🚀 Become our new Forward Deployed Engineer (m/f/d)
As a Forward Deployed Engineer (m/f/d), 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.
Your Responsibilities
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.
- 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.
What We’re Looking For
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 DevOps, GitHub, or GitLab).
- 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.
- 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.
- Experience with modern Python frameworks and tooling, ideally including FastAPI, async IO, and Pydantic.
- 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.
- Experience operating solutions in enterprise Azure environments, including topics such as Managed Identity, Key Vault, monitoring, and basic networking.
- Experience with scalable deployment and integration of AI workloads in cloud environments.
- Experience with Databricks is a plus.
System Thinking
- Ability to design end-to-end AI solution architectures, including orchestration, session/state handling, and system boundaries.
- Thinks beyond models: understands platform constraints, integration challenges, and operational requirements.
- Considers latency, resilience, observability, and tool-call minimization from day one.
Why Join Us?
- Exciting AI projects – work with cutting-edge technologies across Azure, OpenAI, Databricks, and more.
- High-performance culture – we are looking for doers who want to create real impact.
- Fast learning and career growth – benefit from top-tier training, certifications, and hands-on exposure to advanced AI delivery.
- Innovative company culture – we value hands-on execution, team spirit, and AI-driven excellence.
- Broad ecosystem – we work closely with partners, startups, and a strong network across the AI and cloud landscape.