Forward Deployed Engineer; m​/f​/d

Become our new Forward Deployed Engineer (m/f/d)

As a Senior AI Engineer (Forward Deployed), you will lead the hands‑on implementation of AI‑driven solutions in complex customer environments.

You combine deep expertise in NLP, LLMs, and speech technologies with strong software engineering skills to build robust, scalable, and production‑ready systems. Working closely with customers and internal teams, you translate business processes, decision logic, and data flows into real‑world AI applications — from intelligent assistants and speech‑enabled systems to enterprise‑grade integrations on Azure.

This is a hands‑on, AI‑first, delivery‑focused role with strong ownership of technical quality, scalability, and operational excellence.

Understand the Domain

• Analyze and structure business processes, decision logic, and data relationships.
• Challenge assumptions and refine requirements together with customers and stakeholders.
• Translate complex domain needs into clear, implementable technical solutions.

Build AI Solutions End‑to‑End

• Design and implement AI systems with a strong focus on NLP, LLMs, and speech models
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• Build agentic workflows, orchestration layers, tool integrations, and decision logic.
• Develop end‑to‑end solution flows that combine AI capabilities with backend and platform components.
• Apply structured LLM patterns such as tool calling, schema‑validated outputs, retries, fallbacks, and guardrails.
• Integrate AI services into enterprise environments and production systems.

Own Software Engineering Quality

• Actively implement core application and integration logic — this is not a design‑only role.
• Build maintainable, testable, and production‑ready software in Python.
• Use modern engineering practices to ensure reliability, observability, security, and cost awareness.
• Improve development speed and quality through automation, testing, and AI‑assisted engineering workflows.

Deliver in Customer Environments

• Work directly with customers in workshops, implementation sessions, and delivery phases.
• Drive technical solutioning together with Engineering Managers, Cloud AI Architects, and QA.
• Contribute to architecture decisions while maintaining a strong execution mindset.
• Take ownership of successful deployment and integration in real‑world environments.

Core Profile

• Very senior, hands‑on engineer with strong experience in applied AI and software engineering.
• Strong AI‑first mindset, with sound judgment on when AI — and especially LLMs — should or should not be used.
• Strong ownership mentality and delivery focus.
• Solid engineering practices with Git and CI/CD (Azure Dev Ops, Git Hub, or Git Lab).
• Production mindset: reliability, observability, security, and cost control.
• For candidate based in Germany - business‑level German and English. For Candidate based in Portugal - Business‑level English

AI / Applied ML Expertise

• Strong hands‑on experience with NLP, LLMs, and speech models
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• Experience building production‑grade solutions using LLMs, including structured orchestration, tool calling, and schema validation.
• Experience designing agent‑based or multi‑agent systems.
• Ability to implement retries, fallbacks, guardrails, and monitoring for AI systems.
• Strong understanding of the practical trade‑offs of latency, quality, cost, and reliability in AI applications.

Software Engineering & Integration

• Excellent Python skills.
• Strong experience with parallel and asynchronous programming
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• Experience with modern Python frameworks and tooling, ideally including FastAPI, async IO, and Pydantic
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• Experience building production APIs and integrations, including error handling, retries, timeouts, and logging.
• Ability to design clear service contracts and integrate multiple internal and external systems.
• Strong software engineering fundamentals, including clean architecture, testing, and maintainability.

Cloud & Infrastructure

• Strong understanding of infrastructure and deployment patterns on Azure
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• Experience operating solutions in enterprise Azure environments, including topics such as Managed Identity, Key Vault, monitoring, and basic networking
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• Experience with scalable deployment and integration of AI workloads in…