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Salary
$93k – $139k per year
Location
In office (Berlin)
Seniority
Middle · 3+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Clera is a San Francisco company that runs an AI recruiting platform positioned as a talent agent rather than a job board, matching engineers and other technical candidates to roles at venture-backed startups. Its system reads a candidate's background and preferences, then represents them to hiring teams at companies funded by firms such as Andreessen Horowitz, Y Combinator, Index Ventures and General Catalyst, compressing the introduction step that traditional headhunting handles manually. The model is aimed at the segment where recruiter fees are highest and candidate supply is thinnest, and the platform handles screening, scheduling and pipeline tracking for both sides of the match.

About the Role

This is a full-stack AI engineering role on a small, technical product and engineering team building AI-powered tools for construction professionals. You will own features end-to-end, from database schema and LLM integration through to UI, while also contributing to the internal platform foundations that let new use cases ship quickly.

What You'll Do

  • Build and own end-to-end AI features from concept through production, including document versioning and agentic chat workflows.

  • Design and implement features across the full development lifecycle: database schema, LLM tuning, evaluation, and UI.

  • Manage evaluations, scoring, and error analysis on new and shipped AI features to ensure quality.

  • Contribute to the workflow harness, decision-trace standard, and evaluation tooling that accelerates shipping new use cases.

  • Build reusable human review and approval surfaces that earn trust in AI output.

  • Model and evolve a construction domain ontology and project graph, including entity resolution across documents such as bills of quantities, contracts, and drawings.

  • Design features that link answers to evidence and make decisions auditable and traceable.

  • Extend multi-modal ingestion of unstructured documents (PDFs, scans, drawings, and 3D models) at scale.

  • Build read/write integrations with customer systems (document management, ERP) to complete workflows end-to-end.

  • Contribute to scalable data pipelines and support native BIM/DWG file processing.

What We're Looking For

  • 3+ years of experience as a full-stack software engineer, ideally in fast-paced, early-stage B2B startup environments.

  • Proven track record delivering production-grade applied AI features to customers.

  • Proficiency with TypeScript, Python, and SQL for building full-stack applications.

  • Experience building backend APIs and database schemas using frameworks such as Fastify and Prisma, or equivalents.

  • Experience integrating and optimizing LLM APIs (OpenAI, Azure, Gemini, Cohere, or similar).

  • Experience with cloud infrastructure such as AWS (RDS, S3, Elastic Beanstalk) or equivalent.

  • Experience building data pipelines and ETL workflows for processing unstructured data at scale.

  • Experience with vector databases and semantic search implementations.

  • Experience designing and implementing evaluation frameworks and error analysis for AI systems.

  • Experience building internal platform or developer-facing tooling that other engineers ship on top of.

  • Full ownership mindset: comfortable designing and implementing solutions to customer problems end-to-end.

  • Experience with workflow orchestration tools (Prefect, Airflow, or similar) is a plus.

  • Experience with document processing, OCR, or multi-modal data ingestion is a plus.

  • Experience with observability and monitoring tools (such as Datadog or Langfuse) is a plus.

  • German language skills are helpful but not required; the team works in English.

Compensation & Benefits

Salary range: 80,000 to 120,000 EUR annually. Visa sponsorship is not available for this role.

Location

On-site, five days per week in Berlin, Germany. Candidates must be based in Berlin or willing to relocate.

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