Technical Delivery Manager, AI/ML Programs

Private Advertiser; Central Luzon; On-site; PHP 180,000 - 320,000; Full time

Job summary

Private Advertiser is seeking a Technical Delivery Manager to own end-to-end AI/ML program delivery. You will manage model development, training and fine-tuning, LLM implementations, and data pipelines while aligning client expectations with actual delivery and surfacing risks early.

You will serve as the single point of contact for accounts, collaborate with practice heads, engineering, talent acquisition and operations, and drive governance through reviews and sprint cycles.

Qualifications

• Bachelor's degree in engineering, computer science or a closely related technical discipline.

Responsibilities

• Own end-to-end delivery roadmap for AI/ML programs including model development, training and fine-tuning, LLM implementations and evaluation workstreams.
• Translate client requirements into structured delivery plans, milestones and success metrics.
• Track scope, timelines, budgets and resourcing across multiple projects, flag slippage early and drive corrective action.
• Run governance cadence including status reviews, steering committee updates and sprint/iteration reviews.
• Read and challenge project guidelines, taxonomies, evaluation rubrics and workflow designs.
• Interrogate delivery data and build/modify trackers and tools the program needs.
• Troubleshoot delivery issues with engineers and data scientists, test assumptions behind estimates.
• Validate solution approaches and effort estimates with practice/technical leads before commitments.

Skills

AI/ML lifecycle

Delivery ownership

Executive communication

Delivery tooling

Stakeholder management

Education

Bachelor's degree in engineering / CS or related

Postgraduate degree preferred

Tools

Jira

Asana

MS Project

Confluence

Job description

ABOUT THE ROLE

The Technical Delivery Manager owns end-to-end program management for Innodata's AI/ML engagements, spanning model development, training and fine-tuning, LLM-based solutions, data pipelines, model evaluation and the wider AI/ML workflow. You are accountable for keeping what the client expects and what actually gets delivered tightly aligned at every stage, and for surfacing risk early enough that it can still be solved rather than explained.

This is a client-facing position with real exposure and a technical center of gravity. You are the single point of contact for your accounts, you work with stakeholders from day-to-day contacts up to CXO level, and internally you connect practice heads, engineering, talent acquisition and operations around one delivery plan. This role is not a coordinator role. You are expected to read the guidelines, interrogate the data, challenge the estimates and take a problem apart yourself when the program needs it.

WHAT YOU WILL OWN

Program and Delivery Management

• Own the end-to-end delivery roadmap for your AI/ML programs, including model development, training and fine-tuning, LLM implementations and model evaluation workstreams
• Translate client requirements and business goals into structured delivery plans, milestones and success metrics
• Track scope, timelines, budgets and resourcing across multiple concurrent projects, flagging slippage early and driving corrective action
• Run the governance cadence for your engagements, including status reviews, steering committee updates and sprint or iteration reviews

Hands-On Technical Ownership

• Read and challenge project guidelines, annotation taxonomies, evaluation rubrics and workflow designs rather than routing every technical question to the practice teams
• Interrogate delivery and quality data directly, and build or modify the trackers and working tools the program needs
• Troubleshoot technical delivery issues alongside engineers and data scientists, and test the assumptions behind estimates and solution designs
• Work with practice and technical leads to validate solution approaches, technical feasibility and effort estimates before commitments are made to clients

Client and Stakeholder Management

• Serve as the single point of contact for your clients, managing relationships from day-to-day contacts through to CXO-level stakeholders
• Run regular client check-ins, business reviews and escalation calls, presenting delivery status, risks and outcomes
• Capture, document and continuously validate client expectations against what is actually being built, closing gaps before they surface as dissatisfaction
• Build trusted adviser relationships that support account growth and renewal

Cross-Functional Coordination

• Act as the connective tissue between practice heads, engineering, talent acquisition and operations so that everyone is working off the same delivery plan and priorities
• Coordinate staffing and hiring pipelines with talent acquisition so the right people are available in time for project ramp-up
• Partner with operations on resourcing, utilization, invoicing and billing milestones and contractual compliance

Risk, Quality and Reporting

• Identify delivery risks across technical, resourcing, scope and timeline dimensions early, and drive mitigation before they escalated
• Anticipate client concerns from program signals such as slipping milestones, performance issues or resourcing gaps, and act ahead of formal escalation
• Own issue and escalation management end to end, coordinating the right internal teams and communicating transparently with the client throughout
• Maintain accurate, real-time visibility into program health, prepare and present executive-level dashboards and reviews, and ensure contractual SLAs and deliverable timelines are met

WHAT YOU BRING

Education

• Bachelor's degree in engineering, computer science or a closely related technical discipline
• Postgraduate degree preferred. An MBA or equivalent is an advantage but not required where delivery experience compensates

Experience

• 8+ years in technical program or delivery management
• 2 to 3 years minimum specifically managing AI/ML, data science or data engineering programs
• Client SPOC ownership. Demonstrated experience as the primary client-facing point of contact for enterprise or CXO-level stakeholders
• Concurrent program ownership. Proven ability to run multiple cross-functional programs at once in a matrixed environment spanning engineering, practice teams, hiring and operations
• Services delivery model. Experience in IT services, consulting or an AI/ML solutions provider, where delivery is to a client rather than to an internal product team, is preferred

Certifications

• Required, one of the following: PMP; or at least a Lean Six Sigma Green Belt

Technical Skills

• AI/ML lifecycle. Strong working knowledge of model training and fine-tuning, LLM-based solution delivery, model evaluation and MLOps concepts
• Personal technical working capability. Able to read and challenge guidelines and workflow designs, interrogate delivery and quality data directly, build or modify trackers and utilities, and troubleshoot technical issues alongside engineers rather than delegating every technical decision
• GenAI delivery exposure. Direct exposure to LLM and generative AI delivery, including RAG pipelines, fine-tuning, agentic workflows and evaluation frameworks, is preferred
• Delivery tooling. Practical use of Jira, Asana, MS Project or Confluence, plus reporting and dashboarding tools
• Executive communication. Able to translate technical detail into business impact and present credibly to CXO audiences

HOW YOU WORK

• Orchestrator who stays in the detail. You connect client, engineering, hiring and operations, and remain close enough to the technical work to test assumptions, spot a flawed estimate and take a problem apart personally
• Proactive rather than reactive. You anticipate risks, resourcing gaps and client concerns before they surface as problems
• Credible in both rooms. You are equally at home in a technical review with engineers and a business review with a CXO
• Ownership-driven. You treat client outcomes and program health as personally accountable, end to end
• Comfortable operating on fixed governance cadences, with no tolerance for missed or inaccurate deliverables.