Role Overview
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
1. Business Partnership & Strategy (The "Solutioning" Phase)
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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.
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Requirements Synthesis:
Translate ambiguous business "asks" into concrete functional and non-functional requirements (scalability, security, performance).
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Trade-off Analysis:
Facilitate "Build vs. Buy" decisions and conduct architectural trade-off sessions (e.g., speed-to-market vs. long-term technical debt).
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Estimation & Budgeting:
Provide high-level T-shirt sizing and detailed level-of-effort (LOE) estimates to help business stakeholders prioritize the roadmap.
2. Technical Architecture & Governance
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Blueprint Design:
Create end-to-end architectural designs, including system integrations, data flows, and infrastructure requirements.
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Decision Authority:
Own the selection of the tech stack and frameworks, ensuring alignment with enterprise standards.
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Technical Debt Management:
Balance immediate project needs with the long-term health of the system architecture.
3. Program & Execution Management
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Lifecycle Oversight:
Manage the end-to-end program roadmap, identifying critical path dependencies across multiple technical teams.
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Development Steering:
Provide technical leadership to the engineering team. Conduct architecture reviews and unblock developers on complex implementation hurdles.
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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.
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Risk Mitigation:
Identify technical and project risks early (e.g., resource gaps, integration bottlenecks) and drive mitigation plans.
Required Skills & Qualifications
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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
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Strategic Thinking:
Ability to see the "big picture" and explain complex technical concepts to non-technical C-suite executives.
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Agile Program Mastery:
Expert knowledge of SDLC methodologies (Scrum, Kanban, SAFe) and tools (Jira, Confluence, Lucidchart).
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Financial Acumen:
Comfort with cost-benefit analysis and managing project budgets/allocations.
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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)