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deepset

Provides NLP AI tooling for enterprises

Forward Deployed Engineering Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeBerlin, Germany

About the Job

Requirements

  • Experience leading customer-facing engineering, professional services, or delivery teams in enterprise software, AI, or infrastructure.
  • Strong coaching instincts and the ability to develop engineers and build high-trust teams.
  • Technical depth in retrieval-augmented generation (retrieval, embeddings, re-ranking, and evaluation), cloud and self-hosted deployments, model optimization, application programming interfaces, integrations, and identity and access management/security fundamentals.
  • Commercial awareness of how scope, staffing, and execution affect utilization, revenue, and margin.
  • Clear written and verbal communication with technical and executive audiences, and comfort with ambiguity in a remote-first setup.

Responsibilities

  • Own team health and culture across the Advisory, Builder, Operating, and Support Forward Deployed Engineering profiles, creating a safe space for hard questions and enabling engineers to share patterns instead of working in silos.
  • Run 1:1s and career conversations so every Forward Deployed Engineer understands their standing and development opportunities.
  • Build the hiring and onboarding pipeline for a remote-first, asynchronous team.
  • Clear blockers quickly and escalate unresolved blockers before they become delivery risks.
  • Assign the appropriate Forward Deployed Engineering profile to each engagement and deliver against team utilization targets while protecting against burnout and idle capacity.
  • Review architecture and solution decisions across retrieval-augmented generation pipelines, retrieval quality, deployment topology, and production operations to maintain the technical bar.
  • Deliver engagements within scope and plan, follow delivery processes, and own resolution of customer escalations.
  • Partner with the Delivery Lead and Value Engineers on scope, feasibility, and staffing, with clear ownership at each handoff.
  • Feed field insights to Product and Engineering and build reusable patterns that reduce custom work.

Desired Qualifications

  • Experience running services or delivery within a SaaS or platform company transitioning to enterprise and self-hosted deployments.
  • Experience with OKR frameworks and squad-based delivery organizations.
  • Familiarity with agent-based systems, large language model platforms, and AI-native engineering tools.

About the Company

deepset

Provides NLP AI tooling for enterprises

Deepset builds tools for developers to create production-ready AI and NLP systems. Its Haystack open-source Python framework lets you build pipelines for retrieval-augmented generation, intelligent document processing, and semantic search, and it is model- and vendor-agnostic with integrations to providers like OpenAI, Mistral, Anthropic, and Cohere. On top of Haystack, Haystack Enterprise Platform offers a SaaS for prototyping, deployment, monitoring, and governance with options for cloud, on-premise, or air-gapped environments. The company differentiates itself by pairing a flexible open-source framework with enterprise-grade lifecycle tools and deployment flexibility, serving industries from finance to government; its goal is to help organizations scale AI that understands large data sets.

Company size
51-200
Company stage
Early VC
Total funding
$45.6M
Headquarters
Berlin, Germany
Founded
2018

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