Machine Learning Associate Director - HIH - Evernorth

Position Overview

We are seeking a senior engineering leader to establish and scale the Hyderabad engineering organization for AIBEACONS, building a high-performing capability that delivers AI-powered platforms and solutions across AI Enablement and Productization, Clinical AI and Innovation, Behavioral Health, Payer Solutions and Sales AI portfolios.

This role leads the build-out and growth of a 60–70+ person engineering organization based in Hyderabad and serves as a key execution partner to U.S. leadership.

This leader will be responsible for forming, growing, and maturing the Hyderabad organization into a high-performing, outcome-driven engineering organization that consistently delivers portfolio value and supports enterprise AI commitments.

The primary focus of this role is to build the right team, leadership structure, and operating model required to execute at scale combining strong hiring capability, engineering rigor, AI expertise and engagement with the India AI startup ecosystem to accelerate delivery.

You will be accountable for establishing the engineering organization, scaling talent, and enabling consistent delivery of AI powered capabilities, while fostering a culture of ownership, innovation, and engineering excellence in a global, matrixed environment.

Responsibilities  

AI Enablement & Productization

·       Establish and scale AI productization capabilities for U.S. Employer, translating business priorities into deployable AI solutions and reusable platforms

·       Establish the talent strategy and operating model required to deliver AI products for U.S. Employer, in close collaboration with Product and Technology organizations

·       Build and lead forward-deployed engineering teams, partner with other U.S. Employer Technology organizations and co-develop AI products aligned to business priorities

·       Drive research, continuously expand organizational AI proficiency, and operationalize AI capabilities at scale, in partnership with the AI Enablement Office

·       Lead rollout of AI-first SDLC practices, including tooling, frameworks, guardrails, and reusable patterns across teams

·       Define and implement mechanisms to measure AI value realization, including adoption, productivity gains, and business impact

·       Enable enterprise-wide adoption of AI tools, platforms, and solutions, ensuring effective usage and integration into workflows

·       Drive rapid prototyping, iteration, and scaling of AI solutions, ensuring alignment with governance, Responsible AI, and enterprise standards

Enterprise Delivery & Execution

·       Establish and scale high-performing AI and engineering teams delivering AI/GenAI-powered platforms and products across Clinical AI & Innovation, Behavioral Health, Payer Solutions, and Sales AI portfolios

·       Ensure strong execution discipline with clear accountability for scope, timelines, quality, and measurable AI-driven business outcomes

·       Translate business priorities into AI-first engineering roadmaps, aligning use cases to scalable platforms and product delivery

·       Balance rapid AI innovation with enterprise requirements for stability, scalability, security, and compliance

·       Drive measurable value realization from AI and GenAI investments, including adoption, productivity gains, and business impact

People & Organizational Leadership

·       Build, scale, and lead a 60–70+ member AI engineering organization, including hiring strong talent in GenAI, ML engineering, data engineering, and platform engineering

·       Establish a strong leadership bench with AI depth and engineering rigor

·       Create a high-performance culture focused on AI innovation, rapid experimentation, and outcome-driven delivery

·       Partner with Talent and HR to design and execute hiring strategies focused on top-tier AI and GenAI talent

·       Coach and develop engineering leaders in both AI technical depth and people leadership

·       Foster an environment that promotes continuous learning in AI, experimentation, and external engagement

·       Manage vendor and partner contributions, including AI/GenAI technology providers and startups

·       Develop strategic industry and academic partnerships to attract and hire top AI talent in a rapid and scalable manner

Global Partnership & Influence

·       Act as a key execution partner to U.S.-based leadership, aligning Hyderabad teams to enterprise AI strategy and priorities

·       Operate effectively within a global, matrixed model, coordinating across Product, Talent, HR, Architecture, Data, and Technology stakeholders

·       Ensure strong alignment across geographies for AI platform development and delivery

·       Build relationships within the India AI startup ecosystem, academia, and innovation networks to strengthen hiring and capability

·       Provide clear, consistent communication on AI delivery progress, risks, and outcomes

·       Collaborate and establish partnerships with U.S. Employer Technology organizations such as Claims, Provider Tech, Digital, etc. and also create cross functional partnership with the hub teams.

Engineering Excellence & Governance

·       Establish and institutionalize AI/GenAI engineering standards, including model evaluation, observability, performance monitoring, and continuous improvement

·       Ensure alignment with enterprise architecture, Responsible AI, security, privacy, and regulatory compliance requirements

·       Drive improvements in AI engineering productivity, quality, and speed through standardized tooling, platforms, and best practices

·       Build scalable, repeatable engineering practices that enable long-term growth of AI capabilities and consistent delivery across the Hyderabad organization

Qualifications

Experience & Education:

·       Bachelor’s degree in Computer Science or related field; advanced degree preferred

·       14+ years of engineering experience, including 5+ years in AI leadership roles

·       Experience building and scaling engineering teams in global organizations

·       Demonstrated expertise in modern AI/ML and Generative AI systems, including:

o   LLM ecosystems (OpenAI, Azure OpenAI, Anthropic, open-source models such as Llama, Mistral)

o   Retrieval-Augmented Generation (RAG) architectures, including hybrid search, embeddings, vector databases (Pinecone, Weaviate, FAISS), and grounding strategies

o   Context engineering (prompt design, memory management, context windows, tool augmentation, multi-step reasoning)

·       Deep experience designing and implementing agentic AI systems, including:

o   Multi-agent architectures using frameworks such as LangGraph, AutoGen, CrewAI, AWS Agent Core, Agents SDK

o   Agent orchestration, planning, tool use, and agent-to-agent (A2A) communication

o   Familiarity with Model Context Protocol (MCP) and emerging agent interoperability standards

·       Experience building knowledge graph and context graph–driven systems, including:

o   Graph data models (Neo4j, RDF/SPARQL)

o   Integration of structured and unstructured data for reasoning, personalization, and decision intelligence

·       Strong foundation in deep learning and ML frameworks, including:

o   PyTorch, TensorFlow, JAX, and Hugging Face ecosystem (Transformers, Accelerate, PEFT)

o   Model training, fine-tuning (LoRA/PEFT), evaluation, and optimization techniques

·       Experience with MLOps and LLMOps, including:

o   Model lifecycle management, versioning, deployment, monitoring, and observability

o   Evaluation frameworks (LangSmith, DeepEval), human-in-the-loop systems, and continuous improvement pipelines

·       Proven ability to design and implement decision intelligence systems, combining data, models, knowledge graphs, and business rules to drive automated and assistive decisioning

·       Experience establishing AI-first SDLC practices, including secure DevOps, governance, evaluation, guardrails, and Responsible AI controls

·       Experience building AI-native platforms and products, including integration of APIs, microservices, and event-driven architectures

·       Demonstrated ability to drive large-scale AI delivery with measurable business outcomes

·       Experience partnering with startups, product, and business stakeholders to align AI solutions with roadmap and safely deploy capabilities

Success in this role will be defined by the ability to build and scale a high-performing Hyderabad AI engineering organization for AIBEACONS, drive AI enablement for US Employer Technology organization, establish strong AI leadership and delivery foundations, and enable consistent, high-quality execution of GenAI-powered solutions and enterprise AI commitments through the teams and capability created.

About Evernorth Health Services