AI Solution Architect

We are looking for an AI Solution Architect to join our team. This role is a great fit for someone who enjoys guiding teams through the practical realities of building and validating AI-driven systems. You'll work closely with both technical and business stakeholders, helping bridge the gap between emerging AI capabilities and real-world application. If you're motivated by hands-on experimentation paired with clear, structured advisory work, this position offers a strong opportunity to contribute meaningfully Responsibilities Provide practical guidance on agent development, including model and tool selection, deployment approaches, evaluation methods, and ongoing monitoring Evaluate RAG/GraphRAG approaches, chunking strategies, retrieval methods, re-ranking techniques, and vector-store options alongside the architect, implementing only the approach confirmed in the agreed validation plan Define golden datasets, quality thresholds, and regression tests using approved, controlled test data that excludes personal information Build the agreed nonproduction agent workflow in Python when readiness and capacity allow, including its associated tools and a single API/system integration Test success paths, error handling, and permission scenarios, documenting quality outcomes, usage costs, limitations, and any remaining gaps Draft a workflow deployment and reuse blueprint along with engineering playbooks, covering semantic/context handling, identity management, permissions, and autonomy controls Explain AI-assisted development approaches and agent tooling decisions clearly to business users, engineering teams, and the AI team Document practical examples and lead walkthroughs, with advisory work covering production-grade lifecycle guidance, while actual production deployment and ongoing operations fall outside this scope Requirements A minimum of 5 years of relevant experience At least 2 years in Senior, Lead, Manager, or Owner-level roles Proven track record managing engagements for teams of 5 or more full-time employees Hands-on experience in AI agent development, including design, deployment, and iteration Working knowledge of Amazon Web Services for supporting cloud-based AI solutions Experience in GenAI agent evaluation and testing to ensure quality, reliability, and performance Strong proficiency in Python for building and testing AI-driven workflows Solid understanding of REST APIs for enabling system and tool integrations Practical experience with Retrieval-Augmented Generation (RAG) for grounding AI outputs in relevant data Professional proficiency in English (C1) Nice to have Experience with AWS Bedrock for building and deploying generative AI solutions Familiarity with Amazon Bedrock AgentCore for supporting agent orchestration and management Background working with MuleSoft for enabling system integrations Relevant certification, which would be considered a valuable addition to your qualifications