Senior Python Engineer - Backend & Data (Remote)

Senior Python Engineer - Backend & Data (Remote)

Bold Business is an AI-first U.S.-based company building automation systems, AI agents, and production software for clients like AT&T, JP Morgan, and Verizon. We ship real systems that deliver impact — not experiments.

The Role

We're hiring a Senior Python Engineer who can own both backend systems and the data layer behind them. This role sits between backend and data — you will build APIs, design pipelines, and ensure the data powering AI systems is clean and reliable.

You'll work under a Lead Architect. You are expected to execute independently and own outcomes.

What You'll Do

• Build and maintain production Python APIs (FastAPI or similar)
• Design and run data pipelines (ETL, ingestion, transformation)
• Own data quality — validation, monitoring, failure handling
• Structure data for RAG systems and AI agents
• Design and manage databases (PostgreSQL + vector DBs)
• Integrate external systems (APIs, webhooks, third-party tools)
• Debug across backend, data pipelines, and AI outputs

Non-Negotiables (Knockout Requirements)

You should not apply if you cannot clearly demonstrate all of the following:

1. Strong English communication (written and spoken) You can clearly explain technical concepts to non-technical stakeholders and operate in a U.S.-based team environment.
2. You have built and maintained production Python APIs (not tutorials or small scripts — real systems in use)
3. You have owned data pipelines end-to-end (ingestion → transformation → reliability in production)
4. You are strong in SQL and database design (schemas, performance, tradeoffs — not just basic queries)
5. You have worked with real, messy data (multiple sources, failures, edge cases — not clean datasets)

Required Skills

• Python (4–6 years, production backend + data work)
• FastAPI or similar frameworks
• Strong SQL and database design
• API integrations (REST, webhooks)
• Testing and clean Git workflows

AI / Data Context (Expected Working Level)

• LLM API integration (OpenAI, Anthropic, etc.)
• Understanding of how RAG systems use data
• Prompt structure and output handling
• Exposure to vector databases (pgvector, Pinecone, etc.)

Nice to Have

• LangChain, LangGraph, CrewAI
• Airflow, Prefect, or pipeline orchestration
• AWS / GCP experience
• Docker / CI-CD
• Basic BI / analytics tools

What This Role Is

• A hands-on builder role
• Ownership of backend + data layer
• High accountability, low hand-holding

What This Role Is Not

• Not a pure Data Engineer
• Not an ML research role
• Not a junior position

Final Note

• We will go deep into your past work.
• If you can clearly explain what you built, why you built it that way, and what broke — you'll do well here.
• If not, this role will be a stretch.