Senior AI Engineer (Forward Deployed)

As a Senior AI Engineer (Forward Deployed), you are responsible for the hands‑on implementation of AI‑ and data‑driven solutions at domain depth .
You translate business processes, decision logic, and data flows into robust, scalable systems — ranging from agentic AI workflows to classical data‑engineering components (e.g. data layers on Databricks).
This role is hands‑on, AI‑first, and delivery‑focused , with strong ownership for technical quality, structure, and correctness .
Responsibilities
Domain Understanding

- Understand and structure business processes, decision logic, and data relationships .

- Challenge assumptions with customers and stakeholders.

- Translate complex domain logic into clear, implementable solutions .
AI & Data Solution Implementation

- Design and build agentic AI systems (agents, orchestration, tools, context, decision logic).

- Build and evolve data‑engineering components (data layers, models, pipelines, semantic layers).

- Combine agentic and data‑driven approaches into end‑to‑end solution flows .

- Apply structured LLM orchestration, retries, fallbacks, and guardrails where appropriate.
Hands‑On Engineering & Quality

- Actively implement core system logic (not a design‑only role).

- Use AI tools to accelerate development, testing, documentation, and iteration.

- Ensure maintainability, observability, and production readiness .

- Take responsibility for reliability, monitoring, and cost awareness .
Customer & Team Collaboration

- Lead technical domain workshops and solution sessions.

- Work directly with customers at working level.

- Collaborate closely with Engineering Manager, Cloud AI Architect, and QA.

- Contribute to architecture decisions and shared delivery ownership.

What We’re Looking For
Core Profile

- Very senior, hands‑on engineer in AI and/or data engineering .

- Strong AI‑first mindset with sound judgment on when not to use an LLM.

- Solid engineering practice with Git and CI/CD (Azure DevOps, GitHub, GitLab).

- Production mindset: reliability, observability, security, and cost control .

- For Candidates based in Germany. German and English business level proficiency
AI / LLM Engineering

- Experience with structured LLM orchestration (tool calling, schema‑validated outputs).

- Experience designing multi‑agent systems (orchestrator + specialized agents).

- Ability to handle retries, fallbacks, and guardrails .
Backend & System Engineering

- Strong Python skills (ideally FastAPI, async IO, Pydantic).

- Experience building production APIs (errors, retries, timeouts, logging).

- Clear contract design and integration of multiple external systems.
Data & Cloud

- Strong experience with Azure and Databricks (Lakehouse) .

- Solid fundamentals in Spark and Delta Lake .

- Experience operating systems in enterprise Azure environments (e.g. Managed Identity, Key Vault, monitoring, basic networking).
System Thinking

- Can design agent orchestration flows , state handling, and sessions.

- Thinks about latency, tool‑call minimization, and operational constraints .