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# Forward-Deployed Engineer

- **Company:** NTT DATA Deutschland GmbH
- **Location:** Rosenheim, Germany (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Integration Architecture, Microsoft Azure, Cloud Computing, Information Engineering, Python (Programming Language), Machine Learning, OpenAI, Cloud Services, Tensorflow, Software Engineering, Systems Integration, TypeScript, Workflow Management Systems, Data Processing, Google Cloud, Pytorch, LangChain, ReactJS, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Snowflake, Llamaindex, Agentic-AI, Fastapi, Machine Learning Operations, Google Gemini, Databricks, Programming Languages
- **Published:** October 7, 2026
- **Apply:** https://www.arbeitsagentur.de/jobsuche/jobdetail/19913-3044911791151201-S

## About the Role

5+ years of experience in software engineering, AI engineering, data engineering, ML engineering, solution engineering, technical consulting, or related hands-on technical roles.

 - 2+ years of experience building or deploying AI, ML, GenAI, LLM, RAG, agentic AI, data science, or automation solutions.
 - Hands-on experience with programming languages and frameworks such as Python, JavaScript/TypeScript, FastAPI, Flask, React, LangChain, LlamaIndex, PyTorch, TensorFlow, or similar technologies.
 - Experience integrating APIs, data sources, model providers, workflow tools, and cloud services into working demos or prototypes.
 - Working knowledge of responsible AI, security, data handling, privacy, and enterprise deployment considerations.
 - Bachelor's degree or equivalent work experience.
 - Fluency in German and English

Preferred Skills:

 - Experience with OpenAI, Anthropic, Mistral, Google/Gemini, Azure, AWS, GCP, Databricks, Snowflake, vector databases, model registries, and MLOps/LLMOps tooling.
 - Experience working directly with clients, sales teams, or product teams to rapidly prototype solutions under ambiguous conditions.
 - AI/ML, cloud, data engineering, or software engineering certifications.
 - Strong technical curiosity, client empathy, communication, bias for action, collaboration, and ability to explain complex technical concepts clearly.
 - Ability to travel as required for client and internal engagements.

## Description

Rapidly build demos, prototypes, proofs of concept, and MVPs that bring AI use cases to life for clients and account teams.

 - Translate client problems into working technical concepts using models, agents, data, workflows, APIs, integrations, and user experience patterns.
 - Support discovery workshops, executive demos, technical deep dives, proof-of-value sessions, and partner enablement activities.
 - Partner with Solution Architects to ensure prototypes align to scalable architecture, delivery paths, security expectations, and operational requirements.
 - Work with ecosystem partners to showcase differentiated capabilities across OpenAI, Anthropic, Mistral, Google/Gemini, cloud, data, and enterprise platforms.
 - Package prototypes into reusable assets, demo scripts, technical collateral, setup guides, reference architectures, and handoff materials.
 - Validate technical feasibility, data dependencies, integration complexity, user experience assumptions, and implementation risks early in the sales cycle.
 - Help accelerate opportunity conversion by making AI solutions concrete, credible, and client-specific.
 - Contribute lessons learned, reusable code, prompts, agent patterns, and implementation guidance back into the global FDE knowledge base.

Success Measures:

 - Pursuit deal volume, measured as total TCV value of AI deals where the FDE supported.
 - Pursuit win rate for AI deals where the FDE supported.
 - Prototype-to-pipeline conversion, measured by demos, prototypes, or POCs that convert into qualified pipeline, funded POCs, or downstream implementation work.
 - Utilization, reuse of technical assets, demo quality, and stakeholder feedback.