AI Engagement Lead / Solution Architect | Full Time | Remote (USA)
Lead end-to-end GenAI engagements for Fortune 500 financial-services clients at Turing — one of the world's fastest-growing AI companies. You'll own both the solution architecture and program delivery, from POC through full-scale implementation, while managing client relationships and directing a team of specialist AI/ML and integration engineers.
About Turing
Founded in 2018, Turing accelerates the advancement and deployment of powerful AI systems. With over two million global developers on its Talent Cloud and 900+ clients, Turing partners with leading AI labs and enterprises alike. Its leadership team brings experience from Meta, Google, Microsoft, Stanford, MIT, McKinsey, and more.
About the Role
As the AI Engagement Lead / Solution Architect, you will serve as the single point of accountability for architecture, delivery, and client success. You will set the technical direction, govern releases, and ensure that scope, quality, and timelines are consistently met — leaning on your team of specialists to build deep components.
Key Responsibilities
- Architecture & Technical Accountability: Own the solution architecture and key design decisions; guide MCP integration patterns; define security boundaries, guardrails, and human-review checkpoints; provide technical direction to the engineering team.
- Delivery Governance & Release Gates: Establish and enforce quality, security, and compliance release gates; manage program timelines and milestones; identify and mitigate delivery risks; ensure robust business-facing documentation (BRDs, PRDs, roadmaps).
- Client Relationship & Communication: Act as the primary client contact for communication, feedback, and escalations; shape the AI roadmap; evaluate new use-cases to unlock additional client value.
- Team Leadership & Coordination: Drive cross-functional alignment across engineering, product, and client teams; remove blockers; conduct regular 1:1s; assess feasibility and capacity for new client requests.
Required Qualifications
- 10+ years of professional experience, with 4+ years leading Machine Learning / AI projects and solution design.
- Proven accountable ownership of solution architecture — able to set target architecture and defend key design decisions to senior stakeholders.
- Strong working knowledge of modern GenAI agentic frameworks (e.g., LangChain / LangGraph) and AI integration patterns including MCP (Model Context Protocol).
- Ability to define security boundaries, model/tool controls, and human-in-the-loop checkpoints for AI systems.
- Experience establishing delivery governance and release gates with clear quality, security, and compliance criteria.
- Familiarity with cloud platforms (Azure, GCP, or AWS) and Agile delivery tools such as JIRA and Confluence.
- Excellent communication and stakeholder management skills; entrepreneurial, founder's mindset.
- Nice to have: Exposure to financial-services or asset-management valuation workflows, or other regulated enterprise domains.
