AI Engagement Lead / Solution Architect

Own the solution architecture and the key design decisions across the platform and remain accountable for them with the client.

Guide integration design, including MCP integration patterns and how the AI system connects to the client’’s data and tools.

Learn the client’’s workflow well enough to translate business needs into a sound, practical technical approach.

Define security boundaries and model/tool controls - access limits, guardrails, and human-review checkpoints that keep sensitive outputs correct and controlled.

Provide technical direction to the engineering team on solutioning and system design; align them to a technical roadmap and ensure timely execution.

Delivery Governance & Release Gates:

Establish and enforce release gates - the quality, security, and compliance signoffs required before each release.

Own overall delivery so scope, quality, and timelines are consistently met; manage the big-picture program timeline (releases, phases, go-live plans) using engineering velocity/capacity inputs from the EM.

Ensure delivery decisions reflect cost, ROI, and long-term business impact.

Identify delivery risks, create proactive mitigation plans, and track program health across all milestones.

Ensure robust business-facing documentation - requirements/BRDs/PRDs, implementation plans, and roadmaps.

Client Relationship & Communication:

Lead discussions with the client to shape the AI roadmap and expand into new processes.

Act as the primary point of contact for communication, feedback, and escalations; manage expectations proactively.

Evaluate use-cases for new development and unlock new value for the client.

Participate in the client’’s internal stakeholder meetings to capture, clarify, and consolidate requirements into actionable product needs.

Team Leadership & Coordination:

Drive cross-functional alignment across engineering, product, and client teams.

Remove blockers for client and internal teams through clear communication and effective prioritization.

Conduct regular 1:1s focused on support, delivery alignment, and well-being.

Acknowledge new client requests promptly and partner with the EM to assess feasibility, capacity, and timeline impact before committing.

• 10+ years of overall IT experience.
• 4+ years leading AI/ML or Generative AI solution architecture initiatives.
• Proven experience owning enterprise solution architecture from design through implementation.
• Strong experience with:
• Generative AI
• Large Language Models (LLMs)
• Agentic AI
• LangChain
• LangGraph
• MCP (Model Context Protocol)
• Experience designing AI governance, security, guardrails, and Human-in-the-Loop workflows.
• Strong knowledge of enterprise integration patterns and API architecture.
• Experience with at least one major cloud platform:
• AWS
• Azure
• Google Cloud Platform (Google Cloud Platform)
• Experience working in Agile environments using Jira and Confluence.
• Excellent communication, leadership, and executive stakeholder management skills.

Preferred Qualifications

• Financial Services, Banking, Asset Management, Capital Markets, or Wealth Management domain experience.
• Experience delivering AI transformation programs for Fortune 500 organizations.
• Background in enterprise consulting or digital transformation.
• Experience building AI roadmaps and enterprise modernization strategies.