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 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

• 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.