Description
Join our growing Roland Berger AI Lab as the technical backbone for designing secure, scalable (Gen)AI systems.
In this dual role, you will support both our internal transformation and client projects, guiding consulting teams and their clients in building future-proof target architectures for generative AI, including AI agent applications.
You will translate business goals into Enterprise and Solution Architectures, derive Target Architectures from reference patterns, and guide delivery teams from PoV to production.
You will own cross-cutting concerns - identity, data, observability, reliability, cost – you will lead design reviews, architecture decision records (ADRs), and guardrails.
Partnering with Backend, DevOps, AI Engineers, and Product core teams, you will ensure agentic/LLM components, services, and data flows form a coherent platform.
QUALIFICATIONS:
- Degree in Computer Science, Engineering, or equivalent experience
- 6+ years of experience in architecting cloud software, with a proven track record of delivering production systems
- Expertise in Enterprise Architecture and Solution Architecture, with clear artifacts and governance practices
- Ability to derive a Target Architecture from reference designs and constraints
- Strong understanding of non-functional requirements and guardrail implementation: security, observability, performance, reliability and cost
- Proficiency in cloud and hybrid architectures (Azure, AWS, GCP): networking, IAM, data, secrets, policies, and private endpoints
- Experience with MCP architecture and integration: designing MCP server topology, capability schemas, tool gating/permissions, auditing and tracability
- Familiarity with patterns for agentic/LLM systems such as tool-calling, orchestration, evaluation loops and finetuning pathways
- Expertise in API and integration architecture (REST, GraphQL, events), data contracts, versioning, and resilience
- Excellent communication skills in English
- Good development expertise with at least one programming language
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