We are seeking a versatile and strategic AI Solution Delivery Lead/Program manager to bridge the gap between business strategy and technical execution. You will act as a consultant to business stakeholders to qualify ideas and a technical authority to engineering teams to ensure architectural integrity. Your mission is to take a concept from a business spark through rigorous estimation and architectural design, ultimately overseeing a high-quality delivery through QA and deployment.
Core Responsibilities
Required Skills & Qualifications
Business Partnership & Strategy (The Solutioning Phase)
Idea Qualification: Act as the primary point of contact for business units to gather specs and visionary ideas. Evaluate technical feasibility and business value early in the lifecycle.
Requirements Synthesis: Translate ambiguous business asks into concrete functional and non-functional requirements (scalability, security, performance).
Trade-off Analysis: Facilitate Build vs. Buy decisions and conduct architectural trade-off sessions (e.g., speed-to-market vs. long-term technical debt).
Estimation & Budgeting: Provide high-level T-shirt sizing and detailed level-of-effort (LOE) estimates to help business stakeholders prioritize the roadmap.
Technical Architecture & Governance
Blueprint Design: Create end-to-end architectural designs, including system integrations, data flows, and infrastructure requirements.
Decision Authority: Own the selection of the tech stack and frameworks, ensuring alignment with enterprise standards.
Technical Debt Management: Balance immediate project needs with the long-term health of the system architecture.
Program & Execution Management
Lifecycle Oversight: Manage the end-to-end program roadmap, identifying critical path dependencies across multiple technical teams.
Development Steering: Provide technical leadership to the engineering team. Conduct architecture reviews and unblock developers on complex implementation hurdles.
Quality Assurance & Validation: Work with QA leads to define the testing strategy, ensuring that the specs gathered at the start are the realities delivered at the end.
Risk Mitigation: Identify technical and project risks early (e.g., resource gaps, integration bottlenecks) and drive mitigation plans.
Architecture Excellence: Proven experience in designing scalable distributed systems, microservices, or cloud-native architectures (AWS/Azure/GCP). atleast 3 end to end lifecycle pojects in AI
Strategic Thinking: Ability to see the big picture and explain complex technical concepts to non-technical C-suite executives.
Agile Program Mastery: Expert knowledge of SDLC methodologies (Scrum, Kanban, SAFe) and tools (Jira, Confluence, Lucidchart).
Financial Acumen: Comfort with cost-benefit analysis and managing project budgets/allocations.
Experience: 15+ years in technology, with at least 4 years in a leadership role that combined technical design with project/program delivery. deep expertise in AI architectures and beginning of career with distributed technologoes ( java or .net or laternate)
