About the job :

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)