AI​/ML Delivery Manager

We are looking for a  Technical Delivery Manager (TDM)  to own end-to-end program management for our AI/ML engagements — spanning ML model development, training and fine-tuning, LLM-based solutions, data pipelines, model evaluation, and broader AI/ML workflows.
This role is the  single point of contact (SPOC)  for clients and internally coordinates across CXO’s, practice heads, engineering, hiring, operations teams. The TDM acts as the  orchestrator  of the entire delivery engine, ensuring that what clients expect and what gets delivered stay tightly aligned at every stage, while proactively identifying and resolving risks before they become issues.

Key Responsibilities
1. Program & Delivery Management
Own the end-to-end delivery roadmap for AI/ML programs, including ML model development, training/fine-tuning, LLM implementations, and model evaluation work streams.
Translate client requirements and business goals into structured delivery plans, milestones, and success metrics.
Track scope, timelines, budgets, and resourcing across multiple concurrent AI/ML projects; proactively flag slippages and drive corrective action.
Establish and maintain governance cadences (status reviews, steering committee updates, sprint/iteration reviews) across all active engagements.
2. Client & Stakeholder Management
Serve as the  single SPOC  for clients — managing relationships from day-to-day points of contact through to CXO-level stakeholders.
Run regular client check-ins, business reviews, and escalation calls; present delivery status, risks, and outcomes.
Ensure client expectations are clearly captured, documented, and continuously validated against what is actually being built and delivered — closing any gaps before they surface as dissatisfaction.
Build trusted advisor relationships that support account growth and renewal.
3. Cross-Functional Orchestration
Act as the connective tissue between  practice heads, engineering teams, hiring/talent acquisition, and operations , ensuring everyone is working off the same delivery plan and priorities.
Coordinate staffing and hiring pipelines with TA/HR to ensure the right talent is available in time for project ramp-up.
Work with practice/technical leads to validate solution approaches, technical feasibility, and effort estimates before commitments are made to clients.
Partner with operations on resourcing, utilization, invoicing/billing milestones, and contractual compliance.
4. Risk, Quality & Proactive Issue Management
Proactively identify delivery risks (technical, resourcing, scope, timeline) early and drive mitigation plans before they escalate.
Anticipate client concerns based on program signals (e.g., slipping milestones, performance issues, resourcing gaps) and act ahead of formal escalation.
Own issue/escalation management end-to-end — coordinating the right internal teams to resolve problems quickly and communicating transparently with clients throughout.
Drive continuous improvement in delivery processes, templates, and playbooks based on lessons learned across engagements.
6. Reporting & Governance
Maintain accurate, real-time visibility into program health for internal leadership and client stakeholders.
Prepare and present executive-level dashboards and reviews to both client and internal leadership.
Ensure contractual SLAs, deliverable timelines, and commercial commitments are tracked and met.
Required Skills & Experience
8+ years of experience in  technical program/delivery management , with at least 2–3 years specifically managing  AI/ML, data science, or data engineering programs .
Graduate in engineering/Technology/Data Science from Tier 1 institute.
Demonstrated experience being the  primary client-facing SPOC  for enterprise or CXO-level stakeholders.
Strong…