deepset

1 day ago

Product Engineering Tech Lead

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Own deepset’s serverless execution and streaming runtime layer that powers enterprise AI applications. Architect durable, concurrent execution for pipelines and agents, ensuring identical behavior across serverless and deployed services. Lead the team and set technical direction, while making reliability provable through observability, metering, alerting, and incident response. Build a platform that keeps long-lived connections and autonomous workloads running reliably for hours.

Location: Berlin

Workplace: Remote

Employment Type: Full time

Job Function: Administration & Executive Assistance

Seniority: Sr. Manager level

Key Responsibilities

•Own the serverless execution platform, architecting durable, concurrent execution for pipelines and agents so long-running workloads stay alive through failures and deploys.
•Own streaming and long-lived connections, ensuring backpressure, graceful shutdown, and reconnect behavior for conversational and agentic workloads.
•Lead the team and define technical direction, translating product strategy into an architecture that holds up under enterprise load.
•Make reliability provable by owning observability and metering, including tracing, alerting, and per-customer cost and usage visibility.
•Own on-call and incident response, closing the loop between what you build and what you operate.

Pay and Benefits

Equity and Bonus:Equity

Perks:Remote WorkPaid LeaveEquityLearning Budget

Key Requirements

•Builder and founder mindset: you have started things, shipped them, and owned outcomes, with startup/founder experience as a strong signal.
•Built and operated systems on Kubernetes in production and understand how to work from the ground up on new product work.
•Experience with durable, fault-tolerant execution including retries, failover, durable state, and human-in-the-loop.
•Hands-on serverless and function platforms at scale (e.g., Knative, KEDA, OpenFaaS, Fission), including cold start and per-request isolation.
•Comfortable in Python and infrastructure as code (e.g., Terraform) in a cloud-native stack.

Experience:KubernetesServerlessStreamingDurable executionAI/LLM

Skills:Builder mindsetOperator instinctTechnical leadershipReliability focusProblem ownership

Tech Stack:PythonKubernetesKnativeKEDAOpenFaaSFissionTerraformServer-sent eventsWebsocketsHaystack

Company Brief

deepset

Builds production-ready NLP and semantic search solutions for enterprises, authoring the open-source Haystack framework and offering managed Deepset Cloud and services to deploy, search, and extract knowledge from large text collections.

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Growth Stage Startup

Funding: Series A

Headquarters: Berlin, Germany

Founded: 2019

Website LinkedIn

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deepset

1 day ago

Product Engineering Tech Lead

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Berlin

Workplace: Remote

Employment Type: Full time

Job Function: Administration & Executive Assistance

Seniority: Sr. Manager level

Key Responsibilities

•Own the serverless execution platform, architecting durable, concurrent execution for pipelines and agents so long-running workloads stay alive through failures and deploys.
•Own streaming and long-lived connections, ensuring backpressure, graceful shutdown, and reconnect behavior for conversational and agentic workloads.
•Lead the team and define technical direction, translating product strategy into an architecture that holds up under enterprise load.
•Make reliability provable by owning observability and metering, including tracing, alerting, and per-customer cost and usage visibility.
•Own on-call and incident response, closing the loop between what you build and what you operate.

Pay and Benefits

Equity and Bonus:Equity

Perks:Remote WorkPaid LeaveEquityLearning Budget

Key Requirements

•Builder and founder mindset: you have started things, shipped them, and owned outcomes, with startup/founder experience as a strong signal.
•Built and operated systems on Kubernetes in production and understand how to work from the ground up on new product work.
•Experience with durable, fault-tolerant execution including retries, failover, durable state, and human-in-the-loop.
•Hands-on serverless and function platforms at scale (e.g., Knative, KEDA, OpenFaaS, Fission), including cold start and per-request isolation.
•Comfortable in Python and infrastructure as code (e.g., Terraform) in a cloud-native stack.

Experience:KubernetesServerlessStreamingDurable executionAI/LLM

Skills:Builder mindsetOperator instinctTechnical leadershipReliability focusProblem ownership

Tech Stack:PythonKubernetesKnativeKEDAOpenFaaSFissionTerraformServer-sent eventsWebsocketsHaystack

Company Brief

deepset

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Growth Stage Startup

Funding: Series A

Headquarters: Berlin, Germany

Founded: 2019

Website LinkedIn