Artificial Intelligence

• Leading the development and implementation of governance frameworks to manage risk and compliance for clients
• Analyzing complex regulatory landscapes to provide strategic advice and solutions
• Managing client engagements, confirming successful planning, budgeting, and execution of projects
• Coaching and mentoring team members to enhance their skills and performance
• Collaborating with leadership to maintain quality and meet client expectations
• Utilizing risk governance knowledge to enhance internal controls and mitigate risks
• Encouraging innovation and technology adoption to improve service delivery
• Addressing conflicts and facilitating difficult conversations with stakeholders
• Upholding professional and technical standards, including adherence to the firm's code of conduct
• Identifying opportunities for improvement and contributing to the firm's success

AI Governance Manager

• Navigating complex regulatory landscapes to provide risk management solutions for clients
• Building and maintaining meaningful client relationships to understand and anticipate their needs
• Utilizing critical thinking to break down complex concepts and develop actionable insights
• Applying risk governance methodologies to enhance internal controls and mitigate risks
• Interpreting data to inform strategic recommendations and support decision-making processes
• Upholding professional and technical standards in alignment with firm guidelines and independence requirements
• Collaborating with teams to generate innovative ideas and solve regulatory compliance challenges
• Mentoring junior team members to foster their development and enhance team performance

Senior Associate, AI Governance

• Contribute to the strategic oversight and optimization of competitive intelligence and AI-enabled research capabilities.
• Support the Enterprise Strategy team's research tool ecosystem by partnering with the Lead Director.
• Act as the SME and product owner of the team’s knowledge management system (Crayon).
• Organize requirements and work with vendors on new features, oversee utilization reporting, and identify ways to leverage platforms for research needs.
• Partner closely with Strategy leaders and external vendors to align tool capabilities with evolving business needs.

Senior Manager – Market Intelligence, AI Technology Platforms

• Reimagine Credit Strategy Through Automation
• Deconstruct and redesign credit underwriting processes
• Identify opportunities where AI and machine learning can enhance credit decisions
• Partner with IT and business teams to translate credit requirements into technical specifications
• Build compelling business cases for technology investments
• Design sophisticated workflow automation
• Leverage FNBO's AI toolkit to prototype, test, and scale solutions rapidly
• Present recommendations to C-level executives with clarity and confidence
• Drive change management efforts
• Stay ahead of emerging AI capabilities and credit technology trends

Credit Risk AI Enablement

• Build and lead market growth strategy for P&C insurers, reinsurers and insurtechs, to include establishing and owning senior prospect relationships.
• Engage C-suite and VP stakeholders (Claims, Data, Underwriting, Risk) as a trusted advisor, not a vendor.
• Operate as a strategic advisor on AI adoption, from use case identification to production deployment and model governance.
• Lead executive discussions on how AI, particularly human-in-the-loop approaches, can improve efficiency, accuracy, and regulatory defensibility.
• Align complex stakeholder groups across claims, actuarial, IT, data science, and compliance functions.
• Identify and drive expansion opportunities within existing accounts.
• Own new logo acquisition, account expansion and P/L management across enterprise P&C clients in the US and Europe.
• Develop strategic account plans that scale from initial use cases to enterprise-wide AI programs.
• Own the full commercial lifecycle: discovery, solution framing, proposal development, and executive presentations.
• Navigate procurement processes, RFPs, vendor risk frameworks, and regulatory constraints effectively.
• Partner with internal teams to craft tailored, high-impact solutions for insurance clients.
• Identify high-impact AI use cases across the insurance value chain, including:
• - Claims document processing and intelligent document understanding
• - Aerial and satellite imagery analysis for property assessment
• - NLP for policy, coverage, and regulatory interpretation
• - Underwriting data enrichment and risk model validation
• - FNOL automation and subrogation workflows
• Lead discovery sessions and workshops to uncover transformation opportunities.
• Translate operational and regulatory challenges into scalable AI solutions.
• Collaborate closely with data science and engineering teams to ensure successful execution.
• Maintain accountability for delivery quality, timelines, and client satisfaction.
• Stay at the forefront of AI trends in insurance, including fraud detection, intelligent document processing, and risk modeling.
• Represent CloudFactory in industry forums, client workshops, and executive discussions.
• Demonstrate strong awareness of regulatory frameworks (e.g., NAIC guidelines, EU AI Act, model risk management standards).
• Feed market insights back into product development and go-to-market strategy.
• Lead and influence cross-functional teams across consulting, data science, and delivery.
• Foster a culture of collaboration, innovation, and continuous improvement.
• Contribute to knowledge sharing and best practices across engagements.

Client Principal, AI Consulting – Property & Casualty Insurance

• Serve as EnerSys’ executive leader and single point of accountability for enterprise AI strategy, execution, and outcomes.
• Translate enterprise and business strategies into a clear, multi‑year AI vision and roadmap.
• Advise the CIO, ELT, and Board on AI trends, risks, opportunities, and competitive implications.
• Represent EnerSys externally with strategic AI partners, technology providers, and industry forums.
• Design and implement the enterprise AI operating model, including governance forums and funding processes.
• Establish enterprise standards for responsible AI, data usage, security, privacy, and risk management.
• Own AI investment governance, ensuring alignment with capital planning and transformation funding.
• Own the global AI use case portfolio and prioritization framework.
• Define, track, and report enterprise AI value metrics.
• Orchestrate cross-functional delivery across IT, data, and business units.
• Partner with HR to lead enterprise-wide change management and AI literacy initiatives.
• Build, lead, and develop a high performing enterprise AI organization with clear roles.

VP, Enterprise AI Enablement

• Own the full AI engagement arc from discovery through sustained workflow adoption
• Drive requirements and delivery precision to track against plans and surface risks early
• Champion continuous quality through testing and feedback loops during AI engagements
• Hold the R&D feedback loop accountable to ensure field learnings flow back
• Build playbooks to identify reusable patterns and scalable frameworks for the team
• Own engagement economics and track cost structure across active engagements
• This is a field-first role with expected travel to partner locations

AI Engagement Manager

• Own outcomes for programs/portfolios; establish delivery strategy, guardrails, and success metrics
• Drive execution from initiation through release and stabilization; manage scope, estimates, schedules, risks/issues
• Promote advanced Agile behaviors; coach teams toward self‑organization and continuous improvement
• Lead Implementation of best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies
• Serve as a trusted point of contact for sponsors and leaders; proactively manage risks and dependencies
• Mentor Scrum Masters/APOs; coordinate partner resources; uphold engineering and documentation standards
• Align delivery with technical design; leverage knowledge of modern data stacks (AWS, GCP, Snowflake, ETL/ELT, BI), Agentic solutions, graph database solutions, CI/CD, and DevOps
• Stay up to date with industry advancements in GenAI and apply modern technologies and methodologies to our systems
• Drive the culture of Innovative ideas to improve productivity, quality through GenAI, automation and process improvements

Data & AI Delivery Lead

• Serve as a strategic advisor across The Cigna Group senior clinical and business leadership, translating enterprise and organizational priorities into actionable strategies.
• Identify emerging trends in clinical care integrating AI, digital health, and other emerging technologies to inform business planning.
• Engage external industry leaders, prospective partners, and other thought partners for strategy development and benchmarking.
• Partner with business units, finance, and other operating partners to create and validate business cases, along with KPIs/success metrics.
• Create and iterate on high-impact presentations, analyses, and briefing documents for C‑suite and enterprise committees.
• Act as a catalyst for change, positioning The Cigna Group clinical team as a strategic growth engine within the broader enterprise.
• Support the program design and refinement of differentiated technology and AI offerings, tailored to specific clinical and business needs.
• Collaborate with matrix partners across Cigna business units, along with operational partners in technology and data and analytics to ensure alignment and execution.
• Ensure operational readiness and scalability of new clinical programs and services.
• Track and report on initiative performance, ensuring alignment with financial and clinical impact goals.
• Develop executive-level communications, including strategy memos and stakeholder updates.

Principal, Enterprise Clinical Technology & AI Strategic Initiatives

• Partner with stakeholders to understand business needs, operational pain points, and workflow inefficiencies across Marketing and Communications
• Analyze current-state workflows to identify opportunities for AI-enabled process improvement, automation, and redesign
• Serve as a consultant to teams on how to evolve ways of working through AI, agents, and automation
• Facilitate discussions that clarify problems, desired outcomes, and opportunities for workflow transformation
• Translate business needs into clear use cases, workflow requirements, acceptance criteria, and success metrics
• Assess solution feasibility, expected value, scalability, effort, and risk
• Prioritize opportunities in alignment with team needs, business impact, and the broader AI strategy
• Help manage a pipeline of solution opportunities from intake through recommendation and delivery
• Design, build, test, and deploy AI-enabled solutions including agents, automations, workflow improvements, and supporting tools
• Own implementation for assigned solutions, coordinating requirements, testing, stakeholder input, and rollout
• Iterate on solutions based on performance, feedback, and evolving business needs
• Maintain and enhance deployed tools and workflows to improve effectiveness and adoption over time
• Ensure solutions align with enterprise policies, governance requirements, and responsible AI practices
• Support teams in adopting redesigned workflows and integrating AI-enabled solutions into day-to-day operations
• Monitor usage, outcomes, and performance to identify gaps and opportunities for refinement
• Document reusable patterns, use cases, and recommendations that can be scaled across the function

Business Communications Advisor – AI Workflow and Solutions

• Set the multi-year strategy for ML, data, and BI
• Build and scale the Data Science / AI, Data Engineering, and BI Engineering organization
• Manage managers and tech leads
• Run performance management, career development, and retention
• Operate as a peer to VP-level leaders across various functions
• Own the architecture, deployment, and operation of the production ML

VP of AI, ML and Data Strategy

• Own delivery, performance, and risk outcomes for a large, complex Claims Applied AI portfolio spanning multiple teams, domains, and value streams
• Drive measurable business value across the end-to-end claims journey by developing, testing, deploying, and scaling Predictive, Generative, and Agentic AI solutions
• Be the senior business partner for Claims leaders
• Build deep partnerships within portfolio and value stream frameworks
• Lead and develop senior leaders and teams
• Provide portfolio-level technical direction and oversight
• Ensure disciplined architecture and delivery trade-offs across quality, grounding, latency, cost, scalability, and regulatory risk
• Establish and enforce evaluation, monitoring, and production readiness across solution types
• Set governance expectations for unstructured data and retrieval across Claims
• Accountable for AI governance and compliance-by-design across the Claims portfolio
• Influence technology integration and platform strategy
• Champion reuse and scalability by partnering with AI platform owners and peers
• Provide thought leadership and change leadership
• Oversee portfolio planning, dependencies, resourcing, and financial stewardship

AVP Applied AI, Claims

• Lead stakeholders through process mapping and operational improvement
• Own the design, build, and iteration of low-code and AI-enabled workflows
• Translate business needs into reliable, production-grade automations
• Develop and maintain evaluation sets, define quality thresholds, and run A/B tests
• Integrate automation into dashboards and reporting
• Track and communicate impact of automation and AI solutions
• Continuously assess new and existing applications and SaaS platforms
• Lead pilots and proofs of value for new workflows or AI capabilities
• Provide training and enablement to Legal & Compliance teams
• Partner with the Compliance Training team to create AI use case specific policies

Data & AI Operations Manager

• Architect internal productivity revolution and analyze workflows.
• Rapidly prototype and refine agentic solutions.
• Help build and deploy production grade AI agents.
• Integrate AI agents with enterprise resources.
• Define and track productivity & ROI.
• Stay at the forefront of AI developments in the media industry.

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