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.
qlub is scaling fast across markets worldwide, and we look for people who take real ownership of their work.
Who We Are Accenture Song is the world’s largest tech-powered creative group.
Reusable data preparation building blocks & ML‑ready pipelines: Develop, maintain and enhance standardized pipeline patterns, templates and
We are looking for a Lead Solution Architect focused on Generative AI to support our EMEA Emerging Digital Natives and Startups business uni
Wir schreiben dir, sobald eine neue geprüfte Stelle dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
Abmelden mit einem Klick, jederzeit. Keine Weitergabe an Dritte.
Train and deploy ML models for retrieval, reranking, and search relevance, such as embedding models and cross-encoders, in production - Deve
Baut die interne Agenten-Plattform Midnight Clue, verantwortet Evals, Tracing und Guardrails und berät Teams zur Agenten-Entwicklung.
We are looking for a Senior AI Engineer to own and scale the AI layer of one of our core D2C subscription products.
Based on-site at our location in Linz, Austria, you will join our team to build the autonomous systems that reshape how Bosch Power Solutions works.
Du berätst zu KI-Strategien für den digitalen Arbeitsplatz: Use Cases identifizieren, bewerten und in eine Roadmap überführen Du konzipierst
Als AI Solutions Architect gestaltest du die strategische und technologische Weiterentwicklung Künstlicher Intelligenz in den IT-Services de
Als AI Engineer entwickelst und implementierst du innovative KI-Lösungen auf Basis moderner Large Language Models (LLMs) und begleitest dere
Strategische Ausrichtung der divisionalen Data-, AI- und Cloud-Landschaft sowie Entwicklung einer mehrjährigen Roadmap im Einklang mit der K
Erforderliche Skills & Erfahrungen F ull Stack Development AAWU18 technisch und funktional weiterentwickeln neue Features Fullstack umsetzen
Implement agent features and integrations in production codebases – APIs, websockets, tool-calling workflows – following established architecture patterns.
Build the agent runtime. Sandboxed execution, tool orchestration, memory, the closed loop where the agent checks its own work.
Azure-Cloud-Ressourcen, insbesondere API Management, Foundry, OpenAI, AI Search und Document Intelligence, sowie Kubernetes-basierte Anwendu
& Verantwortlichkeiten Entwicklung und Implementierung von AI- und Agenten-Lösungen von der Idee bis zum produktiven Einsatz Konzeption mode
Die Sparda-Bank Hannover ist eine genossenschaftliche Bank.
Delivery-Verantwortung: Schnelle Produktivsetzung, hohe Qualität und Kundenmehrwert sicherstellen (inkl.
Entwickelt Features im ERP-Kernprodukt und in Paula, dem AI-Produkt, von Konzept bis Produktion und verantwortet sie danach.
Als Creative AI Lead (m|w|d) übernimmst Du eine zentrale kreative Rolle in unserem wachsenden AI-Bereich.
Baut Power-Automate-Automatisierungen und Copilot-Use-Cases in M365, entwickelt interne Assistenten und schult Kunden im Prompting.
Verantwortet digitale Innovationsideen von der Anforderungsaufnahme bis zum Rollout, inklusive Robotik-/LIMS-Anbindung und KI-Schulungen in 14 Ländern.
Was du bei uns machst Technische Umsetzung beim Kunden: Architektur, Integration und Inbetriebnahme von KI-Lösungen (LLMs, RAG, Agentic AI,
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.
Interesse an dieser Position?
Die vollständige Anzeige und das Bewerbungsformular liegen beim Arbeitgeber.
Zur OriginalanzeigeKI in bestehende Software und Abläufe bringen: Agenten, RAG-Systeme, Schnittstellen, automatisierte Arbeitsketten.