AI Solutions Architect – Platform Enablement
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Job Description
AI Solutions Architect specializing in platform enablement at Compass UOL. Leading technical enablement and solution architecture for AI platforms.
Responsibilities:
- Lead technical enablement for engineering and product teams in the use of the IARA platform;
- Lead the adoption of components for developing and deploying AI agents at scale;
- Coordinate and execute migrations of legacy AI solutions to the new platform;
- Systematically identify bugs, documentation gaps and adoption barriers, proposing and tracking resolutions;
- Produce high-quality technical materials: guides, reference architectures, runbooks and code samples;
- Translate community feedback into actionable inputs for product and engineering teams;
- Serve as the technical authority and point of contact between the platform and its consumer teams;
Requirements:
- Proven experience with AI/ML platforms in production within large enterprise environments;
- Deep knowledge of AI agents, LLMs and workflow orchestration patterns;
- Background in technical enablement, developer advocacy or AI solution architecture;
- Ability to produce reference technical documentation and lead knowledge-transfer sessions with engineering teams;
- Full autonomy to identify issues, propose solutions and execute without requiring direction;
- Experience with AWS, Azure or GCP in the context of ML/AI platforms;
- Hands-on expertise with agent frameworks: LangChain, LangGraph, CrewAI, AutoGen or similar;
- Experience with MLOps platforms (MLflow, Vertex AI, SageMaker, Kubeflow);
- Previous experience at large banks, fintechs or technology companies with a platform-oriented culture;
- Experience in product environments with agile squads and short delivery cycles;
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