Python Developer (Gen AI)

Infrrd; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Infrrd is seeking a Python Developer to join our engineering team in Bengaluru to build and optimize our product with a focus on rapid debugging, automation, and AI-first workflows.

You will implement GenAI/LLM solutions in production-like settings, design vector retrieval systems with PGVector, and harden deployments with robust observability and rollback strategies. Strong debugging and communication skills are essential.

Qualifications

• 4–6 years of experience in Python development.

Responsibilities

• Build and debug features for the product across APIs and deployment workflows.
• Develop Python utilities/services for validation, transformation, and automation of QC checklists.
• Implement GenAI workflows using LangChain/OpenAI, including prompt design and guards.
• Design and tune vector indexing and retrieval over PGVector for content and artefacts.
• Create evaluators, test harnesses, and regression suites for LLM pipelines and generated code outputs.
• Instrument logs/metrics and perform root‑cause analysis across data, prompts, and model outputs; document playbooks.
• Collaborate with Product/CS/QA to triage tickets and ship hotfixes.
• Harden deployments with config management, secrets hygiene, and rollback strategies.
• Maintain knowledge base and SOPs for integrations and data contracts.

Skills

Python

GenAI/LLM

NLP

MongoDB

PGVector

Observability

LLM orchestration

Vector retrieval

Debugging

Education

Bachelor's in CS/Engineering

Tools

GitHub

JIRA

Confluence

Postman

cURL

VS Code

Docker

Poetry

Pytest

Job description

We are on the lookout for a motivated Python Developer to join our engineering team. In this role, you will help us to build our product in an efficient and solid way. To provide hands‑on technical support during implementation of product features with a focus on rapid debugging, scripting, and data analysis; ensure smooth integrations and reliable deployments while improving developer productivity using AI‑first tools and automation; and optimise the existing code and framework.

Responsibilities

• Build and debug features for the product. Rollout issues across APIs, data transformations, and deployment workflows with rapid turnarounds.
• Build and maintain Python utilities/services for validation, transformation, and automation of QC checklist execution.
• Implement GenAI workflows using LangChain/OpenAI, including prompt design, tools, and guards for reliability and traceability.
• Design and tune vector indexing and retrieval over PGVector for checklist content, policies, and artefacts.
• Create evaluators, test harnesses, and regression suites for LLM pipelines and generated code outputs.
• Instrument logs/metrics and perform root‑cause analysis across data, prompts, and model outputs; document playbooks.
• Collaborate with Product/CS/QA to triage tickets, reproduce issues, and ship hotfixes and safe migrations.
• Harden deployments with config management, secrets hygiene, and rollback strategies for onboarding and production.
• Maintain knowledge base and SOPs for integrations, data contracts, and compliance‑sensitive workflows.

Requirements

• 4-6 years of experience with a strong Python development background.
• Bachelor's in CS/Engineering or equivalent practical experience.
• Experience implementing GenAI/LLM solutions in production‑like settings.
• Excellent debugging and communication skills.

Must-Have Skills

• Python 3 x with strong software engineering and debugging proficiency.
• GenAI/LLM: LangChain, OpenAI API, prompt engineering, tool/function calling, guards.
• NLP utilities and text processing with NLTK or similar.
• MongoDB data modelling and query optimisation for app/ops flows.
• Vector databases and retrieval (PGVector on Postgres) for RAG‑like patterns.
• Observability and log analysis for rapid root‑cause and fix‑forward.
• LLM orchestration with OpenAI/Gemini, including retries, timeouts, and structured outputs.
• Vector retrieval with PGVector (indexing, chunking, similarity tuning, evals).
• Debugging onboarding/deployment issues across configs, data, and environments

Nice To Have Skills

• MLOps fundamentals (model/config/versioning, evals, CI for LLM flows).
• MCP server or tool‑agent patterns for internal developer workflows.
• FastAPI/asyncIO for lightweight services and integrations.
• CI/CD (GitHub Actions) and infra basics (Docker).
• Experience with mortgage/QC/RegTech domains or checklists.
• Python packaging, environments, and testing; REST APIs and JSON.
• Prompt engineering basics: model limits, latency, and cost trade‑offs.
• Data handling with Pandas and text normalization/tokenization

Working Knowledge (Tools)

• GitHub/Git; Issues/Projects; PR reviews.
• JIRA/Confluence for triage and runbooks.
• Postman/cURL for API validation.
• VS Code with Copilot/Cursor; Python tooling (venv/poetry/pytest).

This job was posted by Jacqueline Lobo from Infrrd.