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Senior Full Stack Engineer; m​/w​/d

in 10115, Berlin, Berlin, Deutschland
Unternehmen: Placed Technologies GmbH
Vollzeit position
Verfasst am 2026-10-16
Berufliche Spezialisierung:
  • Software Entwicklung
    Backend Entwicklung, Künstliche Intelligenz Ingenieur, Python, Full Stack Entwickler
Gehalts-/Lohnspanne oder Branchenbenchmark: 90000 - 130000 EUR pro Jahr EUR 90000.00 130000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: Senior Full Stack Engineer (m/w/d)

Start: as soon as possible
Location: Berlin Mitte or Potsdam-Babelsberg

We have two offices, one in Berlin Mitte and one in Potsdam-Babelsberg. You can work from either location.

PLACED is a Berlin-based AI startup rebuilding how Europe's 30,000+ recruitment agencies win business. We combine large-scale job market data with agentic AI, turning outdated, manual workflows into intelligent, automated pipelines. We have just closed our first institutional funding round.

We're looking for Senior Full Stack Engineers to help us take the product to the next level. You'll work on real features for real users with impact from day one.

We're seeking exceptional, A-player engineers who own the full slice: from pixel-perfect Next.js interfaces to high-performance FastAPI and Hono backends, LLM pipelines, and cloud infrastructure. You'll design data models with PostgreSQL, ship production AI features, and help drive our backend migration from Python to Type Script.

Our tech stack
  • Backend:
    Python 3.13, FastAPI (primary production API, 123+ endpoints);
    Type Script 5, Hono, Bun (new backend in active development)

  • Frontend:
    Type Script, React, Next.js 16

  • Database:
    PostgreSQL 17 (pgvector for vector search), Redis (caching, async flags)

  • Infrastructure: AWS (ECS/Fargate, S3, SES, ECR, RDS), GCP (Vertex AI, Document AI, Cloud Translation), Docker

  • AI / LLM:
    OpenAI (embeddings, chat), Google Gemini / Vertex AI, Anthropic Claude, LiteLLM (multi-provider routing), Instructor (structured outputs), Langfuse (LLM observability)

  • Auth:
    WorkOS (Auth Kit, JWT)

  • Observability:
    Sentry, Prometheus, Langfuse, structlog

  • Tooling:
    Git Hub Actions CI/CD, UV (Python), Bun, Ruff, mypy, ESLint, pre-commit, pytest, Drizzle ORM, SQL Alchemy 2.0 (async)

What you'll do
  • Architect and implement responsive, high-performance user interfaces with Next.js 16 and React

  • Design and build secure, high-performance RESTful APIs in FastAPI (Python) and Hono (Type Script/Bun)

  • Drive the active migration from our Python backend to the Type Script/Hono architecture

  • Model and optimize relational schemas in PostgreSQL 17, including pgvector embeddings for semantic search

  • Build and maintain Redis-backed caching layers and async task patterns

  • Orchestrate multi-provider LLM calls via LiteLLM, integrating OpenAI, Gemini/Vertex AI, and Claude

  • Instrument LLM pipelines with Langfuse for observability, cost tracking, and quality evaluation

  • Containerize services with Docker and deploy to AWS ECS/Fargate and GCP (Vertex AI, Document AI)

  • Build and maintain CI/CD pipelines in Git Hub Actions with 100% diff-coverage enforcement

  • Research, design, and implement autonomous AI agents that orchestrate tasks and workflows using LLMs and custom policies

  • Ensure fault tolerance, high availability, and scalability across distributed systems; identify and mitigate bottlenecks

  • Partner with product, design, and QA to deliver end-to-end features

  • Conduct code reviews and champion best practices

What we are looking for
  • 5+ years of professional experience in full-stack development

  • Proficiency with Next.js, React, and Type Script, including SSR, app router, and server components

  • Deep experience building Python APIs with FastAPI (or equivalent async framework)

  • Strong Type Script skills, with experience in Hono, Express, or similar server frameworks

  • Strong SQL skills and hands-on experience with PostgreSQL, including advanced features (partitioning, indexing, full-text search)

  • Experience with vector databases or pgvector for embedding storage and semantic search

  • Familiarity with Redis for caching and async coordination

  • Solid AWS expertise (ECS/Fargate, S3, SES, ECR, RDS); GCP exposure a plus

  • Experience with containerization (Docker) and CI/CD pipelines (Git Hub Actions)

  • Demonstrated knowledge of distributed systems…

Stellen-Anforderungen
10+ Jahre Berufserfahrung
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