You build predictable platform behavior through automation, observability, and continuous validation
• You translate technical platform risks into customer and business impact
• You mentor teams to move from test execution to engineering-driven quality ownership
• You operate with strong ownership, data-driven decisions, and disciplined escalation

What brings us together?

What makes us stand out from the rest is the people. The people who push hard every day to be smarter, passionate, resilient, creative, inclusive and curious. Surrounding ourselves with a bunch of diverse and talented minds has made us what we are, and we can't wait to see the positive impact it would have on you too!

What’s more in store?

AppViewX offers competitive benefits including incentives, health & wellness policies, investment schemes, flexible work models, and strong learning & development opportunities. We empower our employees with flexibility, ownership, and trust to drive impact.

Why AppViewX?

AppViewX serves Fortune 1000 enterprises globally, including leading banks, media companies, and healthcare providers. With a strong global presence and deep customer trust, we continue to scale our platform and engineering capabilities to solve critical enterprise challenges.

Equal Opportunity Statement

AppViewX is an Equal Employment Opportunity Employer committed to diversity, inclusion, and fair employment practices.

Who we are

About Stripe

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

About the Organization 

Stripe Infrastructure is responsible for the reliability, scale, performance, and cost of Stripe’s systems and the productivity and sentiment of Stripe’s people. You may work on a wide variety of critical business areas including: 

• Core Infrastructure: We’re the home for Stripe's critical tier 0 infrastructure systems (Compute, Networking, DocumentDB, Distributed Caching and High assurance engineering). We build the foundational platform for Stripe products and services to allow them to operate at scale. We drive reliability, availability, efficiency and scalability of these systems.
• Developer Infrastructure: We’re responsible for the productivity of all developers at Stripe. Ensure Stripe’s engineers have a reliable, fast, and easy-to-use inner dev loop to maximize productivity while building everything from low-latency microservices to large-scale data pipelines and machine learning models.
• Security : We’re a newly formed security team tasked with building the guardrails to extend Stripe’s secure platform, allowing engineers to leverage new technologies that best meet their needs. We work on enabling new technologies for product and platform teams, prioritizing on business needs as well as building the tooling and controls that further enables self-serve, guaranteeing a high bar is maintained across all Stripe surfaces with security in-built into foundations.
• Application and Revenue Platform: Building the powerful and scalable infrastructure that powers the company’s innovative application offerings and supports the seamless processing and management of Stripe’s global transaction volumes.

Team Matching: exact team matching for one of the subteams within one of these orgs will begin during final stages. Please note we may also consider you for different orgs based on your experience, location, etc. 

What you’ll do

We’re looking for Software Engineers who are interested in building software services and platforms that impact thousands of employees and millions of Stripe users, regardless of whether they’re an end user, developer, or partner. You will work on projects that span technologies, systems, and processes where you will design, build, test, and ship great code every day.

Responsibilities

• Build a great customer experience for internal and external Stripe teams using our infrastructure
• Participate in roadmap planning and prioritization
• Deliver value through a strong collaborative approach with multiple customers and stakeholders across Stripe
• Debug production issues across services and several levels of the stack

Who you are

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

Minimum requirements

• 6-12+ years of industry software engineering experience (does not include internships or co-ops)
• Ability to write well-factored algorithms and have experience with commonly used data structures and algorithms
• Hands-on experience contributing to or building large scale distributed systems
• Strong coding skills in any programming language (we understand new languages can be learned on the job so our interview process is language agnostic)
• Strong collaboration skills, can work across workstreams within your team and contribute to your peers’ success
• Have the ability to thrive on a high level of autonomy, responsibility, and think of yourself as entrepreneurial
• Interest in working as a generalist across varying technologies and stacks to solve problems and delight both internal and external users

Preferred Qualifications

• Experience optimizing the end to end performance of distributed systems
• Focuses on the needs of our users, both internal and external
• Hold yourself and others to a high bar when working with production

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 an experienced Staff Machine Learning Engineer to join our Engineering team. This role is based in Bangalore, reporting to the Senior Engg. Manager - Data + AI.

You will be responsible for designing and developing large scale ML Systems that analyze massive volumes of network data to detect anomalies, threats, and patterns in near real-time. You’ll solve complex real-world business problems by partnering closely with data architects and product teams to deliver impactful automation and intelligence, including the design and orchestration of specialized autonomous agents.

What you’ll do (Role Expectations)

• Build and maintain large-scale distributed systems to support the full ML lifecycle, including data collection, feature engineering, and Agentic AI components like agent workflows and real-time serving
• Solve complex business problems such as threat detection by collaborating with data architects and product teams to build multi-agent solutions that automate analysis and decisioning
• Partner with cross-functional teams to assess requirements, manage scheduling, and lead the development and debugging of agent-based systems
• Support the rollout and monitoring plans for production-grade ML systems to ensure performance, observability, and scalability

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)

• 5+ years of experience as an AI-ML Engineer with technical proficiency in Java, Springboot, Python, and PyTorch or TensorFlow
• Proven experience writing high-performance queries for large-scale analytics platforms such as Azure Data Explorer (ADX/Kusto) or Google BigQuery, including partitioning-aware patterns
• Deep expertise in designing and deploying anomaly detection using tree-based models, statistical techniques, and streaming ML approaches
• Hands-on experience developing multi-agent orchestration, agent-to-agent communications, and autonomous decision-making workflows
• Strong technical background with distributed infrastructure and public cloud platforms like Azure, GCP, or AWS

What Will Make You Stand Out (Preferred Qualifications)

• A track record of shipping end-to-end applications at scale that process billions of events
• Willingness to work across the full spectrum of Big Data and AI-based solutions
• Hands-on experience with SOTA AI frameworks, prompt engineering, and complex agent architectures

#LI-Bangalore #LI-AN4

Role

We are looking for an experienced Staff Machine Learning Engineer to join our Engineering team. This role is based in Bangalore, reporting to the Manager, Machine Learning Engineering. You will be responsible for building and maintaining large-scale distributed systems that power our entire ML pipeline, from data collection to real-time serving. You'll solve complex real-world business problems by partnering closely with data scientists and product teams to deliver impactful automation and intelligence.

What you’ll do (Role Expectations)

• Build and maintain large-scale distributed systems to support the whole pipeline including data collection, feature engineering, model training, model evaluation, model deployment, and real-time serving
• Develop functional specifications, assess task requirements and scheduling, and participate in the development, debug, and support
• Solve complex real-world business problems like threat detection and business intelligence by working closely with stakeholders including data scientists, product management, and product engineering teams

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)

• 5+ years of experience as a Software Engineer or ML Engineer
• Experience with applying machine learning for improving key business metrics, optimized models for accuracy, latency
• Experience with researching newer techniques, and innovating for building ML based solutions
• Experience with algorithms in building out data collection/processing infrastructure, Machine Learning model training, and serving platforms
• Deep expertise with cloud infrastructure (AWS)

What Will Make You Stand Out (Preferred Qualifications)

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

#LI-Hybrid #LI-AN4

Role

We’re looking for a Full Stack Software Engineer to join our team. This role is based in Bangalore, India, reporting to the Sr. Manager of Software Engineering within the Risk360 department You will join the team that built the world’s largest cloud security platform from the ground up to help organizations worldwide harness speed and agility with a cloud-first strategy. In this role, you will be a key contributor to our multitenant architecture, enabling the delivery of innovative services to over 15 million users across 185 countries.

What you’ll do (Role Expectations)

• Develop product features related to data transformations, enrichment, analytics, and user-facing dashboards
• Design and implement intuitive, performant web applications using ReactJS for data visualization and user interaction
• Build and maintain data processing pipelines to handle data ingestion, transformation, and analysis for risk quantification
• Establish monitoring mechanisms to track data platform performance and health while defining maintenance procedures
• Collaborate closely with UX/UI designers and backend engineers to deliver seamless end-to-end solutions

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)

• 3+ years of experience in software development for enterprise solutions, including web-based applications
• 1+ years of experience in ReactJS or similar modern JavaScript frameworks, including component-based architecture and state management
• Solid experience in Core Java, Concurrency, Distributed Computing, and proficiency in SQL
• Exposure to Test Driven Development (TDD) using frameworks such as JUnit, REST Assured, TestNG, or Jest
• Experience with HTML5, CSS3, JavaScript/ES6+, and building responsive interfaces

What Will Make You Stand Out (Preferred Qualifications)

• Experience developing scalable web applications handling large datasets efficiently and working knowledge of GraphQL
• Expertise in state management frameworks like Redux and performance optimization including tuning JVM
• Understanding of security compliance frameworks, statistics, and machine learning

#LI-Hybrid #LI-AN4

Role 

We are looking for a Staff Machine Learning Engineer to join our Exposure Management & Security Operations team. This role is a hybrid position based in Bangalore, reporting to the Sr. Manager, Engineering Strategy, Planning & Analytics. You will join the team that built the world’s largest cloud security platform from the ground up, helping to scale a multitenant architecture that serves over 15 million users globally. Your vision and passion will be critical as we continue to innovate and enable organizations to harness the speed and agility of a cloud-first strategy.

What you’ll do (Role Expectations)

• Designing and deploying scalable, reliable, and efficient production-grade Gen AI/ML systems from data ingestion to monitoring
• Driving innovation by researching and evaluating emerging AI/ML frameworks, rapidly prototyping novel solutions, and championing full-scale implementation
• Implementing and maintaining robust MLOps practices, including logging, monitoring, and CI/CD pipelines for distributed ML systems
• Leading and mentoring junior engineers in system design best practices and promoting technical excellence
• Collaborating with cross-functional teams to translate complex business needs into technical solutions

Who You Are (Success Profile)

• You thrive in ambiguity and are comfortable building the path as you walk it, seeing dynamic environments as the raw material to build something meaningful.
• You act like an owner with a passion for the mission and a bias for action, navigating seamlessly between high-level strategy and hands-on execution.
• You are a problem-solver who seeks out challenges because you are energized by finding solutions that deliver the biggest impact.
• You are a learner with a growth mindset, actively seeking feedback to become a better partner and a stronger teammate.
• You are driven by innovation and have a deep curiosity for how things work, believing in the power of technology to accelerate transformation.

What We’re Looking for (Minimum Qualifications)

• At least 5 years of experience as a Machine Learning Engineer with a track record of shipping complex, scalable ML systems to production
• Proven experience building Gen AI/ML systems with LLMs, fine-tuning, Retrieval-Augmented Generation (RAG), and Agentic AI in production environments
• Experience designing and implementing distributed ML systems with deep knowledge of MLOps, including monitoring and logging
• Strong computer science foundation in data structures, algorithms, and system design with expertise in Python and SQL
• Excellent communication and interpersonal skills to partner effectively across global engineering teams

What Will Make You Stand Out (Preferred Qualifications)

• Expertise with cloud services such as AWS, GCP, or Azure and ML platforms like Kubeflow or SageMaker
• Proficiency in systems programming languages like Go or Rust with an understanding of distributed systems and networking fundamentals
• A record of research, publications, or patents in AI/ML

#LI-Hybrid #LI-VV3

Role

We are looking for a Staff Information Security Engineer to join our Cyber and Data Security team. This is a Bangalore based role, reporting to the Director, Information Security Engineering. You will lead pentesting efforts across our applications and infrastructure while conducting deep security architecture reviews. By prioritizing vulnerabilities and driving security automation, you will serve as a critical partner to our engineering and operations teams in safeguarding our global ecosystem.

What you’ll do (Role Expectations)

• Perform advanced pen-testing on applications and infrastructure to identify and mitigate risks

• Conduct security architecture reviews and provide strategic recommendations for complex systems

• Partner with engineering and operations teams to prioritise vulnerabilities for remediation

• Design and implement security automation to streamline repetitive tasks and improve efficiency

• Lead security assessments across web applications, thick clients, and APIs

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)

• 5+ years of experience in manual security assessments using industry-leading tools for web applications, thick clients, and APIs

• Expertise in thick client penetration testing across Windows, Mac, Linux, Android, and iOS platforms

• Proven experience conducting security architecture reviews in network security and complex application environments

• Strong fundamental knowledge of security concepts, cryptography, Unix architecture, and networking

• Ability to read and debug programming languages such as C/C++, Java, or Javascript to identify security weaknesses

What Will Make You Stand Out (Preferred Qualifications)

• Proven ability to validate findings and perform thorough root cause analysis

• Advanced scripting knowledge used to automate repetitive security tasks and research

• Experience or interest in emerging security research areas including Container, AI/ML, or Cloud security

#LI-Hybrid #LI-PM5

We’re looking for a Senior Data Engineer to design, build, and operate the data pipelines and aggregates that power Zeta’s AdTech platform. This is a hands-on individual contributor role focused on high-scale batch + streaming data processing, reliable data products, and analytics-ready datasets that enable prediction, agentic workflows, BI reporting, and measurement. You will partner closely with backend, ML, and product teams to deliver trusted, well-modeled data with strong performance, quality, and observability.

What You’ll Do

• Build data pipelines: Develop robust batch and streaming pipelines (Kafka/Kinesis) to ingest, transform, and enrich large-scale event data (impressions, clicks, conversions, costs, identity signals).
• Create data aggregates & marts: Design and maintain curated aggregates and dimensional models for multiple consumers—prediction models, agents, BI dashboards, and measurement workflows.
• Data modeling & contracts: Define schemas, data contracts, and versioning strategies to keep downstream systems stable as sources evolve.
• Data quality & reliability: Implement validation, anomaly detection, backfills, and reconciliation to ensure completeness, correctness, and timeliness (SLAs/SLOs).
• Performance & cost optimization: Optimize compute/storage for scale (partitioning, file sizing, incremental processing, indexing), balancing latency, throughput, and cost.
• Orchestration & automation: Build repeatable workflows with scheduling/orchestration (e.g., Airflow, Dagster, Step Functions) and CI/CD for data pipelines.
• Observability for data systems: Instrument pipelines with metrics, logs, lineage, and alerting to accelerate detection and root-cause analysis of data issues.

Security & governance: Apply least-privilege access, PII-aware handling, and governance controls aligned with enterprise standards.

5+ years building production data pipelines and data products (batch and/or streaming) in a high-scale environment.

Strong experience with SQL and data modeling (dimensional modeling, star/snowflake schemas, event modeling).

• Hands-on experience with streaming systems (Kafka preferred) and/or AWS Kinesis, including event-driven designs.
• Proficiency in one or more languages used for data engineering (Python, Java, Scala, or Go).
• Experience with distributed data processing (Spark, Flink, or equivalent) and performance tuning at scale.
• Experience with AWS data services and cloud-native patterns (S3, Glue/EMR, Athena, Redshift, etc. as applicable).
• Familiarity with lakehouse/table formats and large-scale storage patterns (e.g., Parquet; Iceberg/Hudi/Delta are a plus).
• Experience with orchestration/workflow tooling (Airflow/Dagster/Step Functions) and CI/CD for data workloads.
• Strong data quality/observability practices (tests, monitoring, lineage; understanding of SLAs/SLOs).
• Experience with SQL + NoSQL data stores (e.g., Postgres/MySQL; DynamoDB/Cassandra/Redis) and choosing the right store per use case.

Clear communicator and collaborator; able to work with mixed audiences and translate needs into reliable data interfaces.

• AdTech / programmatic advertising domain knowledge: DSP/SSP/exchange/RTB concepts and data flows.
• Experience building measurement pipelines (attribution, incrementality, lift, or experimentation analytics).

Experience supporting ML feature stores, offline/online feature generation, or model training datasets.

• Experience with real-time analytics stores (Druid/ClickHouse/Pinot) and high-cardinality aggregation strategies.
• Deep knowledge of data governance/privacy, including PII handling and consent-aware data processing.
• Open-source contributions, publications, or conference speaking.
• BS/MS in CS/Engineering or equivalent practical experience.

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 

Greetings From Zeta Global !!

Zeta Marketing Platform (ZMP) is a machine learning/AI powered customer acquisition and CRM multi-tenant platform. The backend developer will work on server-side APIs and services that enable a highly distributed event pipeline and a stack that gets tens of thousands of messages per second.

As a senior member of the Software Engineering team, you will join the group responsible for designing, developing, and owning the distributed systems CRM platform for Zeta. You will collaborate with your fellow Engineers and Product Managers to develop a roadmap and subsequent projects to build the next generation comprehensive, multichannel marketing solution that unifies and unlocks data across digital touch points, driving return on marketing investment.

You should have a deep knowledge of distributed systems and cloud architecture. You will need extensive design and development experience and be passionate about working with high-throughput systems where the issues of throughput, performance, redundancy, and concurrency are paramount.

Key Responsibilities:

As a Senior Software Developer, you will be:

• Responsible for independently and cooperatively understanding business requirements, designing, and implementing core components for real-world marketing automation platform.
• Designing, implementing application code to satisfy product requirements
• Ensuring high product quality through rigorous code reviews and unit tests
• Fixing bugs and implementing enhancements
• Taking ownership of a significant product component in design and implementation

Requirements:

• We are looking for exceptional talent with superior academic credentials and a solid foundation in computer sciences and distributed systems design and development.
• The candidate will have had at least 4 years of experience developing scalable, robust software platforms using Java/Ruby/Python or an equivalent language.
• An undergraduate degree in Computer Science (or a related field) from a university where the primary language of instruction is English is strongly desired.
• Strong communication skills in a large-distributed development team environment are essential.

Qualification:

• BS or MS in Computer Science or related field
• 5+ years of working experience with Python, Ruby and/or J2EE technology or equivalent OO paradigm
• Strong knowledge and experience with Kafka, Elastic Search, NoSQL databases such as Aerospike, Thrift, CI, and AWS.
• Experience working with container-based solutions is a plus.
• Experience working in a fast-paced technology environment.
• Strong object-oriented programming and design skills.
• Excellent problem solving, critical thinking, and communication skills.
• Ability and desire to learn new skills and take on new tasks.

Company Summary

Zeta Global is a data-powered marketing technology company with a heritage of innovation and industry leadership. Founded in 2007 by entrepreneur David A. Steinberg and John Sculley, former CEO of Apple Inc and Pepsi-Cola, the Company combines the industry’s 3rd largest proprietary data set (2.4B+ identities) with Artificial Intelligence to unlock consumer intent, personalize experiences and help our clients drive business growth.

Our technology runs on the Zeta Marketing Platform, which powers ‘end to end’ marketing programs for some of the world’s leading brands. With expertise encompassing all digital marketing channels – Email, Display, Social, Search and Mobile – Zeta orchestrates acquisition and engagement programs that deliver results that are scalable, repeatable and sustainable.

Zeta Global is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, gender, ancestry, color, religion, sex, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Zeta Global Recognized in Enterprise Marketing Software and Cross-Channel Campaign Management Reports by Independent Research Firm

https://www.prnewswire.com/news-releases/zeta-global-opens-ai--data-labs-in-san-francisco-and-nyc-300945353.html

https://www.prnewswire.com/news-releases/zeta-global-recognized-in-enterprise-marketing-software-and-cross-channel-campaign-management-reports-by-independent-research-firm-300938241.html

As a Staff Backend Engineer, you will be a highly technical individual contributor responsible for designing, building, and optimizing the backend systems that power our low-latency ad platform. You will take the lead in developing scalable microservices and streaming data infrastructure to handle high-throughput workloads with minimal latency. This role requires deep expertise in distributed systems and real-time data processing (ideally in the programmatic advertising domain) to ensure our systems remain highly performant and reliable. You’ll work closely with product managers, data scientists, and other engineering teams to translate business needs into technical solutions and ensure the platform is fast, fault-tolerant, and observable. This role is based in the United States and can be performed remotely, with a preference for candidates who can join us in a hybrid capacity in San Francisco, New York, or Atlanta.

Responsibilities:

• System Architecture & Development: Lead the design and implementation of scalable, high-performance backend services, including microservices and APIs, that can efficiently handle large volumes of requests with low latency. Ensure the architecture accommodates real-time bidding and personalization use cases common in AdTech.
• Streaming Data Infrastructure: Develop and maintain streaming data pipelines and event-driven systems to process and analyze continuous data flows in real time (e.g., using Apache Kafka). Optimize data ingestion and processing for timeliness and accuracy to support downstream analytics and machine-learning models.
• Performance & Reliability: Ensure the backend systems are highly performant, resilient, and stable under heavy load. Implement robust fault-tolerance mechanisms and optimize for low-latency response times in a high-concurrency environment. Leverage observability best practices (comprehensive monitoring, logging, and tracing) to enable engineers to quickly analyze system behavior and take proactive measures to boost performance and reliability.
• Cross-Functional Collaboration: Work closely with cross-functional teams – including Product, Data Science, DevOps, and Frontend – to translate business requirements into scalable technical solutions. Facilitate effective communication and collaborative problem-solving to deliver new features and improvements that align with our product roadmap.
• Technical Leadership & Mentorship: Provide technical leadership within the engineering team without direct managerial duties. Guide and mentor junior engineers through code reviews, design discussions, and best practice adoption, fostering a culture of technical excellence and continuous improvement.
• Technical Strategy & Innovation: Stay abreast of emerging technologies and industry trends (e.g. new AWS services, streaming frameworks, database technologies) and evaluate their potential benefit to our platform. Contribute to the technical roadmap, making build-vs-buy recommendations and driving innovation to keep our systems ahead of the curve.

Required Qualifications:

• 8+ years of software engineering experience building backend systems, with 3+ years in a senior or lead role (e.g. Staff Engineer, Principal Engineer) in the AdTech or a similar high-volume, low-latency domain.
• Proven track record in designing and building high-throughput, low-latency distributed systems that operate at scale (e.g. handling thousands of requests per second or more).
• Expertise in microservices architecture and distributed system design, including experience decomposing monoliths or building greenfield microservices with well-defined APIs.
• Proficiency in Java and Go for backend development, and experience with Python for scripting, automation, or data processing tasks.
• Hands-on experience with streaming data technologies and event-driven frameworks, such as Apache Kafka (or AWS Kinesis), and possibly stream processing frameworks (Spark Streaming, Flink, or similar, experience with Apache Kafka is highly desired).
• Strong experience with cloud platforms (AWS preferred) and deploying services in a cloud-native environment. Familiarity with AWS components like EC2, S3, Lambda, SNS/SQS, etc., and ability to design cost-effective, performant cloud architectures.
• Experience with both SQL and NoSQL databases for high-volume applications. Comfortable with technologies like PostgreSQL/MySQL as well as key-value or wide-column stores (e.g. DynamoDB, Cassandra, Redis) for caching and fast lookups.
• Familiarity with containerization and orchestration tools (Docker, Kubernetes) and CI/CD pipelines to build and deploy microservices reliably.
• Deep understanding of system observability and monitoring – experience instrumenting applications and using monitoring/logging tools to ensure visibility into system performance (e.g. Prometheus, Grafana, ELK stack or similar).
• Excellent problem-solving and communication skills. Ability to communicate complex technical concepts clearly to cross-functional team members and stakeholders. Proven collaboration skills in an agile development environment.

Preferred Qualifications:

• Domain Expertise: Deep knowledge of the programmatic advertising ecosystem, including how Demand-Side Platforms (DSPs), Supply-Side Platforms (SSPs), ad exchanges, and real-time bidding (RTB) work together. Prior experience building or optimizing components of a DSP or ad server is a strong plus.
• High-Scale Data Processing: Experience designing systems that operate at extreme scale, such as real-time auction systems or high-frequency trading platforms, and optimizing algorithms for latency and throughput (e.g. understanding of auction theory or bidding optimization strategies).
• Data Pipelines & Analytics: Familiarity with big data processing and analytics pipelines (Spark, Hadoop, or columnar data stores) for batch and streaming workloads. Experience with data warehousing or real-time analytics databases (e.g. Druid, ClickHouse) is a plus.
• Advanced Performance Tuning: Demonstrated experience in performance profiling and optimization (e.g. JVM tuning, concurrency, GC optimization, network I/O) in large-scale Java or Go applications.
• Leadership in the Tech Community: A track record of contributing to open-source projects, technical publications, or speaking at industry conferences. Keeping on top of emerging trends and sharing knowledge both inside and outside the organization.
• Education: Bachelor’s degree in Computer Science, Engineering, or related field (Master’s or Ph.D. a plus), with strong foundations in algorithms and data structures.

Company Profile:

Zeta Global is a NYSE listed data-powered marketing technology company with a heritage of innovation and industry leadership. Founded in 2007 by entrepreneur David A. Steinberg and John Sculley, former CEO of Apple Inc and Pepsi-Cola, the Company combines the industry’s 3rd largest proprietary data set (2.4B+ identities) with Artificial Intelligence to unlock consumer intent, personalize experiences and help our clients drive business growth.

Our technology runs on the Zeta Marketing Platform, which powers ‘end to end’ marketing programs for some of the world’s leading brands. With expertise encompassing all digital marketing channels – Email, Display, Social, Search and Mobile – Zeta orchestrates acquisition and engagement programs that deliver results that are scalable, repeatable and sustainable.

Zeta Global is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, gender, ancestry, color, religion, sex, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.

ZETA IN THE NEWS!

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

Zeta Marketing Platform (ZMP) is a machine learning/AI powered customer acquisition and CRM multi-tenant platform. The backend developer will work on server-side APIs and services that enable a highly distributed event pipeline and a stack that gets tens of thousands of messages per second.

As a senior member of the Software Engineering team, you will join the group responsible for designing, developing, and owning the distributed systems CRI 1 platform for Zeta. You will collaborate with your fellow Engineers and Product managers to develop a roadmap and subsequent projects to build the next generation comprehensive, multichannel marketing solution that unifies and unlocks data across digital touch points, driving return on marketing investment.

You should have a deep knowledge of distributed systems and cloud architecture. You will need extensive design and development experience and be passionate about working with high-throughput systems where the issues of throughput, performance, redundancy, and concurrency are paramount.

 Key Responsibilities:

 As a Senior Software Developer, you will be:

• Responsible for independently and cooperatively understanding business requirements, designing, and implementing core components for real-world marketing automation platform.
• Designing, implementing application code to satisfy product requirements
• Ensuring high product quality through rigorous code reviews and unit tests
• Fixing bugs and implementing enhancements
• Taking ownership of a significant product component in design and implementation

Requirements:

• We are looking for exceptional talent with superior academic credentials and a solid foundation in computer sciences and distributed systems design and development.
• The candidate will have at least 4 years of experience developing scalable, robust sohware platforms using Java/Ruby/Python or an equivalent language.
• An undergraduate degree in Computer Science (or a related field) from a university where the primary language of instruction is English is strongly desired.
• Strong communication skills in a large-distributed development team environment are essential.
• Experience in Advertising Attribution domain is a plus

Requirements:

• BS or MS in Computer Science or related field
• 4 - 8 years of working experience with J2EE technology, Python or equivalent OO paradigm
• Strong knowledge and experience with Kafka, Elastic Search, Airflow, NoSQL databases such as Aerospike,Thrift, Cl, and AWS.
• Experience with SQL languages
• Experience working with container-based solutions is a plus.
• Experience working in a fast-paced technology environment.
• Strong object-oriented programming and design skills.
• Excellent problem solving, critical thinking, and communication skills.
• Ability and desire to learn new skills and take on new tasks.

 Company Profile:

Zeta Global is a NYSE listed data-powered marketing technology company with a heritage of innovation and industry leadership. Founded in 2007 by entrepreneur David A. Steinberg and John Sculley, former CEO of Apple Inc and Pepsi-Cola, the Company combines the industry’s 3rd largest proprietary data set (2.4B+ identities) with Artificial Intelligence to unlock consumer intent, personalize experiences and help our clients drive business growth.

Our technology runs on the Zeta Marketing Platform, which powers ‘end to end’ marketing programs for some of the world’s leading brands. With expertise encompassing all digital marketing channels – Email, Display, Social, Search and Mobile – Zeta orchestrates acquisition and engagement programs that deliver results that are scalable, repeatable and sustainable.

Zeta Global is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, gender, ancestry, color, religion, sex, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.

Zeta Global Recognized in Enterprise Marketing Software and Cross-Channel Campaign Management Reports by Independent Research Firm

https://www.forbes.com/sites/shelleykohan/2024/06/19/amazon-partners-with-zeta-global-to-deliver-gen-ai-marketing-automation/

https://www.cnbc.com/video/2024/05/06/zeta-global-ceo-david-steinberg-talks-ai-in-focus-at-milken-conference.html

https://www.businesswire.com/news/home/20240904622808/en/Zeta-Increases-3Q%E2%80%9924-Guidance

https://www.prnewswire.com/news-releases/zeta-global-opens-ai--data-labs-in-san-francisco-and-nyc-300945353.html

https://www.prnewswire.com/news-releases/zeta-global-recognized-in-enterprise-marketing-software-and-cross-channel-campaign-management-reports-by-independent-research-firm-300938241.html

We invite you to explore this opportunity to be a part of the Zeta family……

Should you need any assistance or require further information, please do not hesitate to contact us.

As a Staff Backend Engineer, you will be a highly technical individual contributor responsible for designing, building, and optimizing the backend systems that power our low-latency ad platform. You will take the lead in developing scalable microservices and streaming data infrastructure to handle high-throughput workloads with minimal latency. This role requires deep expertise in distributed systems and real-time data processing (ideally in the programmatic advertising domain) to ensure our systems remain highly performant and reliable. You’ll work closely with product managers, data scientists, and other engineering teams to translate business needs into technical solutions and ensure the platform is fast, fault-tolerant, and observable. This role is based in the United States and can be performed remotely, with a preference for candidates who can join us in a hybrid capacity in San Francisco, New York, or Atlanta.

Key Responsibilities

• System Architecture & Development: Lead the design and implementation of scalable, high-performance backend services, including microservices and APIs, that can efficiently handle large volumes of requests with low latency. Ensure the architecture accommodates real-time bidding and personalization use cases common in AdTech.
• Streaming Data Infrastructure: Develop and maintain streaming data pipelines and event-driven systems to process and analyze continuous data flows in real time (e.g., using Apache Kafka). Optimize data ingestion and processing for timeliness and accuracy to support downstream analytics and machine-learning models.
• Performance & Reliability: Ensure the backend systems are highly performant, resilient, and stable under heavy load. Implement robust fault-tolerance mechanisms and optimize for low-latency response times in a high-concurrency environment. Leverage observability best practices (comprehensive monitoring, logging, and tracing) to enable engineers to quickly analyze system behavior and take proactive measures to boost performance and reliability.
• Cross-Functional Collaboration: Work closely with cross-functional teams – including Product, Data Science, DevOps, and Frontend – to translate business requirements into scalable technical solutions. Facilitate effective communication and collaborative problem-solving to deliver new features and improvements that align with our product roadmap.
• Technical Leadership & Mentorship: Provide technical leadership within the engineering team without direct managerial duties. Guide and mentor junior engineers through code reviews, design discussions, and best practice adoption, fostering a culture of technical excellence and continuous improvement.
• Technical Strategy & Innovation: Stay abreast of emerging technologies and industry trends (e.g. new AWS services, streaming frameworks, database technologies) and evaluate their potential benefit to our platform. Contribute to the technical roadmap, making build-vs-buy recommendations and driving innovation to keep our systems ahead of the curve.

Required Qualifications:

• 8+ years of software engineering experience building backend systems, with 3+ years in a senior or lead role (e.g. Staff Engineer, Principal Engineer) in the AdTech or a similar high-volume, low-latency domain.
• Proven track record in designing and building high-throughput, low-latency distributed systems that operate at scale (e.g. handling thousands of requests per second or more).
• Expertise in microservices architecture and distributed system design, including experience decomposing monoliths or building greenfield microservices with well-defined APIs.
• Proficiency in Java and Go for backend development, and experience with Python for scripting, automation, or data processing tasks.
• Hands-on experience with streaming data technologies and event-driven frameworks, such as Apache Kafka (or AWS Kinesis), and possibly stream processing frameworks (Spark Streaming, Flink, or similar, experience with Apache Kafka is highly desired).
• Strong experience with cloud platforms (AWS preferred) and deploying services in a cloud-native environment. Familiarity with AWS components like EC2, S3, Lambda, SNS/SQS, etc., and ability to design cost-effective, performant cloud architectures.
• Experience with both SQL and NoSQL databases for high-volume applications. Comfortable with technologies like PostgreSQL/MySQL as well as key-value or wide-column stores (e.g. DynamoDB, Cassandra, Redis) for caching and fast lookups.
• Familiarity with containerization and orchestration tools (Docker, Kubernetes) and CI/CD pipelines to build and deploy microservices reliably.
• Deep understanding of system observability and monitoring – experience instrumenting applications and using monitoring/logging tools to ensure visibility into system performance (e.g. Prometheus, Grafana, ELK stack or similar).
• Excellent problem-solving and communication skills. Ability to communicate complex technical concepts clearly to cross-functional team members and stakeholders. Proven collaboration skills in an agile development environment.

Preferred Qualifications:

• Domain Expertise: Deep knowledge of the programmatic advertising ecosystem, including how Demand-Side Platforms (DSPs), Supply-Side Platforms (SSPs), ad exchanges, and real-time bidding (RTB) work together. Prior experience building or optimizing components of a DSP or ad server is a strong plus.
• High-Scale Data Processing: Experience designing systems that operate at extreme scale, such as real-time auction systems or high-frequency trading platforms, and optimizing algorithms for latency and throughput (e.g. understanding of auction theory or bidding optimization strategies).
• Data Pipelines & Analytics: Familiarity with big data processing and analytics pipelines (Spark, Hadoop, or columnar data stores) for batch and streaming workloads. Experience with data warehousing or real-time analytics databases (e.g. Druid, ClickHouse) is a plus.
• Advanced Performance Tuning: Demonstrated experience in performance profiling and optimization (e.g. JVM tuning, concurrency, GC optimization, network I/O) in large-scale Java or Go applications.
• Leadership in the Tech Community: A track record of contributing to open-source projects, technical publications, or speaking at industry conferences. Keeping on top of emerging trends and sharing knowledge both inside and outside the organization.
• Education: Bachelor’s degree in Computer Science, Engineering, or related field (Master’s or Ph.D. a plus), with strong foundations in algorithms and data structures.

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 

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 

We’re seeking a Senior Application Security Engineer to help strengthen Zeta’s application and platform security posture. You’ll play a critical role in embedding security throughout the software development lifecycle, ensuring our systems, applications, and AI-driven platforms are built securely from the ground up.

Zeta operates at massive scale, powering billions of consumer profiles and petabytes of data across real-time, AI-powered marketing platforms. In this role, you’ll collaborate with engineering and product teams to identify risks, implement secure design principles, and build automated controls that enable secure innovation.

This position offers significant technical scope, cross-functional visibility, and opportunities to contribute directly to the company’s overall security maturity.

Key Responsibilities:

Threat Modeling & Security Validation

• Conduct threat modeling and security reviews for distributed cloud-native systems.
• Perform security code reviews, static/dynamic analysis (SAST/DAST), and dependency scanning.
• Participate in incident response exercises and red/blue team simulations.
• Assess third-party libraries, APIs, and vendor integrations for security compliance.

Embedding Security into the SDLC

• Partner with developers and QA engineers to embed security testing into CI/CD pipelines.
• Review architecture and design documents to identify and mitigate risks early.
• Contribute to security automation initiatives and tooling to improve developer velocity.
• Support security checkpoints in release and deployment processes.

Emerging Threat Monitoring & Proactive Defense

• Stay current on evolving security risks, frameworks, and attack vectors, including AI/ML-specific threats (e.g., prompt injection, model poisoning).
• Assist in designing and deploying proactive defense mechanisms across applications and data platforms.
• Support investigations and post-incident reviews to strengthen detection and prevention capabilities.

Security Awareness & Policy Implementation

• Advocate secure coding and best practices through code reviews, workshops, and documentation.
• Contribute to internal security standards and playbooks.
• Collaborate closely with Engineering, DevOps, and Product teams to foster a security-first culture.

What You Need to Succeed

• Bachelor’s degree in computer science, Cybersecurity, or related field, or equivalent experience.
• 2 - 4 years of experience in Application Security, DevSecOps, or Secure Software Development.
• Strong understanding of OWASP Top 10, SANS CWE Top 25, and general application threat modeling.
• Experience with frameworks and architectures such as React, Node.js, Django, or FastAPI.
• Knowledge of securing APIs, microservices, and authentication mechanisms (OAuth2, OIDC, JWT).
• Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• Working knowledge of security testing tools (e.g., Semgrep, SonarQube, Burp Suite, Zap, Trivy).
• Solid collaboration and communication skills with cross-functional teams.

Nice to Have

• Familiarity with AI/ML security concepts such as data poisoning, adversarial testing, and model integrity.
• Experience with automation frameworks and scripting for security testing.
• Relevant certifications (e.g., OSCP, GWAPT, CSSLP, or ML/AI-specific security certifications)

WHO WE ARE

Zeta Global is a NYSE listed data-powered marketing technology company with a heritage of innovation and industry leadership. Founded in 2007 by entrepreneur David A. Steinberg and John Sculley, former CEO of Apple Inc and Pepsi-Cola, the Company combines the industry’s 3rd largest proprietary data set (2.4B+ identities) with Artificial Intelligence to unlock consumer intent, personalize experiences and help our clients drive business growth.

Our technology runs on the Zeta Marketing Platform, which powers ‘end to end’ marketing programs for some of the world’s leading brands. With expertise encompassing all digital marketing channels – Email, Display, Social, Search and Mobile – Zeta orchestrates acquisition and engagement programs that deliver results that are scalable, repeatable and sustainable.

Zeta Global is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, gender, ancestry, color, religion, sex, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.

ZETA IN THE NEWS!

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

Greetings From Zeta Global !!

Requirements:

• Education:
• B.S. or M.S. in Computer Science or a related field.

• Experience:
• 8+ years of experience with UI Automation tools such as Selenium, and API automation works.
• 5+ years of experience working with Python and/or J2EE technology or equivalent OO paradigm.
• Experience with automating test validation either via API or through databases using Snowflake, HIVE, or AWS Athena is highly desirable.
• Web application testing experience required both in frontend and backend validations.
• Experience working in a fast-paced technology environment.

• Technical Skills:
• Knowledge and experience with Robot Framework and its libraries using Python.
• Strong proficiency in Python programming.
• Knowledgeable in Git workflows like branching, merging, and conflict resolution.
• Solid understanding of SDLC and Agile testing methodologies.
• Experience with Atlassian tools such as Jira and Confluence preferred.
• Knowledge and experience with Kafka, Elasticsearch, and SQL/NoSQL databases such as Aerospike, Thrift, CI, and AWS is highly desirable.
• Knowledge of other test automation frameworks such as Selenium, Appium, or Cucumber is a plus.
• Experience working with container-based solutions is a plus.

• Soft Skills:
• Strong communication and interpersonal skills.
• Excellent problem-solving, critical thinking, and analytical skills.
• Ability and desire to learn new skills and take on new tasks.

Responsibilities:

• Testing and Automation:
• Perform automated tests covering both frontend/UI and backend/API tests, analyze results, and report defects.
• Continuously improve the test automation strategy to enhance test coverage and efficiency.
• Proactively involve in the development of automation frameworks to satisfy business requirements as well as improve the performance and usability of the framework.
• Automate tests to ensure functional requirements and performance KPIs are met.
• Ensure high product quality through rigorous functional and API level tests.

• Collaboration and Mentorship:
• Understand business requirements independently and cooperatively.
• Mentor and guide other QA engineers on best practices in test automation.
• Collaborate with cross-functional teams to integrate automated tests into the CI/CD pipeline.

• Development and Documentation:
• Architect, design, and implement a reliable and scalable automation framework for a real-world machine learning platform.
• Develop comprehensive test plans covering business use cases and test cases.
• Identify, record, document thoroughly, and track bugs.
• Perform thorough regression testing when bugs are resolved.

Company Summary

 Zeta Global is a NYSE listed data-powered marketing technology company with a heritage of innovation and industry leadership. Founded in 2007 by entrepreneur David A. Steinberg and John Sculley, former CEO of Apple Inc and Pepsi-Cola, the Company combines the industry’s 3rd largest proprietary data set (2.4B+ identities) with Artificial Intelligence to unlock consumer intent, personalize experiences and help our clients drive business growth.

Our technology runs on the Zeta Marketing Platform, which powers ‘end to end’ marketing programs for some of the world’s leading brands. With expertise encompassing all digital marketing channels – Email, Display, Social, Search and Mobile – Zeta orchestrates acquisition and engagement programs that deliver results that are scalable, repeatable and sustainable.

Zeta Global is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, gender, ancestry, color, religion, sex, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.

Zeta Global Recognized in Enterprise Marketing Software and Cross-Channel Campaign Management Reports by Independent Research Firm

https://www.forbes.com/sites/shelleykohan/2024/06/19/amazon-partners-with-zeta-global-to-deliver-gen-ai-marketing-automation/

https://www.cnbc.com/video/2024/05/06/zeta-global-ceo-david-steinberg-talks-ai-in-focus-at-milken-conference.html

https://www.businesswire.com/news/home/20240904622808/en/Zeta-Increases-3Q%E2%80%9924-Guidance

https://www.prnewswire.com/news-releases/zeta-global-opens-ai--data-labs-in-san-francisco-and-nyc-300945353.html

https://www.prnewswire.com/news-releases/zeta-global-recognized-in-enterprise-marketing-software-and-cross-channel-campaign-management-reports-by-independent-research-firm-300938241.html

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

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 integrity of that system is not a feature. It is the foundation.

Open Problem
The fraud gets smarter every quarter. The models have to keep up.

Integrity isn't about whether you use AI or not; it's about whether you are following the rules. Our integrity system is a portfolio of signals spanning vision, code analysis, browser telemetry, and behavioral sequences. Each signal is independently trained, operates on a different modality, and has its own precision-recall tradeoff and failure distribution. That heterogeneity is not a design choice we made lightly. It reflects the fact that no single modality is sufficient, and that the most informative signal depends heavily on context. A model at 92% precision on today's proxy attempt patterns can sit at 74% within two quarters, not because the model degraded, but because the attack surface shifted and the training distribution did not.

The fusion problem is where current approaches hit a ceiling. Naive aggregation across signals does not work because the signals are not independent and their reliability varies with context. What is needed is calibrated uncertainty at the signal level, a principled way to weight evidence depending on conditions, and the ability to detect when a signal has drifted out of its reliable operating range. The field has good solutions for static multimodal fusion. It does not have good solutions for adversarially non-stationary multimodal fusion where the ground truth labels are expensive, delayed, and partially unobservable.

Latency adds a constraint that rules out many otherwise viable architectures. Inference runs during a live assessment, which bounds what is deployable regardless of accuracy. That means the model quality problem and the systems problem have to be solved together, not sequentially. And the system has to generalize across populations and environments it was not trained on, without encoding the kinds of demographic biases that make a technically accurate classifier practically indefensible.

The honest summary: the current generation of integrity tooling, ours and the market's, has a precision ceiling that the next wave of fraud techniques will break through. Raising that ceiling requires building past what exists, not fine-tuning it.

What you'll do

• Standardize how model quality is defined, measured, and reported across all integrity signals. Build the evaluation infrastructure, golden datasets, and benchmarking pipelines that give us and our customers genuine confidence in what we ship
• Own the performance improvement strategy for each signal. Explore newer architectures, emerging research, and different training paradigms. The approach will not be one-size-fits-all; it will be grounded in each signal's maturity, data quality, and what the science actually supports
• Define the ML strategy for new signals from scratch: audio analysis, gaze tracking, behavioral anomalies. Set the architecture, data requirements, and a clear bar for what production-ready looks like before anything ships
• Continuously monitor how assessment fraud tooling is evolving. Evaluate new models as they emerge. Know when to abandon a strategy that is no longer moving the needle
• Systematically surface edge cases, build training data around them, and turn every customer-reported failure into a model that is harder to fool
• Drive strategy-level decisions: which new signals to build, whether to use models at all, and what the evidence says

Who you are

• You have shipped ML systems in production that real users and real businesses depend on
• You have deep intuition for where precision leaks happen and how to find them systematically, not by luck
• You think in systems. A signal's accuracy number, its data pipeline, its serving infrastructure, and its customer-facing outcome are one problem to you
• You care as much about evaluation methodology as model performance. You know that a metric measured wrong is worse than no metric
• You are genuinely curious about adversarial dynamics. The fact that your model will be attacked is interesting to you, not exhausting

Even better if you have

• Experience with multimodal systems in production: vision, audio, or behavioral signal pipelines
• Background in adversarial ML or fraud/anomaly detection
• Publications or open-source work in detection, robustness, or model evaluation
• Prior experience defining what production-ready means for a new signal category from scratch

You will thrive in this role if

• You find the performance improvement  problem as interesting as the model problem. 
• You are energized by adversarial environments where the threat landscape shifts under your feet and the only valid response is to stay ahead of it. 
• You do not inherit clean problems and optimize within them. 
• You define what the problem even is, and you hold yourself to a higher bar than the one the market has set.

About the role

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

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

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

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

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

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

What you will do

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

Who you are

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

Even better if you have

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

You will thrive here if

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

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

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

Bready* to make a change?

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

About this Roll*:

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

Do you have the right ingredients*?

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

Bonus Ingredients (The "Staff" Edge)

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

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

AI at Toast

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

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

The Challenge 

We are looking for a Senior level SDET to support our product development teams. As the Principal SDET, you will play a crucial role in shaping and leading our software testing strategy. You will be responsible for designing, developing, and implementing robust test automation frameworks, mentoring a team of SDETs (Software Development Engineer in Test), and ensuring the overall quality and reliability of our software products. 

Your Mission 

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 Title: Associate Software Engineer, AI
Location: Bangalore
Reports to: Sr. Manager, AI/ML

A quick snapshot…

As an Associate Software Engineer, you’ll be working on developing robust solutions across next-generation AI/GenAI based products and solutions. As a critical member of our team, you will play a pivotal role in enhancing our design, development, and continued enhancement of our features along with writing unit & integration tests to ensure features never break.

Why it’s a big deal…

This is one of the critical roles under the AI team within Engineering. You will possess deep technical expertise as a AI engineer and a strong commitment to participate in the entire AI development lifecycle, including data collection, preprocessing, model training, evaluation, and deployment. This role works on multiple technologies and databases to make sure the product development moves towards rapid development, rich controls, more scalable, and better security.

Are you the person we’re looking for?

Related Experience. You should have at least 6 Months of experience in the software industry as a AI Engineer and the technical requirements necessary to design, develop, test and implement solutions.

Technical Skills. You’re likely to have proficiency in AI development technologies such as Python, FastAPI, PyTest, Celery and other Python frameworks and familiarity with AI/ML, GenAI, and MLOps concepts.  You also possess good understanding with object-oriented programming, concurrency, design patterns, and REST APIs. Your familiarity with CI/CD tooling such as Terraform and GitHub Actions and frameworks like LangChain, LangGraph, and databases like SQL and NoSQL such as MongoDB, MSSQL, or Postgres. Understanding of Data Structure & Algorithm analysis and its usage in scalable software design.

Strong communication and interpersonal skills. You’re not just comfortable engaging in collaborative discussions, but initiating them, too. You are skilled at reading and adapting to different communication styles. When you speak you are clear and concise. Your strong listening skills foster connections with our clients and allow you to accurately collect the right information so you can resolve issues most expediently.

Education. A bachelor’s degree in engineering or equivalent.

Here’s what will give you an edge…

Initiative. You don’t wait around for things to happen or for your manager to tell you what to do. You’re not only proactive about completing your work, but when you sense the need to introduce a project that will benefit the team or the organization -- even if it’s outside your scope of work -- you put a proposal together, talk to the team about it, and own it. And that also goes back to having an entrepreneurial spirit.

Strong troubleshooting skills and logic based thinking is your forte. This is an absolute must. Your proven ability to analyze and apply logical thinking to determine the root cause of an issue is fundamental to success in this role.

Clear, deliberate, and collaborative communicator. You don’t just engage in collaborative discussions, you initiate them regularly. You are clear and concise when you speak and write -- and even creative in terms of ensuring your messages are received and understood. You leave no room for assumptions or misunderstanding. It’s what sets you apart from the rest.

Exposure to mature SDLC practices. Understanding of Agile methodologies. Experience with unit testing, code coverage, and security scan tools. Proficient in working with source control tools like GitHub/Bitbucket.

#LI-RT1

About the Role

🤖 Power Groupon’s Next Chapter with AI-Driven Innovation

Are you a hands-on technical leader ready to shape the next generation of B2B platforms? Join Groupon at a pivotal moment as we transform our business with an aggressive AI-first strategy and modern technology stack. As our new Backend  Engineer for Deal Management, you will drive the architecture, development, and impact of systems that empower local businesses worldwide—right from the ground up.

Key Responsibilities:

• Deliver complex technical initiatives independently within high-availability, mission-critical systems.
• Lead technical reviews and contribute to architectural decisions, specifically driving TypeScript/Node.js migrations.
• Champion AI-assisted development by using tools like Cursor and Claude hands-on; mentor teammates on effective practices and prompt engineering.
• Communicate technical trade-offs clearly to both technical and non-technical stakeholders to ensure alignment on roadmap priorities.
• Own operational excellence by maintaining and improving SLOs, observability, and comprehensive documentation for your areas of ownership.

Key Requirements:

• 6+ years of software engineering experience with deep proficiency in production-grade TypeScript, Node.js
• Distributed systems expertise in high-traffic environments, including API design, monitoring, and advanced debugging.
• AI-Native workflow: Hands-on experience integrating AI coding tools (e.g., Cursor, Claude) into your daily development cycle.
• Strong communication skills and a proven ability to drive cross-functional collaboration.
• Set engineering quality bars by driving best practices around code reviews, testing strategy, security, and performance, ensuring long-term maintainability and scalability of the platform.

Nice to Have:

• Experience scaling E-commerce or marketplace platforms.
• A background in Java to support modernization and refactoring projects will be considered.
• Open source contributions or practical experience with AI/ML integration.
• Experience owning systems end-to-end, including design, development, rollout, and post-production support in fast-moving environments.
• Strong fundamentals in data modeling, system performance optimization, and resilience patterns.
• Prior experience influencing technical direction beyond your immediate team (RFCs, design docs, tech talks, or migration leadership).

What Success Looks Like:

• Independence: Delivering high-quality, well-tested features with minimal guidance.
• Architectural Impact: Active participation in design reviews that tangibly improve team-wide technical solutions.
• Mentorship: Effective coaching of junior engineers with a measurable impact on their technical growth.
• Risk Management: Maintaining clear documentation and proactively identifying risks before they impact the platform.

We Are Interested In:

Engineers who take full technical ownership, embrace AI tooling in their daily work, and deliver reliable systems while growing their impact across the team. We seek a candidate who can balance high-stakes stability with the speed of modern transformation.

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/ML Ops 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:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

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/ML Ops 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:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective.

You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. 

You Will:

Model and Pipeline Automation 

• Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. 
• Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models.
• Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models.

Governance & Compliance

• Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards.

Performance Monitoring

• Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. 
• Incorporate user feedback for iterative improvements and manage necessary model retraining cycles.

Cross-Functional Collaboration

• Act as the "glue" between Data Scientists (who build models) and Software Engineers (who consume them).
• Partner effectively with software engineers, product managers and business functions to integrate the machine learning solutions across smartsheet.

Architecture and Infrastructure Management

• Provision and manage scalable cloud infrastructure using Infrastructure as Code (IaC).
• Provide architectural guidance and mentorship to a team consisting of ML engineers, data scientists and analytics engineers.
• Distill complex ML concepts into easy-to-follow technical documentation.

You Have:

• 5+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines. 
• 7+ years of programming experience in languages used in AI/ML (eg python, scala etc)
• 4+ years of experience in developing deep learning and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc.
• Strong applied data science skills - ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms. 
• Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs).
• Experience developing, documenting, and supporting REST APIs
• A degree in Computer Science, Engineering, or a related field or equivalent practical experience.

As a global leader in Collaborative Work Management and with a market cap of $10bn we’ve experienced incredible growth in EMEA, expanding from 1 team and 3 engineers in 2018 to 9 teams with over 70 engineers in 2024. As we expand into India and build out a new operation, we're searching for a talented and motivated Principal Analytics Engineer (Data Architect) to serve as a thought leader in our data-driven decision-making. You will be responsible for the end-to-end system design and architecture of our business critical analytical systems (DWs). This role will be responsible for the design and development of a governed, reliable, and scalable analytics ecosystem, transforming raw data into high-value, performant data products for DS/ML, analytics, and reporting.

A key aspect of this role is providing thought leadership and architecting efficient, large-scale data transformation systems within Snowflake. You will have demonstrated experience architecting data solutions for SaaS companies, specifically within the Go-To-Market (GTM), Marketing, Customer Experience, and Financial business domains. Working as a strategic advisor to BI analysts, Data Scientists, and business leadership, you will drive the organization's data strategy, ensure data accessibility, and foster data democratization across the enterprise.

This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India.

You Will:

• Lead the end-to-end system design and architecture for large, complex analytics systems, optimizing data transformations from our data lake in Snowflake into analytical data products (DWs).
• Define and drive the adoption of design standards, architectural principles, and data modeling methodologies (including Data Vault (DV 2.0) and dimensional modeling) across the organization.
• Propose and drive strategic initiatives and coordinate the technical roadmap for analytical systems across the engineering organization partnering closely with the Big Data Platforms (BDP) team.
• Serve as the data architect for critical SaaS business domains, including Go-To-Market, Marketing, Customer Experience, and Finance, translating ambiguous business problems into scalable technical analytical solutions.
• Develop and implement the organization's data strategy for data quality, observability, and testing, raising the bar for engineering quality.
• Architect and guide teams to build and maintain a governed, robust, reliable, and scalable analytics system leveraging Gen AI capabilities including AI-assisted code development practices.
• Act as a trusted advisor to BI analysts, data scientists, and business leaders, educating and advising leadership on technical data topics and data accessibility strategies.
• Foster data democratization via activation of data on critical platforms like Smartsheet Platform, Amplitude, ThoughtSpot, Gainsight & Salesforce.
• Actively mentor analytics engineers and provide mentorship across disciplines, leading forums such as guilds, design reviews, and engineering forums.
• Collaborate with cross-functional teams to assess data privacy needs and define data masking strategies aligned with industry compliance standards (e.g., GDPR, HIPAA, CCPA).

You Have:

• 12+ years of experience in advanced data modeling, data architecture, and data warehousing. This role is expected to do development activities in combination of the data architecture scope, so hands-on experience is necessary.
• Deep expertise and 10+ years of hands-on experience with Data Vault (DV 2.0) and Dimensional Modeling.
• Expert-level knowledge of modern data stacks, including Snowflake, dbt, and data orchestration tools (e.g., Airflow, GitLab pipelines).
• Proven experience architecting and building analytical products for SaaS companies in GTM, Marketing, Customer Experience, and Financial data domains.
• Comprehensive understanding of data topologies (e.g., data mesh, hub/spoke) and data modeling methodologies (e.g., Data Vault, Kimball, Inmon).
• Demonstrated ability to drive clarity in ambiguous environments where the strategy may not be defined.
• Proven experience with building and maintaining business analytics layers and semantic layers to enable self-service for non-technical end-users.
• Strong production experience supporting and maintaining analytics/data warehouse solutions with mission-critical datasets.
• Exceptional communication skills, with experience educating and advising senior leadership and mentoring teams across disciplines.
• Strong knowledge of data governance principles, CI/CD practices (e.g., GitLab), self-serve analytics tools (e.g., Amplitude, ThoughtSpot), and cloud architectures (AWS preferred).

Smartsheet is hiring a Senior Analytics Engineer to lead the way in data-driven decision-making. You will be responsible for the creation and maintenance of a governed, reliable, and scalable analytics system, transforming raw data into usable datasets for DS/ML, analytics, and reporting. 

A key aspect of this role is leading the architecture and implementation of efficient data transformation systems within Snowflake, fostering data democratization and impacting business outcomes. Working closely with BI analysts and Data scientists, you will ensure data accessibility and drive activation on critical customer-facing platforms.

This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India.

You Will:

• Leading the implementation of efficient and scalable systems that optimize data transformations from our data lake in Snowflake into clean, documented data products. 
• Contribute to the design standards and architectural principle standards, designs and processes.
• Build and maintain a governed, robust, reliable, and scalable analytics system (DW/DV).
• Collaborating with BI analysts and data scientists to provide proper data accessibility guidelines.
• Foster data democratization via activation of data on critical platforms like Smartsheet platform, Amplitude, Thoughtspot , Gainsight.
• Create and contribute to frameworks that improve data quality and observability to identify and resolve issues faster.
• Create and implement data testing plans, encompassing data validation, data quality assessment, and regression testing, to identify anomalies, inconsistencies, or errors in produced datasets.
• Mentor and guide teams and help drive high standards across the team by conducting design reviews and engineering ideation forums.
• Collaborate with cross-functional teams to assess data privacy needs and define data masking strategies aligned with industry compliance standards (e.g., GDPR, HIPAA, CCPA).

You Have:

• 6+ years of experience in advanced data modeling using Data Vault (DV 2.0), dbt, and Snowflake.
• Proven experience in building analytics systems with data transformation, dependency, and workload management (Data Vault, AutomateDV, dbt core, Airflow, Snowflake, GitLab, SQL).
• Proven experience with building and maintaining business analytics layers and semantic layers to enable self-service for non-technical end-users.
• Strong production experience supporting and maintaining analytics/data warehouse solutions with mission-critical datasets.
• Familiarity with data governance principles for maintaining datasets to enable a single source of truth.
• Familiarity with self-serve product analytics tools (Amplitude, Thoughtspot, Tableau, Gainsight, etc.).
• Knowledge of code management and CI/CD practices (GitLab, Airflow, Snowflake, Terraform).
• Familiarity with AWS solutions such as S3, EC2, VPC.

Smartsheet is looking for an experienced Data Engineer to support and accelerate the productivity of our Go-To Market organization. In this role, you will work with Data Engineers to help build scalable and reliable data and reporting infrastructure. You will partner with Analytics decision-makers as part of a collaborative, motivated team. Your work will be instrumental in helping our Sales partners optimize their pipeline, increase retention, and close deals.

Our ideal candidate is curious and displays an ability to translate abstract data requests into actionable data solutions . To be successful in this role, you are able to communicate to a diverse audience of internal stakeholders. You should have strong technical acumen with data analytics tools and languages, the ability to identify areas of opportunity within the business, and build innovative solutions.

You Will:

• Help to create, evolve, and maintain the reporting infrastructure for the Sales organization to facilitate data across the organization
• Partner with engineering, data science, and other analytics teams to build scalable analytics solutions with a focus on reporting capabilities
• Mine large datasets to ensure data accuracy and completeness for reporting purposes   
• Analyze and monitor data for anomalies, with a focus on data quality and consistency within reports     
• Develop and maintain key performance indicators (KPIs) to track sales performance, pipeline health, and other critical metrics   
• Automate report generation and distribution to improve efficiency
• Provide technical expertise and guidance to junior analysts on data extraction, transformation, and loading (ETL) processes and reporting best practices
• Ensure data governance and data integrity across all reporting tools and platforms
• Proactively identify and propose improvements to existing reporting processes and systems
• Be a mentor and leader to the more junior analysts on the team
• Perform other duties as assigned

You Have:

• Bachelor's degree in a quantitative field (e.g. engineering, sciences, math, statistics, business, or economics)
• 5+ years of experience in an analytics/engineering role with increasing responsibility
• Experience in Cloud and SaaS go-to-market (GTM)
• Expertise in SQL and preparing data for analysis, modeling, and visualization
• 3+ years of experience using Python for data analysis / automation 
• 3+ years of experience with dbt core
• 3+ years of experience with Git (Gitlab, Github etc.) and CI/CD concepts like branching, merging, Code Reviews etc. 
• Demonstrated experience with a modern engineering tech stack (Airflow, AWS, Docker etc.) 
• Experience working with a business intelligence tool like Tableau, PowerBI, Looker, etc.

Nice To Have:

• Experience building ML models
• Proficiency with Tableau preferred
• Experience with statistics (time series analysis, cluster analysis, multivariate analysis)
• Experience publishing and presenting data and findings to executives and non-data users

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 Principal Data & AI/ML Ops 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:

• Data Architecture and Design: Designing and overseeing the architecture of scalable and reliable data platforms, including data pipelines, storage solutions, and processing systems
• Data Modelling and Management:Developing and implementing data models, ensuring data quality, and establishing data governance policies
• Data Pipeline Development: Building and optimising data pipelines for ingesting, processing, and transforming large datasets from various sources
• Performance Optimisation: Identifying and resolving performance bottlenecks in data pipelines and systems, ensuring efficient data retrieval and processing
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Data Security and Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining data platform systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design involving large Petabytes of data with Databricks Lakehouse
• Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context)
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python, SQL, and potentially Java or Scala
• Exposure to Snowflake and Data pipeline frameworks like Airbyte/Airflow is preferable
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Driving engineering excellence initiatives
• Legally eligible to work in India on an ongoing basis

About the Role:

Production Engineer
The Production Engineer at Rubrik plays a critical role in operational excellence, managing alerts, responding to outages, and leading incident resolution as an Incident Manager. This role requires hands-on experience in maintaining highly available critical services across multi-cloud environments while driving continuous improvements through automation and intelligent monitoring.

What you’ll do:

• Join a 24/7 Production Operations team responsible for managing and supporting critical infrastructure and services in multi-cloud environments.
• Oversee staging and production environments to ensure maximum uptime and reliability.
• Implement and maintain comprehensive observability solutions for real-time monitoring, alerting, and metrics collection.
• Lead incident management efforts by swiftly responding to alerts and outages, coordinating teams to drive timely resolution.
• Analyze recurring incidents to identify root causes, reduce toil, and improve system resilience.
• Design and develop automation tools to proactively detect, triage, and remediate production issues.
• Maintain and update runbooks to support incident response and recurring issues.
• Demonstrate strong decision-making skills under pressure, effectively managing critical situations with urgency and composure.

Experience you’ll need:

• Solid understanding of distributed system concepts.
• Practical experience working with production systems and environments, preferably within public cloud infrastructures.
• Familiarity with container orchestration platforms, especially Kubernetes.
• Hands-on experience with infrastructure  management tools like CloudFormation and Terraform.
• Strong analytical and problem-solving skills  for diagnosing and resolving system and application issues.
• Proficient in data structures and algorithms, UNIX, networking, operating systems, and database systems such as MySQL.
• Proficient with Python programming skills.
• Excellent verbal and written communication skills.

Location: Bangalore, India
Work Shift: Rotation (24/7 coverage expected) 

ABOUT RUBRIK

Join Us in Securing the World's Data

Rubrik (NYSE: RBRK) is on a mission to secure the world’s data. With Zero Trust Data Security™, we help organizations achieve business resilience against cyberattacks, malicious insiders, and operational disruptions. Rubrik Security Cloud, powered by machine learning, secures data across enterprise, cloud, and SaaS applications. We help organizations uphold data integrity, deliver data availability that withstands adverse conditions, continuously monitor data risks and threats, and restore businesses with their data when infrastructure is attacked.

Rubrik provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Rubrik complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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.

As a Software Development in Test Engineer, you will be tasked with full responsibility for the design, implementation, and maintenance of Automated tests using object-oriented frameworks and AI. We're looking for a new team member who is versatile and knows exactly how to improve processes and make them more efficient to make sure we have a winning product. The ideal candidate has a strong technical background in software automation development, sees the big picture and has the “can do” attitude.

What Will You Do?

Primary responsibilities include:

• Design, develop (Python//TypeScript) and implement automation tests in all components of SentinelOne products with main focus on our SAAS platform and its EndPoint Protection services
• Testing the quality of SentinelOne EPP/EDR solutions
• Triage and automate the triaging of test execution results
• Ensure coverage on critical components and close any test gaps that have been identified
• Work closely with other automation engineers, developers and product managers to ensure high quality products

What Skills and Knowledge Will You Bring?

Ideal candidates will have:

• Proven experience in automation development testing multi-layered products 
• Previous experience in testing SAAS products (cloud based) 
• Experience with Python using Pytest framework
• Experience with Dockers
• Ability to reproduce issues and work closely with development to resolve them
• Debugging skills and ability to investigate and triage difficult problems
• Experience in SW validation methodologies and concepts, testing and integration
• Strong self-management capabilities: proactive, initiative, self-learner, team player

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Flexible working hours and hybrid/remote work model.
• Flexible Time Off.
• Flexible Paid Sick Days.
• Global gender-neutral Parental Leave (16 weeks, beyond the leave provided by the local laws) 
• Generous employee stock plan in the form of RSUs (restricted stock units)
• On top of RSUs, you can benefit from our attractive ESPP (employee stock purchase plan)
• Gym membership/sports gears by Cultfit.
• Wellness Coach app, with 3,000+ on-demand sessions, daily interactive classes, audiobooks, and unlimited private coaching. 
• Private medical insurance plan for you and your family.
• Life Insurance covered by S1 (for employees)
• Telemedical app consultation (Practo)
• Global Employee Assistance Program (confidential counseling related to both personal and work life matters)
• High-end MacBook or Windows laptop.
• Home-office-setup allowances (one time) and maintenance allowance. 
• Internet allowances.
• Provident Fund and Gratuity (as per govt clause)
• NPS contribution (Employee contribution)
• Half yearly bonus program depending on the individual and company performance.
• Above standard referral bonus as per policy.

As a Senior Software Development in Test Engineer, you will be tasked with full responsibility for the design, implementation, and maintenance of Automated tests using object-oriented frameworks and AI. We're looking for a new team member who is versatile and knows exactly how to improve processes and make them more efficient to make sure we have a winning product. The ideal candidate has a strong technical background in software automation development, sees the big picture and has the “can do” attitude. Primary responsibilities include:

What Will You Do?

Primary responsibilities include:

• Design, develop (Python//TypeScript) and implement automation tests in all components of SentinelOne products with main focus on our SAAS platform and its EndPoint Protection services
• Testing the quality of SentinelOne EPP/EDR solutions
• Triage and automate the triaging of test execution results
• Ensure coverage on critical components and close any test gaps that have been identified
• Work closely with other automation engineers, developers and product managers to ensure high quality products

What Skills and Knowledge Will You Bring?

Ideal candidates will have:

• Proven experience in automation development testing multi-layered products 
• Previous experience in testing SAAS products (cloud based) 
• Experience with Python using Pytest framework
• Experience with Dockers
• Ability to reproduce issues and work closely with development to resolve them
• Debugging skills and ability to investigate and triage difficult problems
• Experience in SW validation methodologies and concepts, testing and integration
• Strong self-management capabilities: proactive, initiative, self-learner, team player

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Flexible working hours and hybrid/remote work model.
• Flexible Time Off.
• Flexible Paid Sick Days.
• Global gender-neutral Parental Leave (16 weeks, beyond the leave provided by the local laws) 
• Generous employee stock plan in the form of RSUs (restricted stock units)
• On top of RSUs, you can benefit from our attractive ESPP (employee stock purchase plan)
• Gym membership/sports gears by Cultfit.
• Wellness Coach app, with 3,000+ on-demand sessions, daily interactive classes, audiobooks, and unlimited private coaching. 
• Private medical insurance plan for you and your family.
• Life Insurance covered by S1 (for employees)
• Telemedical app consultation (Practo)
• Global Employee Assistance Program (confidential counseling related to both personal and work life matters)
• High-end MacBook or Windows laptop.
• Home-office-setup allowances (one time) and maintenance allowance. 
• Internet allowances.
• Provident Fund and Gratuity (as per govt clause)
• NPS contribution (Employee contribution)
• Half yearly bonus program depending on the individual and company performance.
• Above standard referral bonus as per policy.

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. 

About the Opportunity

User Store is the foundational intelligence platform of InMobi Group. The Senior PM in this role will define its long-term strategy, shape how user signals are transformed into AI-ready intelligence, and directly influence how InMobi empowers its partners globally.

At its core, this role is about turning scale into intelligence. InMobi processes billions of real-time signals daily — affinity, context, cross-platform behaviour, and more — and the Senior PM for User Store will own the strategy for converting that raw signal into structured, ML-ready user intelligence that is actionable for advertisers at every stage of the funnel. The PM in this role will have end-to-end ownership of a platform that has direct, measurable impact on group revenue.

The Charter

The Senior PM will define and own the strategy for building a unified, enriched, integrated user intelligence layer that drives the roadmap for how raw user signals are structured, enriched, and made consumable by ML & AI systems and advertiser products at scale. This also includes owning the product vision for how internal teams and external advertisers access and act on that intelligence, working closely with ML and engineering to ensure the platform is aligned with real advertiser needs. Central to this role is a single-minded focus on KPI delivery — measuring success through the quality and revenue impact of audiences and intelligence features generated from the user intelligence layer.

The Senior PM needs to understand how to generate and use high-quality user embeddings and latent space representations that are directly consumable by ML models and downstream advertisers. He/ she will work closely with data science and engineering to ensure the enrichment pipeline is production-grade, privacy-compliant, and built for scale.

What You Will Own

• The multi-year product strategy for the Central User Intelligence Spine across InMobi Group.
• The data enrichment and embedding generation roadmap — from raw signals to ML-consumable intelligence.
• Adoption of User Store across internal InMobi products and external advertiser and publisher integrations.
• Strategic data partnerships and sourcing relationships that expand the signal universe.
• Client-facing presence — representing User Store capabilities in advertiser and DSP conversations independently.
• The AI-native user studio product — vision, roadmap, and go-to-market with internal and external stakeholders.

What We Are Looking For

We are looking for a rare profile: someone with the PM craft to drive strategy and adoption, the data intuition of a seasoned practitioner, and the AI fluency to have a genuine opinion on how embeddings are built and consumed — not just talk about them.

Non-Negotiables

• AI-native mindset — Deep familiarity with how AI and ML systems are actually built. You understand how embeddings are generated, what they represent, and how downstream systems consume them. This role will not be a good fit without this foundation.
• End-to-end ownership — You drive things to completion. You are rigorous, deeply accountable, and do not let initiatives stall between strategy and execution.
• Impact-first prioritisation — You have a strong instinct for what moves the needle and the discipline to say no to everything else.
• Engineer or data scientist at heart — You think in systems and are comfortable going deep in technical discussions. A formal background in engineering or data science is not mandatory but is a strong bonus.
• [Bonus Points] Data platform experience — You have built or owned intelligence stores, data pipelines, or recommendation systems at scale. You think in terms of exposing intelligence, not raw data.

Strong Differentiators

• Experience encoding user behaviour into structured, learnable representations for ML systems — embeddings, vector spaces, affinity graphs, or adaptive learning systems.
• Background in CDP (Customer Data Platforms), user store systems, or large-scale data infrastructure products.
• Familiarity with privacy-preserving architectures: clean rooms, differential privacy, or data governance in regulated environments.
• Experience with recommendation systems — understanding what users like and dislike and translating that into product decisions.
• Comfortable with hands-on data deep-dives: able to look at data cuts quickly, visualise hypotheses, and challenge assumptions in technical discussions.
• Prior experience in ad tech, DSP, or publisher ecosystems is a plus, though not a requirement — strong candidates from adjacent industries such as recommendation systems, data platforms, or consumer tech are encouraged to apply.

Core PM Fundamentals

• 5+ years of product management experience with a track record of shipping complex, cross-functional products.
• Ability to translate ambiguous, long-horizon strategy into a clear roadmap with measurable milestones.
• Strong cross-functional leadership — able to align data science, engineering, and commercial teams without direct authority.
• Executive-level communication: able to represent User Store in leadership reviews and client meetings independently.

Why This Role

• One of the most strategically significant product charters within InMobi Group — the intelligence layer that powers the broader platform.
• Direct, measurable impact on group revenue across the advertiser funnel.
• End-to-end ownership from data strategy to ML interfaces to advertiser-facing products — one of the broadest scope PM roles in the organisation.
• High visibility with InMobi Group leadership and external partners.
• An opportunity to work on problems that sit at the frontier of applied AI in mobile advertising.

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

Why you should join us?

At our core, we believe in the power of data to drive smarter decisions and transform operations. As an Operational Data Scientist, you'll be at the forefront of this mission—leading initiatives that streamline business processes, accelerate time to insight, and align analytics with strategic goals.

You'll work in an environment that values rigor in experimental design, seamless model integration, and impactful operational analytics. We’re not just looking for technical talent—we want a strategic thinker and a collaborative leader who thrives at the intersection of data, business, and execution.

If you're passionate about solving complex problems, influencing high-stakes decisions, and driving measurable outcomes, this is the opportunity to make your mark. Join us and be part of a team that turns data into action—and action into impact.

What will you be doing?

1. Experiment Design and Interpretation:

• Lead and design complex experiments, addressing challenges with statistical rigor.
• Interpret results and provide actionable insights to drive business decisions.

2. Data Engineering Workflow and Design:

• Partner with stakeholders to ensure data systems and structures are efficient and reliable.
• Reduce turnaround time (TAT) for analytics, feature exploration, and experimentation setup

3. Data Science Model Integration:

• Collaborate with data science teams to integrate models into workflows.
• Define success metrics, identify inefficiencies, and leverage model outputs to enhance operations.

4. Proactive and Reactive Analysis:

• Conduct exploratory data analysis, simulations, and hypothesis testing.
• Provide strategic support and actionable insights to address business challenges.

5. Health Metrics Design and Implementation:

• Define, implement, and monitor key performance metrics to assess platform performance and user behavior.

6. Leadership and Collaboration:

• Serve as a liaison between cross-functional teams, advocating for data-driven decisions.
• Mentor analysts and promote a culture of analytics within the organization.

7. Product Impact Tracking:

• Design and implement analyses to monitor product impact.
• Ensure alignment of analytics initiatives with broader business objectives.

What are we looking for?

Skills and Attributes:

• 8–15 years of total professional experience, preferably in Tech, Consulting, or high-scale Analytics organizations.
• 4+ years of people management experience, leading data science, analytics, or operational analytics teams in system-heavy environments.
• Advanced proficiency in SQL and Python — able to drive deep analyses, RCA investigations, and metric instrumentation independently.
• Hands-on experience with Spark or distributed data processing frameworks for scalable analysis.
• Proven ability to design and deploy control systems or feedback loops in collaboration with engineering teams to tune complex algorithms in production.
• Successfully implemented and maintained Data Science models in production, including monitoring and post-deployment tuning.
• Solid foundation in statistical methods, hypothesis testing, and experimental design, especially as applied to system performance and anomaly detection.
• Comfort working with observability and visualization tools — Tableau, Looker, Power BI, or internal metric dashboards like Grafana or Superset.
• Strong record of cross-functional collaboration with engineering, product, SRE, and ML teams to drive system health and platform improvements.
• Demonstrated ability to work through ambiguity, structure diagnostic approaches, and drive data-informed operational decisions.
• Strong strategic and systems thinking mindset — able to reason about interdependent metrics and optimize for system-wide health.

THE ROLE

We are seeking a highly skilled and hands-on Senior Finance Data & Analytics Engineer (IC role) to lead the design and development of the Finance Data Cube, enabling enterprise-wide insights into Customer Lifetime Value (CLTV), Contribution Margin, and other key financial metrics.

WHAT YOU'LL DO

• Design, build, and own the Finance Data Cube, integrating financial, customer, and operational datasets.
• Model data to support CLTV, Contribution Margin, and other profitability KPIs across multiple dimensions (customer, product, LOB, geography, etc.)
• Be a data architect for Finance , bring different data into cohesive and answer critical questions
• Leverage AI tools to automate data summarization, anomaly detection, and narrative insights for Finance stakeholders.
• Scale data infrastructure to support large volumes and complex financial models.
• Build and manage Semantic Layer models to standardize business metrics and enable self-serve analytics
• Translate complex financial concepts and KPIs into scalable, maintainable data models.
• Implement strong controls for data quality, lineage, and governance.
• Maintain clear documentation of data transformations, metric definitions, and AI model logic.
• We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

• Experience: 8+ years in Finance Data Engineering, FP&A Analytics, or Financial Systems, with exposure to AI/ML-based analytics(added advantage)
• Proficiency with Snowflake and modern data stacks with strong SQl and data modeling expertise 
• Deep understanding of finance data set , SAP , Contribution margin, CLTV would be an added advantage
• Experience with data orchestration tools (Airflow, dbt) and tableau platform
• Hands-on experience with Python, PySpark, or R for automation and model integration.
• Proven ability to translate financial logic into scalable data models.
• Experience in Cortex Analyst/Search components to enable AI/ML-driven insights, natural language querying, and intelligent data discovery is preferred. 
• Knowledge of predictive modeling, time-series forecasting, and generative AI in analytics.
• Ability to evaluate and apply AI responsibly in financial contexts.

 #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

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 Role:

Production Engineer
The Production Engineer at Rubrik plays a critical role in operational excellence, managing alerts, responding to outages, and leading incident resolution as an Incident Manager. This role requires hands-on experience in maintaining highly available critical services across multi-cloud environments while driving continuous improvements through automation and intelligent monitoring.

What you’ll do:

• Join a 24/7 Production Operations team responsible for managing and supporting critical infrastructure and services in multi-cloud environments.
• Oversee staging and production environments to ensure maximum uptime and reliability.
• Implement and maintain comprehensive observability solutions for real-time monitoring, alerting, and metrics collection.
• Lead incident management efforts by swiftly responding to alerts and outages, coordinating teams to drive timely resolution.
• Analyze recurring incidents to identify root causes, reduce toil, and improve system resilience.
• Design and develop automation tools to proactively detect, triage, and remediate production issues.
• Maintain and update runbooks to support incident response and recurring issues.
• Demonstrate strong decision-making skills under pressure, effectively managing critical situations with urgency and composure.

Experience you’ll need:

• Solid understanding of distributed system concepts.
• Practical experience working with production systems and environments, preferably within public cloud infrastructures.
• Familiarity with container orchestration platforms, especially Kubernetes.
• Hands-on experience with infrastructure  management tools like CloudFormation and Terraform.
• Strong analytical and problem-solving skills  for diagnosing and resolving system and application issues.
• Proficient in data structures and algorithms, UNIX, networking, operating systems, and database systems such as MySQL.
• Proficient with Python programming skills.
• Excellent verbal and written communication skills.

Location: Bangalore, India
Work Shift: Rotation (24/7 coverage expected) 

ABOUT RUBRIK

Join Us in Securing the World's Data

Rubrik (NYSE: RBRK) is on a mission to secure the world’s data. With Zero Trust Data Security™, we help organizations achieve business resilience against cyberattacks, malicious insiders, and operational disruptions. Rubrik Security Cloud, powered by machine learning, secures data across enterprise, cloud, and SaaS applications. We help organizations uphold data integrity, deliver data availability that withstands adverse conditions, continuously monitor data risks and threats, and restore businesses with their data when infrastructure is attacked.

Rubrik provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Rubrik complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.