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AI / ML Engineer

AI / ML Engineer

ChargebeeDelhi, India
17 days ago
Job description

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 agents that 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 stack using 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 harden solutions with offline tests, golden sets, guardrails, and observability; drive down hallucinations and failure modes.
  • Document clearly and 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 integrated OpenAI and / or Anthropic (Claude) (or comparable model APIs) to build real features.
  • Strong coding in Python or TypeScript, with sound software engineering practices (testing, code reviews, CI / CD, Git Best Practices).
  • Working knowledge of prompt design, function / tool calling, RAG (vector stores, chunking, indexing), and pipeline orchestration.
  • Comfort with HTTP APIs, authentication, and integrating multiple systems into a coherent solution.
  • Experience in developing, debugging and optimizing data pipelines and transformations using Python / 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 with LangChain, 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 of ML 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 Query
  • How we work

  • Small, outcome-oriented team that ships iteratively with clear success metrics (accuracy, deflection rate, cycle time, $ impact).
  • Bias to automation + ownership : you’ll take features from discovery → design → deployment.
  • Model-agnostic approach : choose the right tool / model for quality, latency, and cost.
  • Apply with

  • A short note on an agent or AI workflow you’ve built, your role, tech stack, and impact. Links (repo, demo, doc) welcome.
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    Ai Ml Engineer • Delhi, India

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