HIH - Machine Learning Advisor

Position Overview

We’re looking for an AI/ML Advisor who will be responsible for accelerating enterprise-scale AI adoption across our platforms and portfolios. This journey requires defining and governing enterprise AI architecture & strategy, establishing platform standards, driving portfolio prioritization & ROI, and enabling teams through governance, risk management, and scalable operating models. This role requires proven technology leadership with strong hands-on grounding, plus the ability to influence senior stakeholders, steer investment decisions, and enable organization-wide adoption responsibly.

We are seeking a highly skilled and innovative AI/ML Advisor with 11–13 years of experience to join our team. This role is ideal for professionals who combine deep experience across software/AI architecture with strong leadership in Responsible AI/HIPAA-aligned governance, agentic AI reference architectures, RAG-at-scale, and LLMOps quality frameworks. You will be instrumental in shaping AI strategy, building adoption playbooks, enabling teams through coaching and learning programs, and providing thought leadership through research, benchmarks, and vendor evaluations.

Responsibilities

• Drive Enterprise AI Architecture & Strategy, defining target-state architectures and adoption patterns for AI/GenAI across business domains.
• Lead portfolio prioritization & ROI by establishing intake/prioritization frameworks, value measurement approaches, and investment recommendations.
• Establish and enforce Governance & Risk practices aligned to HIPAA/Responsible AI, including privacy, security, compliance controls, and escalation pathways.
• Define platform standards & vendor strategy, including reference stacks, vendor scans, evaluation criteria, and decision frameworks for enterprise adoption.
• Develop and maintain agentic AI reference architectures, including orchestration patterns, tool-calling standards, autonomy boundaries, and human-in-the-loop controls.
• Lead RAG-at-scale strategy and standards (knowledge ingestion, chunking, retrieval patterns, grounding, caching, multi-index approaches), ensuring quality and governance alignment.
• Establish LLMOps & Quality Frameworks, including evaluation methodology, test harnesses, golden datasets, safety/quality gates, and continuous monitoring.
• Own cost/capacity management for AI systems—token economics, usage forecasting, capacity planning, optimization levers, and executive-ready reporting.
• Drive change management & stakeholder enablement, ensuring teams understand standards, adoption pathways, and operational readiness requirements.
• Provide team coaching & technical mentorship for architects, engineers, and analysts—raising maturity across design, delivery, and operational excellence.
• Create and scale org-wide learning programs (curricula/certifications), including enabling assets like playbooks, templates, examples, and role-based pathways.
• Produce internal enablement content such as vlogs/blogs/brown-bags, and establish repeatable mechanisms to share learnings and accelerate adoption.
• Provide research & thought leadership through benchmarks, evaluations, vendor scans, and literature reviews; synthesize findings into actionable recommendations.
• Facilitate and grow a Community of Practice, driving standards adoption, knowledge sharing, and consistent solution quality across teams.
• Partner with Product, Architecture, Security, Compliance, and Delivery leadership to ensure solutions align with enterprise strategy and responsible AI commitments.
• Support the full lifecycle from strategy → architecture → adoption, ensuring delivery teams have the frameworks, guardrails, and reference implementations needed to execute successfully.

Qualifications

Required Skills:

• Bachelor’s Degree in Information Technology, Computer Science, Engineering, or related coursework
• 11–13 years of experience across enterprise architecture, software engineering, AI/ML strategy, and scalable delivery leadership
• Deep expertise in Enterprise AI Architecture & Strategy and driving adoption through reusable patterns and standards
• Strong experience in portfolio prioritization, ROI measurement, and value realization for AI initiatives
• Expertise in Governance & Risk with Responsible AI and privacy/security considerations (HIPAA-aligned practices preferred)
• Experience defining platform standards and vendor strategy, including evaluations, scoring frameworks, and decision guidance
• Strong experience with agentic AI reference architectures, orchestration, and tool-calling patterns
• Proven expertise delivering RAG-at-scale patterns and enterprise knowledge grounding strategies
• Strong capability in LLMOps quality frameworks: evaluation design, guardrails, monitoring, regression testing, and governance gates
• Experience with cost/capacity management and operational metrics for GenAI/LLM systems
• Strong change leadership: stakeholder enablement, adoption planning, communication, and operating model alignment
• Demonstrated coaching/mentorship ability across engineers/architects and cross-functional leaders
• Ability to build and scale org-wide learning programs (curricula/certifications) and create internal content assets
• Excellent communication skills—able to convey complex strategy/architecture topics to executive and delivery audiences

Required Experience & Education:

• Proven experience leading enterprise-scale strategy and architecture for large, complex technology ecosystems
• College degree (Bachelor) in related technical/business areas or equivalent work experience
• Demonstrated success influencing senior stakeholders and driving decisions across architecture councils, governance forums, and portfolio reviews
• Experience establishing standards and enabling multiple teams to deliver consistently within guardrails and quality frameworks
• Willing to go above and beyond attitude; thrives in ambiguity and fast-moving environments

Desired Experience:

• Healthcare experience is preferred
• Experience operating in regulated environments with strong emphasis on privacy/security/compliance and Responsible AI governance

Location & Hours of Work

• Full-time position, working 40 hours per week. Expected overlap with US hours as appropriate
• Primarily based in the Innovation Hub in Hyderabad, India in a hybrid working model (3 days WFO and 2 days WAH)

Equal Opportunity Statement

Evernorth is an Equal Opportunity Employer actively encouraging and supporting organization-wide involvement of staff in diversity, equity, and inclusion efforts to educate, inform and advance both internal practices and external work with diverse client populations.

About Evernorth Health Services

Evernorth Health Services, a division of The Cigna Group, creates pharmacy, care and benefit solutions to improve health and increase vitality. We relentlessly innovate to make the prediction, prevention and treatment of illness and disease more accessible to millions of people. Join us in driving growth and improving lives.