AI / ML Engineer

Why this role Chargebee’s GBT AI team builds internal AI agents and workflows that power smarter, faster operations across Finance, HR, Legal , Marketing, RevOps and GTM. We’re looking for an AI Engineer who can think end-to-end—understand the business process, design the right solution (not just an out-of-the-box tool), and ship robust agentic systems that deliver measurable impact.What you’ll do Design, build, and ship AI agentsthat automate internal workflows (e.g., case triage, knowledge assistants, data reconciliation, summarization, entity extraction, task orchestration). Own the full lifecycle : problem framing, data/knowledge mapping, prototype → production, instrumentation, and iteration based on metrics. Integrate with the GBT Tech stackusing APIs, webhooks, and internal services across our SaaS stack (ticketing/CRM/data warehouse). Engineer LLM prompts & tools(function calling, tools/toolkits, retrieval/RAG, multi-step planning) and select the right model for the job. Evaluate and hardensolutions with offline tests, golden sets, guardrails, and observability; drive down hallucinations and failure modes. Document clearlyand partner with stakeholders to align on success criteria, SLAs, and ongoing maintenance. (Nice-to-have ML) : apply ML where it adds value—basic classifiers/embeddings, light fine-tuning/adapters, feature work, and A/B evaluation.What you’ll bring (must-haves) 2-6 years of professional software experience , including hands-on delivery of at least one AI agent or workflow in production or a serious pilot. Practical LLM API experience : you’ve integratedOpenAIand/orAnthropic (Claude)(or comparable model APIs) to build real features. Strong coding inPython or TypeScript , with sound software engineering practices (testing, code reviews, CI/CD, Git Best Practices). Working knowledge ofprompt design ,function/tool calling ,RAG(vector stores, chunking, indexing), andpipeline orchestration . Comfort withHTTP APIs , authentication, and integrating multiple systems into a coherent solution. Experience in developing, debugging and optimizing data pipelines and transformations usingPython/Pandas/SQL. Experience working with at least one no-code or low-code agentic workflow automation tool such as n8n, Zapier, or OpenAI Agent Builder.Nice to have Experience withLangChain, LangGraph, LlamaIndex, Semantic Kernel , or similar agent frameworks. Observability/eval tools (e.g.,LangSmith, Phoenix/Arize, Weights & Biases , OpenTelemetry). Vector databases ( Pinecone, Weaviate, pgvector,etc ) and data systems (SQL, dbt, warehouse basics). Knowledge ofML fundamentals(classification,forecasting, embeddings, evaluation) Security & compliance awareness (PII handling, access controls, red-team/guardrails). SaaS/B2B domain familiarity; subscription billing/revenue ops context is a plus. Experience working with major cloud technologies (AWS, Azure, or GCP) Experience integrations data to GTM Tech stack and other business systems such as SFDC, Netsuite, Success Factors, ADP, Google Big QueryHow we work Small, outcome-oriented team that ships iteratively withclear success metrics(accuracy, deflection rate, cycle time, $ impact). Bias toautomation + ownership : you’ll take features from discovery → design → deployment. Model-agnostic approach: choose theright tool/modelfor quality, latency, and cost.Apply with A short note on anagent or AI workflow you’ve built , your role, tech stack, and impact. Links (repo, demo, doc) welcome.

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