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This job expired on 26/08/2026. It no longer accepts applications.

AI Backend Engineer – Hybrid (Heidelberg)

paretos

Hybrid 🇬🇧 English
Python FastAPI pydantic PostgreSQL dbt RAG pipelines Claude Code

Job description

About the role

As an AI Backend Engineer at paretos, you will help build the technical backbone of a leading Decision Intelligence platform. Working in a hybrid setup (1–2 days onsite in Heidelberg), you will collaborate closely with product managers, forward‑deployed AI engineers, and data scientists to turn forecasting and optimization models into production‑ready services.

Key responsibilities

  • Design, develop, and operate scalable backend services in Python using FastAPI and pydantic.
  • Create clean, robust APIs that connect the platform, agents, ML models, front‑end, and customer systems such as ERP and BI tools.
  • Build and maintain the semantic data layer with PostgreSQL, dbt transformations, pipelines, caching, and retrieval mechanisms.
  • Integrate large language models and agentic workflows, including tool use, function calling, RAG pipelines, evaluation frameworks, and production guardrails.
  • Measure feature adoption, observe usage patterns, and iterate with product and AI teams to maximize impact.

Required profile

  • Strong product mindset with a focus on customer value and measurable outcomes.
  • Ability to translate business requirements into pragmatic technical solutions.
  • Experience prototyping quickly, gathering feedback, and iterating in short cycles.

Required skills

  • Python
  • FastAPI
  • pydantic
  • PostgreSQL
  • dbt
  • Large Language Model (LLM) integration
  • Retrieval‑Augmented Generation (RAG) pipelines
  • Claude Code or similar AI‑assisted coding tools

What we offer

  • Inclusive, equal‑opportunity culture guided by the GUNG HO principles.
  • Opportunity to work on cutting‑edge AI‑first products that impact enterprise decision‑making.
  • Hybrid work arrangement with a collaborative team in Heidelberg.

Questions fréquentes

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Published 3 months ago

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