Agentic AI Architect - Intelligence Engineering (Agentic AI)

Who You’ll Work With At Slalom, we co-create modern technology and software products with clients who are ready to accelerate their digital product development. As a Senior Architect or Architect in Intelligence Engineering, you’ll design and deliver innovative AI/ML and agentic AI solutions as part of intelligent products and automating / re-envisioning human workflows on Amazon Web Services, Azure, and Google Cloud. What You’ll Do 5+ years of software engineering experience building and deploying production systems; experience with machine learning, applied AI, or intelligent software systems is a plus, with 2+ years focused on generative AI, LLMs, or agentic AI systemsHands-on experience designing or building multi-agent systems including agent orchestration, tool integration, and autonomous decision-making workflowsProficiency with at least one agentic AI or workflow framework such asLangGraph,Strands,AutoGen,CrewAI, Semantic Kernel, OpenAI Agents SDK, Google ADK, or similarExperience with RAG architectures including vector databases, embeddings, and retrieval optimization,and context management techniques such as chunking, summarization, and memory handlingExperience developing production-ready solutions on at least one major cloud AI platform, such as AWS Bedrock, Azure AI Foundry/OpenAI Service, GCP Vertex AI/Gemini, or Databricks; experience operating and maintaining production environments is a plusExperience with AI-assisted development tools such as Claude Code, Cursor, Kiro, or similar IDE-based coding agents, including effective use for code generation, refactoring, debugging, and developer workflow accelerationStrong Python development skills; experience withFastAPI, Flask, or equivalent API frameworksExperience building ML or AI systems end to end, including data access, feature or retrieval flows, APIs, testing, deployment, and production supportFamiliarity with evaluation frameworks, tracing, observability, model behavior analysis, and regression testing for GenAI systemsUnderstanding of prompt engineering, LLM fine-tuning, chain-of-thought reasoning, and structured output techniquesRecognized as an authority on at least one technical domain (e.g., Agentic Systems, RAG, Multi-Agent Orchestration) with generalist familiarity across AI/ML techniquesAbility to work across new domains and unfamiliar data structures and lead exploratory analysis when requirements are not fully definedExcellent verbal and written communication skills; ability to lead highly technical presentationsFamiliarity with Agile project delivery(Preferred) Experience with Model Context Protocol (MCP) server development and integration(Preferred) Experience with MLOps/LLMOps pipelines, CI/CD for ML, and model monitoring/observabilityAbout Us

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