Netomi

<div><strong>About the Company:</strong></div>
<div><span>Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. </span></div>
<div> </div>
<div><span>Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!</span></div><div><br /></div><div>Netomi is hiring a Senior Technical PM to own the product strategy and roadmap for our Agents platform. You will decide what we build and why, tie every investment to enterprise customer and business outcomes, and get capabilities shipped and adopted by some of the world’s largest brands.</div>
<div><br />This role is also firmly hands-on. You will work directly with AI labs, understand new model capabilities early, build experiments and prototypes yourself, design evaluations and debug failing agents. You use that hands-on work to make better, faster product decisions.</div>
<h2>Product and business ownership</h2><div>

<li><strong>Business focus:</strong> tie the roadmap to measurable business outcomes such as autonomous resolution rate, cost per resolution, CSAT, revenue expansion and competitive wins. Know where Netomi wins and loses against competitors, and shape our position.</li>
<li><strong>Product strategy and roadmap:</strong> own the multi-quarter roadmap for Agents end to end, from problem discovery and prioritization to delivery and outcome tracking. Make and defend hard trade-offs when priorities compete.</li>
<li><strong>Customer and partner needs:</strong> work directly with enterprise customers, Customer Success, Delivery and Sales to find the highest-value problems. Translate them into clear problem statements, PRDs, user stories, success metrics and dependency maps.</li>
<li><strong>Cross-functional leadership:</strong> drive alignment across engineering, research, data science, QA and go-to-market on scope, dependencies and launch readiness, without direct authority.</li>
<li><strong>Planning and execution:</strong> run the cadence of quarterly roadmap inputs, monthly scope lock, weekly execution reviews and launch readiness sign-offs.</li>
<li><strong>Launch and adoption:</strong> own launch checklists (instrumentation, enablement, success criteria), track adoption per capability and publish a monthly Agent Outcomes readout across deployments. </li>
<li><strong>Post-release learning:</strong> run monitoring windows and post-incident reviews, and feed what you learn back into the roadmap.</li>

</div>
<h2>Product areas you will own</h2><div>

<li><strong>Agent reasoning and orchestration:</strong> multi-step task planning, action selection, retry and fallback logic, and supervisor and sub-agent patterns.</li>
<li><strong>Tool and API use:</strong> reliable, observable, policy-compliant tool calling for CRM, ITSM and custom enterprise systems, including MCP.</li>
<li><strong>Memory and context:</strong> conversation memory, long-running task state and continuity across channels and sessions.</li>
<li><strong>Human-in-the-loop:</strong> clarification, graceful escalation to live agents, approval steps for high-risk actions and hybrid autonomy modes.</li>
<li><strong>Enterprise governance:</strong> guardrails, audit trails, explainable decisions, role-based access, and safe rollout through shadow mode, staged releases and rollback.</li>

</div>
<h2>Hands-on work</h2><div>

<li><strong>AI labs and new capabilities:</strong> be our product point person with AI labs and model providers. Test new models and features (reasoning, tool use, realtime voice, memory) on our use cases, decide what to build, change or skip, and give labs evidence-based feedback.</li>
<li><strong>Experiments and prototypes:</strong> vibe code prototypes, build agents, and connect them to real systems through APIs and MCP tools. Run offline tests, shadow mode and canary releases with clear decision criteria, and hand engineering a working reference, not just a document.</li>
<li><strong>Evaluation and quality:</strong> define the Agent Readiness Scorecard and Go/No-Go criteria. Design evals for task completion, tool success, policy compliance, latency and cost, and keep regression tests running on every model, prompt or tool change.</li>
<li><strong>Debugging production failures:</strong> read agent traces with engineering, find root causes (wrong action, missed escalation, bad tool call, memory gaps) and make sure each serious failure gets a fix and a test.</li>
<li><strong>Model choices:</strong> inform model selection and routing decisions by weighing quality, latency and cost with real data.</li>

</div>
<h2>Requirements</h2><div><strong>Product skills</strong>

<li>Roughly 4–8 years of relevant experience, ideally from a deeply technical product role, applied AI engineering or research engineering with clear product ownership.</li>
<li>Proven ownership of a complex technical product area, with features delivered to enterprise customers and measurable business results.</li>
<li>Strong product judgment: you can prioritize, work with customers and get capabilities shipped.</li>
<li>Customer-first: you turn enterprise needs into clear, actionable requirements.</li>
<li>Excellent communicator who can align engineering, research and go-to-market teams and present clearly to executives.</li>

<strong>Hands-on skills</strong>

<li>Comfortable vibe coding, building agents, connecting APIs and MCP tools, designing evaluations and debugging production failures.</li>
<li>Deep understanding of LLM reasoning, tool calling, multi-step task execution, orchestration patterns, evaluation methods and production observability for agents.</li>
<li>Technical fluency with APIs, cloud environments and AI deployment workflows.</li>

</div>
<h2>Nice to have</h2><div>

<li>Experience shipping AI agent products at a conversational AI or enterprise AI platform company.</li>
<li>Direct experience working with AI labs or model providers (early-access programs, model evaluations).</li>
<li>Familiarity with agent frameworks and protocols (e.g., LangGraph, MCP) and with voice AI.</li>
<li>Experience in regulated or mission-critical industries (airlines, banking, healthcare, payments) and with large SI partners.</li>
<li>Public work you can show: a repo, demo, blog post or talk.</li>

</div>

Senior Technical PM, Applied AI

<div><strong>About the Company:</strong></div>
<div><span>Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. </span></div>
<div> </div>
<div><span>Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!</span></div><div><br /></div><p>Netomi is seeking a highly analytical and detail-oriented candidate to join the Analytics team in Gurugram. As part of the team, you will work with data science, product, engineering, and customer success teams to drive complex data and trend analyses to propose ways to improve and, thereby contributing to improve the experience. You will also be responsible for benchmarking and measuring the performance of various product operations projects, building and publishing detailed scorecards and reports, identifying and driving new opportunities based on customer and business data.<br /><br />We are looking for an Engineer with a passion for using data to discover and solve real-world problems. You will enjoy working with rich data sets, modern business intelligence technology, and the ability to see your insights drive the features for our customers. You will also have the opportunity to contribute to the development of policies, processes, and tools to address product quality challenges in collaboration with teams.</p>
<h2>Responsibilities:</h2><div>

<li>Architect and implement scalable, secure, and reliable data pipelines using modern data platforms (e.g., <strong>Spark, Databricks, Airflow, Snowflake</strong>, etc.).</li>
<li>Develop <strong>ETL/ELT</strong> processes to ingest data from various structured and unstructured sources.</li>
<li>Perform <strong>Exploratory Data Analysis (EDA)</strong> to uncover trends, validate data integrity, and derive insights that inform data product development and business decisions.</li>
<li>Collaborate closely with data scientists, analysts, and software engineers to design data models that support high-quality analytics and real-time insights.</li>
<li>Write clean, maintainable code with <strong>comprehensive unit and integration tests</strong> to ensure reliability and stability in <strong>Python</strong>.</li>
<li>Thrive in an agile, collaborative environment and take ownership of end-to-end feature delivery.</li>

</div>
<h2>Requirements:</h2><div>

<li>Bachelor's or Master's degree in Computer Science, Engineering, or a related field.</li>
<li><strong>4+ years</strong> of hands-on experience in data engineering or backend software development roles.</li>
<li>Solid understanding of <strong>Relational Databases</strong> (RDS, MySQL, PostgreSQL).</li>
<li>Experience with <strong>Apache Kafka</strong> or <strong>RabbitMQ</strong> for building asynchronous, decoupled systems.</li>
<li>Proficiency with <strong>Python, SQL</strong>, and at least one data pipeline orchestration tool (e.g., <strong>Apache Airflow, Luigi, Prefect</strong>).</li>
<li>Strong experience with cloud-based data platforms (e.g., <strong>AWS Redshift, GCP BigQuery, Snowflake, Databricks</strong>).</li>
<li>Deep understanding of data modeling, data warehousing, and distributed systems.</li>

</div>
<h2>Additional Skills:</h2><div>

<li>Familiarity with DevOps practices (CI/CD, infrastructure as code, containerization with Docker/Kubernetes).</li>
<li>Exposure to <strong>AI/ML-integrated solutions</strong> or interest in working alongside data science teams.</li>
<li>Knowledge of data security and privacy regulations (e.g., <strong>GDPR, HIPAA</strong>).</li>
<li>Familiarity with prompt engineering and how <strong>LLM-based</strong> systems interact with data</li>

</div>

Data Engineer II

<div><strong>About the Company:</strong></div>
<div><span>Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. </span></div>
<div> </div>
<div><span>Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!</span></div><div><br /></div><p>Netomi is seeking a highly analytical and detail-oriented candidate to join the Analytics team in Gurugram. As part of the team, you will work with data science, product, engineering, and customer success teams to drive complex data and trend analyses to propose ways to improve and thereby contribute to improving the experience. You will also be responsible for benchmarking and measuring the performance of various product operations projects, building and publishing detailed scorecards and reports, identifying and driving new opportunities based on customer and business data.<br /><br />We are looking for an Engineer with a passion for using data to discover and solve real-world problems. You will enjoy working with rich data sets, modern business intelligence technology, and the ability to see your insights drive the features for our customers. You will also have the opportunity to contribute to the development of policies, processes, and tools to address product quality challenges in collaboration with teams.</p>
<h2>Responsibilities</h2><div>

<li>Architect and implement scalable, secure, and reliable data pipelines using modern data platforms (e.g., <strong>Spark, Databricks, Airflow, Snowflake</strong>, etc.).</li>
<li>Develop <strong>ETL/ELT</strong> processes to ingest data from various structured and unstructured sources.</li>
<li>Perform <strong>Exploratory Data Analysis (EDA)</strong> to uncover trends, validate data integrity, and derive insights that inform data product development and business decisions.</li>
<li>Collaborate closely with data scientists, analysts, and software engineers to design data models that support high-quality analytics and real-time insights.</li>
<li>Write clean, maintainable code with <strong>comprehensive unit and integration tests</strong> to ensure reliability and stability in <strong>Python</strong>.</li>
<li>Thrive in an agile, collaborative environment and take ownership of end-to-end feature delivery.</li>

</div>
<h2>Requirements:</h2><div>

<li>Bachelor's or Master's degree in Computer Science, Engineering, or a related field.</li>
<li>2+ years of hands-on experience in data engineering or backend software development roles.</li>
<li>Solid understanding of Relational Databases (RDS, MySQL, PostgreSQL).</li>
<li>Experience with Apache Kafka or RabbitMQ for building asynchronous, decoupled systems.</li>
<li>Proficiency with Python, SQL, and at least one data pipeline orchestration tool (e.g., Apache Airflow, Luigi, Prefect).</li>
<li>Strong experience with cloud-based data platforms (e.g., AWS Redshift, GCP BigQuery, Snowflake, Databricks).</li>
<li>Deep understanding of data modeling, data warehousing, and distributed systems.</li>

</div>
<h2>Additional Skills</h2><div>

<li>Familiarity with DevOps practices (CI/CD, infrastructure as code, containerization with Docker/Kubernetes).</li>
<li>Exposure to AI/ML-integrated solutions or interest in working alongside data science teams.</li>
<li>Knowledge of data security and privacy regulations (e.g., GDPR, HIPAA).</li>
<li>Familiarity with prompt engineering and how LLM-based systems interact with data.</li>

</div>

Data Engineer I

<div><strong>About the Company:</strong></div>
<div><span>Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. </span></div>
<div> </div>
<div><span>Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!</span></div><div><br /></div><p>As a Staff Agentic AI Engineer at Netomi, you will be a senior individual contributor helping buildthe core agentic factory platform that will enable customers to agentically define and buildcustomer-specific agents to expand marketing-oriented enterprise automation and brandinteraction use cases. You will deliver innovative designs and implement reliable, scalable, andmeasurable agentic systems used by enterprise customers and business users in complex,real-world production environments.<br /><br />This is a hands-on engineering role for someone who drives innovation and has built productionLLM and agent systems, understands modern agent architectures, and has strong instincts forevaluation, observability, performance diagnosis, and continuous optimization. You will workacross agent orchestration, tool use, prompt and tool-selection strategies, RAG, embeddings,guardrails, and LLM evaluation systems and marry these with appropriate deterministic andML-based solutions to expand Netomi’s agentic factory.</p>
<h2>Responsibilities:</h2><ul><li>Design, build, and improve production-grade AI agentic systems that optimizeweb-based and chat-based experiences leveraging grounded, structured data</li>
<li>Architect agent workflows involving reasoning, tool use, retrieval, guardrails, escalation paths, and performance monitoring</li>
<li>Evaluate Deep Agent, Claude Agent, OpenAI Agent, LangGraph, and other emerging agent orchestration patterns and frameworks for marketing-oriented use cases</li>
<li>Build and maintain LLM evaluation systems, including LLM-as-judge workflows, regression evals, guardrail testing, quality metrics, and production behavior analysis</li>
<li>Diagnose agent performance issues across prompts, tool selection, retrieval quality, latency, cost, task completion, and failure modes</li>
<li>Design and implement RAG and embedding-based capabilities for enterprise knowledge access and automation workflows</li>
<li>Build scalable Python services and platform components deployed in AWS cloud environments</li>
<li>Partner with product, platform, and engineering teams to translate emerging agentic AI capabilities into reliable platform features</li>
<li>Establish engineering best practices for continuous optimization of agentic systems</li>
<li>Stay current with advances in LLMs, agent architectures, AI coding tools, eval methodologies, retrieval systems, and enterprise automation</li></ul>
<h2>Requirements:</h2><ul><li>Bachelor’s Degree or higher in a quantitative field (Statistics, Computer Science, Engineering, Mathematics)</li>
<li>5-7+ years of experience in AI/ML engineering, applied machine learning, natural language processing, and/or AI systems development</li>
<li>3-5 years of experience in applying AI, data science, and machine learning in the marketing space</li>
<li>Experience leveraging data from Adobe Experience Platform, AdobeCommerce/Magento, Adobe Real-time CDP, Adobe Target, and/or AdobeAnalytics/Customer Journey Analytics for data science modeling and performance analysis</li>
<li>Strong Python engineering skills and experience building scalable production software systems</li>
<li>Hands-on experience with LangGraph, LangChain, or related agent orchestration frameworks</li>
<li>Strong understanding of RAG, embeddings, retrieval quality, and knowledge-grounded generation</li>
<li>Experience deploying or operating systems in AWS cloud environments</li>
<li>Daily use of AI coding tools such as Codex, Claude Code, Cursor, or similar tools as part of software development workflows</li>
<li>Strong engineering judgment, ability to work independently, and comfort operating as a senior individual contributor on ambiguous technical problems</li></ul>
<h2>Preferred Qualifications:</h2><ul><li>Master’s Degree or higher in a quantitative field (Statistics, Computer Science,Engineering, Mathematics)</li>
<li>Experience building or using knowledge graphs for enterprise knowledge modeling,retrieval, reasoning, or personalization</li>
<li>Hands-on experience building production LLM or AI agent systems</li>
<li>Experience designing agent architectures involving tool use, reasoning flows, retrieval, memory, guardrails, and workflow orchestration</li>
<li>Experience developing AI evaluation systems, including LLM-as-judge, guardrail evaluation, regression testing, and production quality measurement</li>
<li>Experience with enterprise automation platforms, customer experience systems, workflow automation, or AI-powered business process automation</li>
<li>Experience with observability and tracing for LLM or agent systems</li>
<li>Experience optimizing agent systems for latency, cost, reliability, safety, and task success</li>
<li>Experience with vector databases, search infrastructure, model routing, caching, ormulti-model architectures</li></ul>

Staff Agentic AI Engineer - Marketing

<div><strong>About the Company:</strong></div>
<div><span>Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences. </span></div>
<div> </div>
<div><span>Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!</span></div><div><br /></div><p><span>About the role<br /><br />We are looking for an Agentic Engineer to build and scale agentic workflows and tools using Netomi’s no-code platform. This role requires strong software engineering fundamentals combined with prompt engineering and API-driven automation to power reliable, autonomous AI agents.</span></p>
<h2>Responsibilities</h2><ul><li>
<p>Design and write high-quality prompts for LLM-based agents (GPT-class models preferred).</p>
</li>
<li>
<p>Build agentic tools and workflows using Netomi’s no-code platform (similar to Workato, Zapier, n8n).</p>
</li>
<li>
<p>Integrate external and internal APIs, including authentication, data mapping, and error handling.</p>
</li>
<li>
<p>Implement unit tests, debug issues, and ensure reliability of agent workflows.</p>
</li>
<li>
<p>Apply engineering best practices and design patterns such as retries, timeouts, idempotency, and lazy loading.</p>
</li>
<li>
<p>Optimize agents for performance, cost, and fault tolerance.</p>
</li>
<li>
<p>Collaborate with Product, QA, and Delivery teams to ship production-grade agentic solutions.</p>
</li></ul>
<h2>Requirement</h2><ul><li>
<p>4–7 years of experience as a Software Development Engineer or similar role.</p>
</li>
<li>
<p>Strong understanding of prompt engineering and LLM behavior.</p>
</li>
<li>
<p>Hands-on experience with REST APIs, webhooks, and JSON-based integrations.</p>
</li>
<li>
<p>Solid experience in unit testing, debugging, and troubleshooting.</p>
</li>
<li>
<p>Knowledge of resilient system design patterns and non-happy path handling.</p>
</li></ul>
<h2>Nice to Have</h2><ul><li>
<p>Experience with no-code/low-code automation platforms.</p>
</li>
<li>
<p>Exposure to agentic AI, conversational AI, or workflow orchestration systems.</p>
</li>
<li>
<p>Familiarity with observability and monitoring in production systems.</p>
</li></ul>

Netomi

Open jobs at Netomi

Senior Technical PM, Applied AI

Data Engineer II

Data Engineer I

Staff Agentic AI Engineer - Marketing

Agentic Engineer Level II/III

Working for Netomi?

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