15 hours ago
Kronberg, GermanyStaff+
Responsibilities
- Design, build, and ship production-grade AI applications, including custom agents, LLM-powered workflows, MCP servers, sub-agents, and agent skills, within client environments.
- Own full-stack delivery across backend logic, API integrations, frontend surfaces, cloud infrastructure, and enterprise systems integration.
- Move AI concepts from rapid prototypes to production deployments while maintaining enterprise-grade rigor.
- Integrate AI capabilities with client APIs, data pipelines, identity systems, and enterprise tooling.
- Monitor, debug, optimize, and manage incidents for deployed systems until stability and handover are achieved.
- Translate complex AI behaviors into transparent and controllable user experiences in collaboration with designers.
- Scope ambiguous client problems, communicate technical trade-offs, and present architecture to engineering and executive audiences.
- Document reusable architectures and deployment patterns, run workshops and code-with sessions, and transfer capability to client teams.
- Feed client and production insights back into the engineering practice and contribute to offering development and go-to-market thinking.
Requirements
- Extensive experience engineering and delivering production software, with significant client-facing, consulting, or Forward Deployed Engineering experience.
- Demonstrated experience shipping AI-native systems such as LLM-powered applications, agentic workflows, RAG pipelines, or multi-agent orchestration into production.
- Strong backend engineering skills in Python and proficiency in at least one of TypeScript or Java, with the ability to build frontend surfaces when needed.
- Experience deploying to AWS, GCP, or Azure using CI/CD pipelines, Terraform or Helm, Kubernetes, and Docker, while owning production operations end to end.
- Strong data engineering fundamentals, including pipelines and structured and unstructured datasets, with the ability to reason about data quality.
- Experience designing and deploying enterprise AI applications involving agentic workflows, RAG pipelines, vector databases, embeddings, and semantic search.
- Ability to scope ambiguous real-world problems, develop working software quickly, and operate autonomously in unfamiliar client environments.
- Strong cross-functional communication skills, including design workshops, executive presentations, documentation, and client relationship building.
- Fluency in English and ability to embed with DACH clients and facilitate workshops.
- Bonus experience with MCP servers, sub-agents, agent skills, custom connectors, production LLM evaluation harnesses, solutions engineering, technical consulting, design systems, responsible AI, or production AI portfolios.
Benefits
- Meaningful career development and flexible working between client engagements.
- Opportunity to work directly inside client organizations across Central and Eastern Europe and shape the engineering practice through field experience.
- Inclusive and diverse culture with responsibility for creating and sustaining an inclusive environment.
Categories
Forward Deployed
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.