Job Description
AI Delivery Lead
Who we are: -
At CitiusTech, we constantly strive to solve the industry's greatest challenges with technology, creativity, and agility. With over 8,500 healthcare technology professionals worldwide, CitiusTech powers healthcare digital innovation, business transformation, and industry-wide convergence for over 140 organizations through next-generation technologies, solutions, and products. We aim to accelerate the transition to a human-first, sustainable, and digital healthcare ecosystem with the world's leading Healthcare and life sciences organizations and our partners.
Here is an opportunity for you to make a difference and collaborate with global leaders to shape the future of healthcare and positively impact human lives.
What is in it for you?
The AI Delivery Lead is a senior leadership role responsible for end-to-end delivery of AI and GenAI projects for enterprise customers. This individual will serve as the primary delivery owner across the full project lifecycle — from discovery and solution design through implementation and go-live — ensuring that projects are delivered on time, within budget, and aligned with customer outcomes.
The role combines strategic project leadership with deep technical fluency in AI/ML, enabling the AI Delivery Lead to bridge the gap between business stakeholders, technical teams, and customer leadership. This person will be hands-on during discovery and planning phases and shift to a governance and review role during implementation, while maintaining overall accountability for delivery quality and resource utilization.
1. Discovery & Assessment Phase
- Lead customer discovery workshops to identify high-value AI use cases, assess data readiness, and define success criteria
- Conduct current-state assessment of customer’s technology landscape, data infrastructure, and organizational AI maturity
- Collaborate with solution architects and data engineers to evaluate feasibility, estimate effort, and identify technical risks
- Develop discovery deliverables including use case prioritization matrices, data readiness scorecards, and preliminary solution hypotheses
- Engage customer stakeholders (IT, business, clinical/operations) to align on scope, timelines, and expected business outcomes
2. Planning & Solution Design Phase
- Define project scope, work breakdown structure (WBS), milestones, dependencies, and delivery timelines
- Partner with AI/ML architects to design solution architecture covering data pipelines, model training, serving infrastructure, and integration touchpoints
- Establish project governance framework including steering committees, escalation paths, RACI matrices, and communication cadence
- Create staffing plans and resource allocation strategies across onshore, offshore, and customer teams
- Define acceptance criteria, quality gates, and definition of done for each sprint and phase
- Identify and document project risks with mitigation and contingency strategies
3. Implementation Phase (Governance & Review)
- Serve as the delivery governance lead, conducting sprint reviews, code and architecture reviews, and quality checkpoints
- Monitor delivery velocity, burndown metrics, and team health; intervene proactively when delivery is at risk
- Review technical artifacts including model evaluation reports, data pipeline designs, API specifications, and deployment runbooks
- Ensure adherence to coding standards, MLOps best practices, security protocols, and compliance requirements
- Facilitate customer demos, UAT cycles, and sign-off processes at each milestone
- Act as the escalation point for technical blockers, scope changes, and cross-team dependencies
4. Resource Management & Delivery Operations
- Own day-to-day delivery operations ensuring sprint commitments are met and impediments are cleared within 24 hours
- Manage project team composition including onboarding, skill-gap assessment, and performance feedback for delivery resources
- Optimize resource utilization across concurrent AI engagements, balancing workload and bench time
- Coordinate with the talent and hiring team to forecast resourcing needs and participate in technical interviews
- Manage project financials including budget tracking, effort variance analysis, and margin reporting
5. Customer Relationship & Stakeholder Management
- Serve as the single point of accountability for the customer on all delivery matters
- Conduct weekly and monthly status reviews with customer leadership, presenting progress, risks, and decisions needed
- Build trusted advisor relationships with customer CIOs, CDOs, VPs, and line-of-business owners
- Identify upsell and expansion opportunities during engagements and partner with sales/account teams to pursue them
- 12–15 years of total IT experience with at least 4–5 years in delivery management of AI/ML or data engineering projects
- Demonstrated experience leading teams of 10–25+ across onshore/offshore delivery models
- Strong understanding of ML lifecycle including data preparation, feature engineering, model training, evaluation, deployment, and monitoring
- Experience with GenAI technologies including LLMs, RAG architectures, prompt engineering, vector databases, and agentic AI frameworks (e.g., LangChain, LangGraph, CrewAI)
- Proficiency in at least one cloud platform (AWS, GCP, or Azure) with understanding of AI/ML managed services
- Experience with Agile/Scrum delivery at scale; certified Scrum Master or SAFe credentials preferred
- Excellent verbal and written communication skills with the ability to present to C-suite and technical audiences
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field
- Prior experience delivering AI solutions in healthcare (payer, provider, pharma, or life sciences verticals)
- Familiarity with healthcare data standards such as HL7, FHIR, EDI (837/835), HIPAA, and clinical terminologies
- Experience in Revenue Cycle Management (RCM) automation, claim processing, prior authorization, or clinical NLP use cases
- PMP, PgMP, or equivalent project management certification
- Experience building and scaling AI Centers of Excellence or AI platform teams within IT services organizations
- Exposure to AI governance frameworks, responsible AI principles, and model risk management
One of CitiusTech offices at
Life at CitiusTech
We focus on building highly motivated engineering teams and thought leaders with an entrepreneurial mindset, centered on our core values of Passion, Respect, Openness, Unity, and Depth (PROUD) of knowledge. Our success lies in creating a fun, transparent, non-hierarchical, diverse work culture that focuses on continuous learning and work-life balance.
Rated by our employees as the ‘Great Place to Work for’ according to the Great Place to Work survey. We offer you a comprehensive set of benefits to ensure that you have a long and rewarding career with us.
Our EVP
Be You Be Awesome is our EVP and it reflects our continuing efforts to create CitiusTech as a great place to work where our employees can thrive, both personally and professionally. It encompasses the unique benefits and opportunities we offer to support your growth, well-being, and success throughout your journey with us and beyond. Together with our clients, we are solving some of the greatest healthcare challenges and positively impacting human lives. Welcome to the world of Faster Growth, Higher Learning, and Stronger Impact.
Join CitiusTech. Be You. Be Awesome.
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