Senior AI Engineer

RAIVA Technologies UG (haftungsbeschränkt); Potsdam; Vor Ort; EUR 65.000 - 85.000; Vollzeit

Zusammenfassung

RAIVA in Potsdam is looking for an experienced AI/ML engineer to build their evidence-first retrieval and reasoning core. Your role involves designing multi-agent retrieval pipelines and improving evidence extraction quality.

Ideal candidates will have extensive experience in production AI systems, deep practical knowledge in retrieval engineering, and strong Python skills. This position offers the chance to impact high-stakes industries like legal and finance.

Qualifikationen

• 5+ years building production AI/ML or applied LLM systems.
• Deep practical experience with RAG, hybrid search, embeddings, and rerankers.
• Track record of shipping evidence-backed or high-stakes AI features.

Aufgaben

• Design and ship multi-agent retrieval pipelines.
• Own embedding strategy across primary and domain-specific models.
• Improve evidence extraction and verification quality.

Kenntnisse

Production AI/ML systems

RAG and hybrid search

Embeddings and rerankers

Strong Python skills

FastAPI

Async workloads

Vector DBs (Qdrant)

Tools

Python

FastAPI

Qdrant

Docker

Jobbeschreibung

Build the evidence-first retrieval and reasoning core powering RAIVA across regulated industries.

About the role

You will own large parts of our multi-agent retrieval, evidence verification, and consortium scoring stack. We care about provable answers — not vibes — so your work directly determines whether a legal, financial, or real‑estate professional can trust an answer enough to act on it.

What you'll do

• Design and ship multi-agent retrieval pipelines (SQL, BM25, vector, optional graph)
• Own embedding strategy across primary (Cohere v4) and domain‑specific models
• Improve evidence extraction, verification, and consortium scoring quality
• Define evals and guardrails so quality regressions are caught before users see them
• Collaborate with backend/MLOps to take experiments to stable, observable production

What we look for

• 5+ years building production AI/ML or applied LLM systems
• Deep practical experience with RAG, hybrid search, embeddings, and rerankers
• Strong Python; comfortable with FastAPI, async workloads, and vector DBs (Qdrant)
• Track record of shipping evidence-backed or high‑stakes AI features

Nice to have

• Experience with Cohere, OpenAI, Gemini, or domain‑tuned embedding models
• Prior work in legal, financial, tax, or real‑estate tech
• Open‑source contributions in retrieval/LLM tooling

Stack & tools

Python

FastAPI

Supabase

Qdrant

LangChain

Cohere

OpenTelemetry

Docker