Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future.
Join our team as the expert you are now and create your future.
We are looking for a senior, technically grounded Project Manager to lead the execution of complex Digital and AI solutions within our AI practice. You will own technical delivery across multiple workstreams and pods that bring AI-powered solutions to life for clients in industries such as higher education, healthcare, and utilities.
This is a hands-on delivery leadership role. You will work side by side with Solution Architects and AI Engineers to turn an architecture into a sequenced, buildable plan — then drive it through sprints, integration, testing, and production release. You are expected to be technical enough to read the design, question an estimate, manage risk, communicate dependencies, and hold the team to engineering standards.
You will also raise delivery maturity across the practice: coaching project managers and scrum leads, and strengthening the estimation models, engineering checklists, and delivery metrics we reuse across engagements.
If you enjoy staying close to the build while leading at scale, and thrive in fast-moving, client-facing environments, this role is for you.
Key Responsibilities
- Own technical delivery execution across multiple AI workstreams and pods — release plan, sprint cadence, technical milestones, and definition of done.
- Partner with Solution Architects to translate architecture and design into a sequenced build plan; decompose epics into deliverable increments and own the health of the technical backlog.
- Run agile delivery at scale: sprint planning, backlog refinement, demos, and retrospectives across pods, with active resolution of cross-pod dependencies.
- Manage technical dependencies end to end — environments, data access and readiness, API and integration availability, infrastructure provisioning, and client IT or third-party prerequisites.
- Hold teams to engineering standards: branching and version control, code review, CI/CD, test automation, observability, documentation, and deliberate management of technical debt.
- Own AI-specific quality gates — dataset readiness, prompt and model evaluation harnesses, accuracy and hallucination thresholds, human-in-the-loop review, and regression testing ahead of each release.
- Drive non-functional requirements into the backlog early rather than at the end: performance, cost-to-serve, scalability, security, data privacy, and responsible AI review.
- Lead release and production readiness — cutover planning, UAT, deployment runbooks, hypercare, and handover to support or managed service.
- Track and report technical progress, burn, risks, and blockers to client stakeholders and Huron leadership with an honest, evidence-based view; escalate early and constructively.
- Coach technical project managers, scrum leads, and analysts; raise delivery discipline and consistency across the pods you oversee.
- Build and maintain reusable delivery assets: templates, estimation models, engineering checklists, and delivery metrics for the practice.
Preferred Qualifications
- 13+ years managing technical delivery of software or AI/ML projects, including 4+ years in a consulting, professional services, or client delivery setting.
- A hands-on technical background — engineering, data, or architecture — prior to moving into delivery management; able to read an architecture diagram, review a data model or API contract, and pressure-test an estimate.
- Demonstrated experience running multiple concurrent agile pods or workstreams on a single program.
- Strong command of agile delivery, backlog management, release coordination, and dependency management.
- Practical understanding of AI and GenAI solution development lifecycles — data pipelines, RAG and agentic patterns, prompt and model evaluation, MLOps/LLMOps, and production deployment.
- Working knowledge of modern engineering practice: Git-based workflows, CI/CD, containers, test automation, and observability.
- Familiarity with major cloud platforms (AWS, Azure, Google Cloud, or OCI) and enterprise data and integration landscapes.
- Comfortable holding architecture, security, and data privacy review conversations with client IT teams.
- Ability to communicate credibly with both technical teams and executive business audiences, and to hold a clear point of view under pressure.
- Experience in healthcare domain is a plus.
- Bachelor’s degree in Engineering, Computer Science, or a related field; advanced degree and PMP, SAFe, or Agile certification are a plus.
Position Level
Senior Manager
Country
India
