Endava
Technology
AIArchitect–AgenticSystems(LLM&Multi-AgentSolutions)
Neural analysis suggests this role is
optimal for mid candidates.
“AI Architect – Agentic Systems (LLM & Multi-Agent Solutions) at Endava. Skills: Agentic Systems, LLM, Multi-Agent Solutions, Software Architecture. Design multi-agent architectures. Define LLM agent interaction”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
Software architecture background, Distributed systems background, Hands-on LLM applications, Complex workflows experience, Orchestration systems experience, RAG architectures understanding, Retrieval optimization understanding, Retrieval quality understanding, LLM fundamentals understanding, Transformer architecture grasp, LLM training behavior understanding, NLP concepts familiarity, Model behavior reasoning, Multi-agent frameworks experience, Generative AI lifecycle platforms experience, Cloud experience, Python coding skills, AI enterprise systems integration
Nice to Have
LangChain experience, Semantic Kernel experience, Agent Framework experience, CrewAI experience, Custom agent framework experience, Amazon Bedrock experience, Google Vertex AI experience, Azure AI Foundry experience, MCP protocol familiarity, UCP protocol familiarity, A2A protocol familiarity, AP2 protocol familiarity, Tool use familiarity, Function calling familiarity, Agent coordination patterns familiarity, Memory management familiarity, Context management familiarity, AWS experience, Azure experience, GCP experience
What You'll Do.
Design multi-agent architectures
Define LLM agent interaction
Establish observability
Establish feedback loops
Establish controls for agent behavior
Define memory strategies
Collaborate with data teams
Collaborate with platform teams
Collaborate with engineering teams
Integrate AI into core systems
Guide teams on best practices
Train teams on best practices
How You'll Work.
Team & Collaboration
Data teams; Platform teams; Engineering teams
Full Job Description
Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses. From prototype to real-world impact - be part of a global shift by doing work that matters. We are looking for a highly skilled and hands-on AI Architect to design and lead the implementation of multi-agent (agentic) systems in enterprise environments. This is not a prompt engineering or chatbot role. We are focused on building production-grade AI systems, where multiple agents collaborate, reason, and execute complex workflows integrated with real business processes. Key Responsibilities * Design multi-agent architectures (task decomposition, orchestration, coordination patterns) * Define how LLM-powered agents interact with: * Enterprise data platforms * APIs and tools * Operational workflows * Lead agentic systems from PoC to production with model, cost, security, privacy, and responsible AI guardrails * Establish observability, tracing, feedback loops, and controls for agent behavior * Define memory strategies (short-term, long-term, contextual grounding) * Collaborate with data, platform, and engineering teams to integrate AI into core systems * Guide and train teams on best practices for scalable and reliable AI systems ## Qualifications What We’re Looking For Core Experience * Strong background in software architecture and distributed systems * Hands-on experience building complex LLM-based applications * Experience designing complex workflows or orchestration systems * Solid understanding of RAG architectures, retrieval optimization, and retrieval quality LLM & AI Foundations * Strong understanding of Large Language Model (LLM) fundamentals, not just usage * Solid gra
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