Hire Python Developers
Hire Python developers.
Get Python engineers who build backends, automation, and AI features that work in production — not notebooks. FortifiLab developers have shipped RAG pipelines, LLM chatbots, and automation that connects Zoom, AI, and Slack for real teams.
AI & LLM features
RAG pipelines, embeddings, agents, and evaluations with LangChain and OpenAI — grounded in your data and measured, not vibes.
APIs & services
FastAPI and Django services with clean typing, background workers, and the observability to run them reliably.
Automation & data
Workflow automation, scraping, ETL, and data pipelines that turn manual, repetitive work into something that just runs.
What our Python developers build
- LLM & RAG pipelines
- AI agents & automation
- FastAPI / Django backends
- Data pipelines & ETL
- Third-party & API integrations
- Evaluations & guardrails
Tools & libraries
How to work with us
Engagement models
Dedicated developer
A senior Python engineer for your backend, data, or AI work, embedded in your team with weekly demos.
AI feature build
A scoped AI or automation feature — a RAG chatbot, a pipeline, an agent — delivered and integrated into your product.
Backend / data project
A defined backend or data-pipeline deliverable with a clear timeline and budget.
Built with Python
Recent work
CCA User Insight Hub — RAG
Retrieval-augmented chatbot on LangChain + OpenAI with a custom knowledge ingestion pipeline.
Videxa — AI SaaS
RAG pipeline and transcription orchestration for automated clinical video review. 90% faster review.
AI Automation Pipeline
Zoom → AI → Slack pipeline extracting structured insights from recordings automatically.
Frequently asked
How much does it cost to hire Python developers?
Dedicated Python engineers are billed monthly at a fraction of a comparable US/UK in-house hire. AI feature builds can also be scoped as fixed-price projects.
Can your Python developers build AI and LLM features?
Yes — AI/LLM work is a core strength: RAG pipelines, agents, and automation with LangChain and OpenAI, shipped with evaluations so they hold up in production.
Do you do data pipelines and automation, not just AI?
Yes. FastAPI/Django backends, ETL, scraping, and workflow automation are all standard work for our Python engineers.
How do you make AI features reliable?
We ground models in your data, add guardrails, and build evaluations so behavior is measurable rather than a demo that breaks on real inputs.
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