Senior Software/AI Engineer
A very strong senior software engineer with deep, hands-on experience building and operating production systems.
A very strong senior software engineer with deep, hands-on experience building and operating production systems.
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Before the detail, here s the challenge you d help us solve.
Wir schreiben dir, sobald eine neue geprüfte Stelle dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
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Shape the future of enterprise AI by designing and governing advanced AI platforms, generative AI ecosystems, and agentic solutions at enterprise scale.
Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
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.
- 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
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 About EggAI Agentic workforces are inevitable. Making them work is our mission.
EggAI is building the engineering methods, operating models, and reusable technology to deploy agentic workforces with the quality and control required for sustained business impact. Working closely with enterprise clients, we design, implement and operate agentic systems that evolve from augmenting individual tasks to autonomously executing end-to-end processes alongside people—resilient, controlled, and scalable. We begin with the client problem, select the technical approach that best serves it, and remain accountable through deployment, adoption, and operations.
Each deployment strengthens the next by turning production learning into reusable capability. We are an experienced, international team working across Europe. We set high standards, take ownership of outcomes, and value clear thinking, candid feedback, and the ability to turn ideas into tangible results.
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