- Location
- BLR, AMR TECH PARK 2A - 1F - Service, India
- Workplace
- Remote
- Type
- Full-time
- Seniority
- Entry
- Experience
- 8+ years
- Education
- Master
- Source
- Workday
Description
Sagility combines industry-leading technology and transformation-driven BPM services with decades of healthcare domain expertise to help clients draw closer to their members. The company optimizes the entire member/patient experience through service offerings for clinical, case management, member engagement, provider solutions, payment integrity, claims cost containment, and analytics. Sagility has more than 25,000 employees across 5 countries.
The ideal candidate will have hands-on experience managing end-to-end AI, analytics, automation, and digital transformation projects, translating business challenges into AI-enabled solutions, and driving measurable business outcomes.
Job title:
Job Description:
Role Overview
Job Title: Associate Director/Sr. Manager - Projects
Level: Associate Director/Sr. Manager
Department: Enterprise Application Management
Location: Bangalore
Reporting To: Lead – Engagement & Solutions
Experience: 8–12+ years
Key Responsibilities
1. AI & Digital Transformation Leadership
• Lead end-to-end delivery of AI, GenAI, analytics, automation, and digital transformation initiatives.
• Partner with business stakeholders to identify opportunities for AI adoption and process transformation.
• Define project vision, objectives, business cases, KPIs, and success metrics.
• Drive AI use case prioritization based on business value, feasibility, and implementation complexity.
• Ensure alignment between business goals, technology capabilities, and delivery outcomes.
2. Project & Program Management
• Manage multiple AI and digital transformation projects simultaneously.
• Develop project plans, timelines, resource allocation, budgets, and risk mitigation strategies.
• Track project progress, dependencies, milestones, and deliverables.
• Facilitate governance meetings, steering committees, and executive status reporting.
• Ensure projects are delivered on time, within budget, and with high quality.
3. Functional & Business Consulting
• Gather and document business requirements, process maps, user journeys, and functional specifications.
• Conduct workshops with business leaders to identify process inefficiencies and automation opportunities.
• Support change management, user adoption, training, and business readiness activities.
• Drive value realization by tracking business benefits post-implementation.
4. AI &Technical Delivery Oversight
• Collaborate with Data and BI Engineers, AI Engineers, Architects, Product Managers, and Business SMEs.
• Understand AI/ML lifecycle, GenAI architectures, RAG frameworks, LLMs, and intelligent automation solutions.
• Review solution designs, data requirements, integration approaches, and deployment plans.
• Ensure adherence to AI governance, security, compliance, and responsible AI principles.
• Coordinate model deployment, testing, monitoring, and performance evaluation activities
5. Stakeholder Management & Communication
• Act as the primary liaison between business stakeholders, leadership, and technology teams.
• Manage expectations and communicate project status, risks, and recommendations effectively.
• Build strong relationships across business units and technology teams.
• Prepare clear and concise documentation including BRDs, user stories, wireframes, and solution summaries.
• Present findings, prototypes, and solution approaches to stakeholders for review and approval.
• Support change management and user training during deployment
Key Skills & Competencies
Functional
• Business Process Transformation
• Requirements Gathering & Solution Design
• Product Thinking & Value Realization
• Change Management & User Adoption
• Stakeholder & Executive Communication
• Risk & Dependency Management
• Vendor and Partner Management
• Strategic Problem Solving
• Financial and Budget Management
Technical
• AI/ML project lifecycle
• Generative AI and LLM concepts
• Prompt engineering fundamentals
• Retrieval-Augmented Generation (RAG)
• AI agents and workflow automation
• Data engineering fundamentals
• Cloud platforms (AWS, Azure, or GCP)
• API integrations
• Agile, Scrum, Kanban
• Jira, Confluence, Azure DevOps
Qualifications & Experience
• Bachelor’s degree in business, Data Analytics, Computer Science, Information Systems, or a related field
• Master's degree (MBA, MS, or equivalent) preferred.
• 8–12+ years of experience in IT, Digital Transformation, Data, or AI programs.
• Proven experience leading enterprise-scale AI and digital transformation initiatives.
• Strong experience managing cross-functional and geographically distributed teams.
Nice to Have
• MLOps concepts
• AI governance frameworks
• Model monitoring
• Data governance
• Python fundamentals
• Vector databases
• Familiarity with enterprise source systems such as Workday, SAP, Salesforce, or ERP platforms
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