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Owns architecture and technical direction for enterprise AI platforms, AWS Quick integrations, and an internal AI Artifact Hub. Leads development of connectors, agents, knowledge retrieval, MCP servers, data pipelines, quality systems, observability, and resilient distributed workflows. Guides Python engineering, architecture reviews, incident response, and cross-functional alignment with security, cloud, enterprise architecture, and AWS teams. Establishes standards for AI evaluation, governance, reliability, and verification-first development.

Build and operate secure AI platform infrastructure on AWS, including connector governance, authentication, integrations, ingestion pipelines, agents, access controls, DLP, observability, cost controls, evaluation frameworks, and feedback APIs. Mentor engineers, guide architecture, collaborate with domain teams and AWS, and support production systems through on-call participation.

Owns technical direction and end-to-end architecture for AWS Quick customization and an internal AI Artifact Hub. Leads development of connectors, agents, knowledge retrieval, data pipelines, MCP integrations, quality evaluation, reliability, observability, and incident response. Guides Python implementation, architecture reviews, enterprise integrations, and cross-functional technical alignment. Establishes engineering standards for AI-assisted development, security, governance, testing, and resilient distributed systems while contributing hands-on to complex platform challenges.

Build and maintain enterprise AI connectors and platform features using Python and AWS. Develop APIs, data pipelines, agent skills, and infrastructure; implement secure integrations, access controls, testing, monitoring, CI/CD, and Terraform infrastructure as code. Contribute to AI evaluation systems, documentation, production support, and on-call operations while learning RAG, embeddings, agent orchestration, MCP, and cloud engineering practices.

Own the architecture and technical direction of AWS Quick customization and Cox Automotive’s AI Artifact Hub. Lead development of connectors, agents, knowledge retrieval, data pipelines, MCP integrations, quality evaluation, reliability standards, and incident response. Guide Python implementation, architecture reviews, cross-functional alignment, and AWS partnership while establishing secure, scalable, spec-driven engineering practices for enterprise AI platforms.

Build and maintain enterprise AI connectors, APIs, data pipelines, agent skills, and platform tooling using Python and AWS. Develop features end to end, implement secure access controls, integrate third-party services, and support AI evaluation systems. Maintain CI/CD pipelines and Terraform infrastructure, monitor production systems, document solutions, and participate in on-call support. Collaborate with senior engineers while developing expertise in RAG, embeddings, agent orchestration, MCP, and responsible AI platform engineering.

Build and govern enterprise AI platform integrations on AWS Quick, including connectors, authentication, ingestion pipelines, agents, access controls, DLP, observability, cost tracking, evaluation frameworks, and feedback APIs. Improve the AI Artifact Hub, ensure reliability and security, mentor engineers, review designs, and collaborate with domain teams and AWS technical staff. Participate in on-call support and guide architecture and engineering standards.

Build and maintain Python-based connectors, APIs, data pipelines, agent skills, and platform tooling for an enterprise AI platform on AWS. Deliver features end-to-end, support MCP integrations, enforce access controls and data safety, and contribute to testing, monitoring, CI/CD, Terraform infrastructure, documentation, evaluations, and on-call operations. Collaborate with senior engineers while developing expertise in RAG, embeddings, agent orchestration, and AI platform engineering.

Build and operate secure AI platform infrastructure on AWS, including enterprise connectors, authentication, monitoring, knowledge ingestion, agents, access controls, DLP, evaluation frameworks, feedback APIs, and observability. The role owns the AI Artifact Hub, supports third-party integrations, improves reliability and cost controls, mentors engineers, contributes to architecture decisions, and collaborates with AWS teams. Participation in an on-call rotation and three days per week in the office are required.

Manages and grows a vehicle finance portfolio within an assigned territory. Builds client relationships, optimizes line-of-credit usage, monitors dealer financial performance, mitigates pre-default risk, supports collections, identifies fraud or noncompliance, and documents activities in Salesforce. The role requires frequent client engagement, financial analysis, negotiation, collaboration with risk and recovery teams, and travel exceeding 25%, including occasional overnight travel.