ABOUT THE ROLE
Innodata builds and delivers AI/ML programs for some of the most demanding clients in the market, spanning model development, training and fine-tuning, LLM-based solutions, data pipelines and model evaluation. The Head of Technical Operations owns the delivery portfolio behind that work. 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 senior, client-facing position with real exposure. You own relationships from day-to-day contacts up to CXO level, lead the delivery and program managers running individual engagements, and connect practice heads, engineering, talent acquisition and operations around one delivery plan. This is a technical leadership role, not an administrative one. You are expected to stay close enough to the work to read the guidelines, interrogate the data, challenge an estimate and take a problem apart yourself when a program needs it.
WHAT YOU WILL OWN
Portfolio and Delivery Ownership
- Own the end-to-end delivery roadmap for a portfolio of 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 that your managers can execute against
- Hold scope, timelines, budgets and resourcing across multiple concurrent engagements, and intervene where slippage threatens a client commitment
- Set and enforce the governance cadence across all active engagements, including status reviews, steering committee updates and sprint or iteration reviews
Technical Ownership and Depth
- 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 instead of relying on summarized reporting, and build or modify the trackers and working tools a program needs
- Work with practice and technical leads to validate solution approaches, technical feasibility and effort estimates before commitments are made to clients
- Get into the detail with engineers and data scientists when a program is off track, and set the technical standard your delivery managers are held to
Client and Executive Relationships
- Own the senior client relationship for the portfolio, working with stakeholders from day-to-day contacts through to CXO level
- Lead business reviews and escalation calls, presenting delivery status, risks and outcomes with a clear point of view
- 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
Team and Cross-Functional Leadership
- Lead delivery and program managers, set the delivery standard for the portfolio and develop the capability of the team behind it
- 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
Risk, Quality and Governance
- 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 portfolio health, present executive dashboards and reviews, and ensure contractual SLAs, deliverable timelines and commercial commitments are tracked and met
- Drive continuous improvement in delivery processes, templates and playbooks based on lessons learned across engagements
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
- 10+ years in technical program or delivery management, with progression into portfolio or multi-account ownership
- 3+ years specifically managing AI/ML, data science or data engineering programs
- Executive client ownership. Demonstrated experience as the senior client-facing owner for enterprise or CXO-level stakeholders, including escalations and commercial conversations
- People leadership. Experience leading delivery managers, program managers or senior individual contributors, with accountability for their output and development
- Portfolio scale. 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 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 portfolio health as personally accountable, end to end
- Comfortable operating on fixed governance cadences, with no tolerance for missed or inaccurate deliverables