Python Developer Gen AI

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.
  
  

• 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.
  
  

• 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
  
  

• 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
  
  

• 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).