Hello there! Infrrd here.
Haven’t heard of us before? No problem. First off, it’s pronounced In-fur-d. We are the creators of a proprietary Intelligent Document Processing platform that automates data extraction from complex and messy unstructured documents. For over a decade, we’ve been building expertise in Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Neural Networks and much more. We are building technology that is disrupting the data extraction space for 5+ years now.
And now, we are on the lookout for a motivated Senior Python Developer to join our Engineering team. In this role, you will help us to build our product in an efficient and solid way.
Job Purpose :
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 optimize the existing code and framework.
Job Duties and 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 artifacts.
- 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.
Required Qualifications :
Minimum 6+ years of experience.Bachelor's in CS / Engineering or equivalent practical experienceStrong Python development backgroundExperience implementing GenAI / LLM solutions in production-like settingsExcellent 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 modeling and query optimization 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 environmentsNice 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 normalization / tokenizationWorking 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).