nd now, we are on the lookout for a motivated Python Developer (w/ GenAI) 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 the 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
- Bachelor's in CS/Engineering or equivalent practical experience.
- Strong Python development background.
- 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
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/async IO 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 tradeoffs.
- Data handling with Pandas and text normalisation/tokenisation.
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.
