2 months ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Build and debug product features and resolve issues across APIs, data transformations, and deployment workflows.
- Build and maintain Python utilities and services for validation, transformation, and automated QC checklist execution.
- Implement GenAI workflows using LangChain and OpenAI, including prompts, tool/function calling, and reliability guards.
- Design and tune PGVector indexing and retrieval for checklist content, policies, and artifacts.
- Create evaluators, test harnesses, and regression suites for LLM pipelines and generated code outputs.
- Instrument logs and metrics, perform root-cause analysis across data, prompts, and model outputs, and document playbooks.
- Collaborate with Product, Customer Success, and QA to triage tickets, reproduce issues, ship hotfixes, and execute safe migrations.
- Harden onboarding and production deployments through configuration management, secrets hygiene, and rollback strategies.
- Maintain knowledge bases and SOPs for integrations, data contracts, and compliance-sensitive workflows.
Requirements
- 4–6 years of strong Python development experience.
- Bachelor’s degree in computer science or engineering, or equivalent practical experience.
- Experience implementing GenAI/LLM solutions in production-like settings.
- Strong Python 3.x software engineering and debugging proficiency.
- Experience with LangChain, OpenAI API, prompt engineering, tool/function calling, and reliability guards.
- Experience with NLP utilities and text processing using nltk or similar tools.
- Experience with MongoDB data modeling and query optimization.
- Experience with vector databases and retrieval, particularly PGVector on Postgres and RAG-like patterns.
- Experience with LLM orchestration using OpenAI or Gemini, including retries, timeouts, and structured outputs.
- Strong observability, log analysis, debugging, and communication skills.
- Nice-to-have experience with MLOps fundamentals, MCP server or tool-agent patterns, FastAPI, async IO, GitHub Actions, Docker, Python packaging, environments, testing, REST APIs, JSON, Pandas, and text normalization/tokenization.
- Experience in mortgage, QC, RegTech, or checklist-related domains is beneficial.
- Working knowledge of GitHub, Git, Issues/Projects, pull-request reviews, JIRA, Confluence, Postman, cURL, VS Code, Copilot, Cursor, venv, poetry, and pytest.
Tech Stack
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