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Senior Software/AI Engineer

Eggai·Germany

Full-time

Posted 2 days ago

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Job details

CompanyEggai
CategoryData & AI
Job typeFull-time
ExperienceSenior / lead (from title)
Work settingOn-site / hybrid (check listing)
LocationGermany
SalaryNot stated
Posted2026-10-30 (2 days ago)
SourceArbeitnow

Requirements

  • 10+ years designing, building and maintaining production systems that real users depend on — clean testable code, sound API and data modelling, and the judgement to know which abstractions are worth it
  • Production AI experience : You have built and operated GenAI systens in production with real users
  • Has owned code in production — deployment, monitoring, on-call or equivalent — and can debug hard problems in live systems: concurrency, performance, data correctness
  • Distributed systems fundamentals : services, queues, retries, idempotency, failure modes, and integrating third-party APIs that are not reliable
  • Databases : schema design, query performance, migrations
  • Operational rigour : meaningful automated testing, useful instrumentation, CI/CD and shipping incrementally
  • Client-facing ability : has delivered against real business requirements and can hold a technical conversation with non-engineers
  • Languages : Python (primary), TypeScript/JavaScript. Strong engineers coming from Go, Java, C#, Rust or similar who are willing to work in Python are in scope
  • Infrastructure : cloud platforms (AWS/GCP/Azure), containerisation

Job description

EggAI · Full-time · Remote (EU & UK)

The Role

A very strong senior software engineer with deep, hands-on experience building and operating production systems. We hire for engineering strength first: people who write good software, reason about failure, and own what they ship.

You will work in a team of 2 to 6 engineers on a client project . Clients come to us because we work at the forefront of AI in the enterprise; you help implement our AI strategy.

AI experience is required. Much of our work involves LLM-powered and agentic systems, and while you may not be working directly on LLMs, you will be working on LLM based systems.

What You'll Do

Build and operate the production systems at the centre of the engagement, end to end — you own what you ship, including after it's reached production

Lead architecture discussions for your part of the system, with the support of the wider team

Take ownership: pick up the ambiguous problem, chase down the answer, and say so when something is going wrong

Work directly with the client's engineers and with our project manager / product owner

Work in a "normal" team rhythm — daily standups, planning, retrospectives, code and design review

What We're Looking For

10+ years designing, building and maintaining production systems that real users depend on — clean testable code, sound API and data modelling, and the judgement to know which abstractions are worth it

Production AI experience : You have built and operated GenAI systens in production with real users

Has owned code in production — deployment, monitoring, on-call or equivalent — and can debug hard problems in live systems: concurrency, performance, data correctness

Distributed systems fundamentals : services, queues, retries, idempotency, failure modes, and integrating third-party APIs that are not reliable

Databases : schema design, query performance, migrations

Operational rigour : meaningful automated testing, useful instrumentation, CI/CD and shipping incrementally

Client-facing ability : has delivered against real business requirements and can hold a technical conversation with non-engineers

Languages : Python (primary), TypeScript/JavaScript. Strong engineers coming from Go, Java, C#, Rust or similar who are willing to work in Python are in scope

Infrastructure : cloud platforms (AWS/GCP/Azure), containerisation

Desired qualities

Depth — you can explain the systems you built and the trade-offs you chose

Balances speed of iteration with production reliability

Clear communicator, in writing as well as in conversation

Learns new domains quickly and deliberately

Interview Process

Introductory call - 30 minutes

Behavioural/Management interview - 60 minutes

Technical interview (choice of walking through own code, live coding, or take home exercise) - 60 minutes

Tags: Engineering

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