Forward Deployed Engineer (Applied AI) – Europe at act-digital-deutschland – Mobil | Jobyssey

Your role

As a Forward Deployed Engineer, you will work closely with our clients to turn complex business challenges into production-ready AI solutions.

Location: Germany, with regular presence at client sites in Germany and occasionally elsewhere in Europe

You will take ownership of an applied-AI workstream from end to end: identifying a use case with measurable business value, designing and building AI agents connected to the client’s systems and data, deploying the solution in the client’s environment, and enabling the client’s team to operate it independently.
This is a senior, hands-on engineering role combining:

Production-grade software engineering
Applied LLM and agent engineering
Evaluation and observability
Client-facing consulting and stakeholder communication

You will work as part of a small delivery team, collaborating with a Delivery Manager and senior technical specialists from our international Applied AI unit.

Your responsibilities

Discover and define valuable use cases

Lead data-driven discovery together with the client
Understand operational processes and establish a measurable baseline
Define the target metric and clear acceptance criteria before development begins
Assess whether an AI agent is the right solution or whether a simpler deterministic approach would be more effective
Translate business requirements into a technically achievable workstream

Design and build AI agents

Architect AI agents, including their purpose, scope, decision-making authority, human escalation points, and division of responsibilities
Create executable specifications and evaluation sets that govern development and releases
Build and verify solutions using modern coding agents and development tools
Integrate agents with real enterprise systems through MCP servers and APIs
Connect to environments such as ticketing systems, ERPs, CRMs, legacy databases, and data pipelines
Establish automated evaluations and quality gates in CI/CD workflows

Deploy and operate production systems

Deploy solutions within the client’s cloud, network, security, and compliance environment
Implement tracing, monitoring, alerting, and cost measurement
Monitor latency, quality, drift, and cost per transaction
Apply security principles such as least-privilege access, sandboxing, prompt-injection protection, and auditability
Support technical reviews relating to security, data protection, and production readiness

Enable a sustainable handover

Create clear architecture documentation, runbooks, evaluation suites, and incident playbooks
Train the client’s technical and operational teams
Document known limitations and operational responsibilities
Ensure that the solution can be operated independently by the client
Complete the handover against clear, objective readiness criteria

Communicate with stakeholders

Provide transparent progress reporting in situations with incomplete or changing information
Clearly distinguish between confirmed information, assumptions, risks, and dependencies
Translate technical decisions into business consequences
Communicate challenges early and accompany them with practical options and recommendations

How we work

Metric first: Every workstream begins with a measurable baseline and a business-relevant target.
Production over prototypes: We build operational systems, not isolated proofs of concept.
Handover by design: Solutions are documented and designed so that the client’s team can own and operate them.
Technology-agnostic thinking: We select the appropriate model, framework, and architecture for the problem rather than forcing every use case into one stack.
Close client collaboration: Discovery, delivery, communication, and capability transfer are integral parts of the engineering work.

Your profile

Essential experience

At least five years of software-engineering experience, including responsibility for systems running in production
Strong backend and integration experience, with enough frontend knowledge to deliver a complete solution
Strong Python skills and experience with an additional technology stack, preferably TypeScript or Java
Practical experience using LLMs through APIs in a real application
Experience with prompting, structured output, function or tool calling, and at least one agent framework
Demonstrable experience with systematic evaluation, such as:
- Error analysis using real data
- Failure taxonomies
- Evaluation datasets
- Automated quality gates for releases
Working knowledge of machine-learning and deep-learning fundamentals, including transformers, tokenization, context windows, post-training, and common failure modes
Experience with SQL, data pipelines, ETL processes, containers, and at least one major cloud platform
Customer-facing, consulting, or technical-founder experience
Experience taking responsibility for a technical or business outcome in front of a client or senior stakeholder
Ability to work independently in ambiguous environments and resolve blockers proactively
Clear communication under pressure
Excellent German and English skills at C1–C2 level: You communicate confidently in German with clients and stakeholders, while English is the primary language for technical documentation and collaboration with our international Applied AI team.

Nice to have

Experience operating agent-based or RAG systems in production, including monitoring, evaluation, and cost management
Experience building or consuming MCP servers
Experience designing tools that can be reliably used by language models
Enterprise integration experience involving legacy ERP, CRM, ITSM, or ticketing systems
Knowledge of experimentation methods such as A/B testing and guardrail metrics
Experience supporting security or data-protection reviews for AI systems
Familiarity with the EU AI Act or ISO/IEC 42001
Experience in regulated or industrial environments such as automotive, manufacturing, financial services, or telematics
Experience teaching, mentoring, or enabling other engineers

What this role is not

It is not a prompt-engineering or AI-tool-adoption role
It is not a research or model-training position
It is not a platform role without direct client interaction
It is not a project-management or people-management position
It is not a consulting role focused primarily on presentations or concepts
It is a hands-on engineering role with responsibility for delivering measurable production outcomes

What you can expect

Ownership of technically challenging applied-AI workstreams
Direct collaboration with clients and senior stakeholders
Close cooperation with an international Applied AI team
The opportunity to build AI systems that move beyond prototypes and deliver measurable operational value
A working environment that values engineering quality, transparency, pragmatic decision-making, and sustainable knowledge transfer

Forward Deployed Engineer (Applied AI) – Europe

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