Experience: 8+ years of experience in a technical role such as Solution Architecture, Enterprise Architecture, or senior-level Software Engineering, with at least 3+ years in a client-facing capacity.
Architectural Expertise: Proven ability to design and document complex, distributed, and scalable software systems. Deep understanding of microservices, event-driven architecture, and MCP-first design principles.
AI/ML Acumen: Strong foundational knowledge of modern AI concepts, including Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and vector databases (e.g., Qdrant, Pinecone, Weaviate).
Data Integration: Hands-on experience designing data pipelines and integrating with diverse enterprise data sources (e.g., relational databases like PostgreSQL, unstructured document stores like SharePoint, APIs, and data warehouses).
Cloud Proficiency: Experience architecting solutions on a major cloud platform.
Technical Foundation: Proficiency in Python is strongly preferred. Familiarity with containerization (Docker) and orchestration (Kubernetes) is essential.
Communication: Exceptional verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
Direct, hands-on experience designing or building systems using agentic AI frameworks (e.g. LangGraph, CrewAI).
Knowledge of semantic web technologies, including ontologies (OWL/RDF) and familiarity with the concepts behind the Model Context Protocol (MCP) or similar advanced agentic architectures.
Experience with modern observability stacks, particularly OpenTelemetry.
Knowledge of enterprise security patterns and identity management systems.
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#J-18808-LjbffrApplication Support Analyst • Cambridge, England, GB
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