AI Delivery Lead - Healthcare AI & GenAI Projects

About CitiusTech

CitiusTech specializes in healthcare IT and digital technology services, empowering healthcare providers, payers, medical technology firms, and life sciences organizations. They deliver solutions around data analytics, interoperability, digital engineering, and AI-powered healthcare platforms to enhance patient care and operational efficiency. Global teams of over 8,500 professionals collaborate with more than 140 organizations to drive digital transformation in healthcare.

Role Overview

The AI Delivery Lead is a senior leadership role responsible for managing the end-to-end delivery of AI and Generative AI projects for enterprise clients. This role demands strategic oversight combined with hands-on technical expertise in AI and machine learning. The lead acts as the primary delivery owner, ensuring projects meet timelines, budgets, and customer goals while bridging communication between business, technology teams, and client executives.

Key Responsibilities

• Conduct client discovery workshops to identify impactful AI opportunities, evaluate data readiness, and define success metrics.
• Assess clients' current technology ecosystems, data infrastructures, and AI maturity levels.
• Work with solution architects and data engineers to assess feasibility, estimate efforts, and identify technical risks.
• Produce discovery artifacts like use case prioritizations and data readiness reports.
• Collaborate with stakeholders across IT, business, and operations to align on scope, timing, and outcomes.
• Design detailed project plans including scope, timeline, milestones, and governance structures.
• Partner with AI/ML architects to define solution architectures encompassing data pipelines, model training, deployment, and integration.
• Establish governance processes such as steering committees, escalation protocols, RACI matrices, and communication schedules.
• Manage staffing and resource allocations across onshore, offshore, and client teams.
• Set acceptance criteria, quality benchmarks, and definitions of done for each delivery phase.
• Identify and mitigate project risks with contingency plans.
• Lead governance activities during implementation, including sprint and code reviews, quality assurance, and adherence to coding, security, compliance, and MLOps best practices.
• Track delivery progress metrics and intervene proactively to resolve issues.
• Facilitate customer demonstrations, user acceptance testing, and milestone sign-offs.
• Resolve escalations related to technical obstacles, scope changes, and cross-team dependencies.
• Oversee daily delivery operations, ensure sprint goal achievements, and clear impediments promptly.
• Manage project team performance, onboarding, skill evaluations, and feedback cycles.
• Optimize resource utilization across concurrent engagements to maintain balanced workloads.
• Work with talent acquisition for resource forecasting and support technical hiring processes.
• Control project finances including budget monitoring, variance analysis, and margin reporting.
• Serve as the main point of contact and accountability for clients regarding delivery status.
• Conduct regular progress and risk reviews with customer leadership.
• Build trusted advisor relationships with CIOs, CDOs, VPs, and business stakeholders.
• Identify opportunities for upselling and partner with sales teams to expand engagements.

Qualifications

• 12 to 15 years of overall IT experience.
• 4 to 5 years in managing delivery of AI/ML or data engineering projects.
• Proven leadership of teams ranging from 10 to 25+ members across onshore and offshore environments.
• In-depth knowledge of the machine learning lifecycle, including data preparation, feature engineering, model training, and evaluation.