Python Developer (Gen AI)

Infrrd seeks a Python Developer (Gen AI) for its Product Engineering team in Bangalore, Karnataka. The role supports product-feature implementation for an Intelligent Document Processing platform, with an emphasis on rapid debugging, scripting, data analysis, reliable integrations and deployments, and improving developer productivity through AI-first tools and automation.

Responsibilities

• Build and debug product features and resolve rollout issues across APIs, data transformations, and deployment workflows. Develop Python utilities and services for validation, transformation, and automated execution of quality-control checklists; optimize existing code and frameworks.
• Implement GenAI workflows with LangChain and OpenAI, including prompts, tools, and safeguards for reliability and traceability. 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.
• Analyze logs, metrics, data, prompts, and model outputs to identify root causes. Work with Product, Customer Success, and QA to reproduce issues and deliver hotfixes and safe migrations. Strengthen deployment configuration, secrets handling, and rollback strategies; maintain integration playbooks, data contracts, and procedures for compliance-sensitive workflows.

Required qualifications and skills:

• 4–6 years of strong Python development experience; a bachelor’s degree in computer science or engineering, or equivalent practical experience. Production-like GenAI/LLM implementation experience, strong debugging skills, and effective communication are required.
• Python 3.x; LangChain, OpenAI API, prompt engineering, tool/function calling, and safeguards; NLP and text processing with NLTK or similar tools; MongoDB modeling and query optimization; PGVector on PostgreSQL for RAG-style retrieval, including chunking and similarity tuning. The role also calls for observability, log analysis, LLM orchestration with OpenAI or Gemini, and troubleshooting configuration, data, and environment issues.

Preferred and working knowledge:

• MLOps, MCP servers or tool-agent patterns, FastAPI and asynchronous I/O, GitHub Actions, Docker, Python packaging and testing, REST APIs, JSON, Pandas, and mortgage, QC, or RegTech workflows are desirable. Working knowledge of Git/GitHub, Jira, Confluence, Postman or cURL, VS Code, Copilot or Cursor, and Python environment and testing tools is also listed.