Developing AI-driven strategies to support business value
Identify, qualify, and prioritize high impact AI, analytics, and agentic automation opportunities across business domains.
Quantify full value at stake and value levers (automation, augmentation, revenue lift, risk mitigation), with clear dependencies and path to realization.
Bringing together expertise in AI, data engineering, solution architecture, and relevant business domains to design fit-for-purpose solutions leveraging LLMs, RAG, and agentic automation.
Translating ambitious north star visions into executable plans, building alignment among relevant executives and business stakeholders on timing and delivery
Achieving maximum scale from AI solutions by proactively identifying and addressing barriers to scale and generalizing solutions to multiple applications
Partner with vendors and internal platform teams on best practices on platform (i.e., Copilot Studio, Azure OpenAI, Power Platform, AWS Bedrock, Sagemaker, Databricks, etc.) governance to ensure enterprise grade scalability, security, and compliance.
Enabling rapid and iterative delivery of AI solutions with consistent value creation
Serve as solutions architect and product owner for critical initiatives—defining scope, non functional requirements, SLAs/SLOs, and acceptance criteria.
Partnering with AI and ML engineering leaders to manage versioning, iteration planning, and solution delivery, creating transparency for business stakeholders and proactively mitigating delivery issues
Building productive relationships with key business stakeholders to help them co-own the AI solutions, enabling the business to provide feedback and guidance all stages of development
Bringing business expertise and focus on value capture to AI problem-solving during development, helping the team to maximize impact and minimize unnecessary complexity
Augmenting our business stakeholders’ teams with AI and change management expertise, helping them to realize maximum value from AI solutions
Advancing our innovative operating model for AI teams
Leading in interactions with AI and ML engineering teams to develop and codify more effective ways to AI and strategy teams to collaborate
Monitor industry trends and emerging technologies to ensure the organization remains at the forefront of AI and automation advancements.
Oversee the needs for documenting knowledge, creating templates, and authoring playbooks to help the team scale
Develop and maintain three synchronized roadmaps: stakeholder engagement & adoption, use case portfolio, and technical capabilities/platform evolution
Conducting peer training and authoring thought leadership along with other members of the team to augment the full team’s skills
Developing new delivery frameworks and helping the team build new service offerings

Requirements

Years using data and AI to solve complex business problems and drive measurable impact in large, regulated environments.
Proven track record influencing and aligning executives and cross functional teams to deliver outcomes at portfolio scale.
Hands on leadership of technology strategies in AI/ML, analytics, BI, and automation—spanning both low code (e.g., Copilot Studio/Power Platform) and pro code stacks.
Strong communicator—executive presence, crisp storytelling, and the ability to translate complex technical concepts into actionable business strategy.
Familiarity with large datasets, ML modeling, and modern AI patterns (LLMs, RAG, vector databases, embeddings, prompt/response optimization, agents & tools).
Practical understanding of evaluation and safety for LLM/ML solutions (offline/online testing, adversarial testing, guardrails, telemetry, policy enforcement).
Comfortable with analytics scripting (Python/R preferred) and data/ML platforms (e.g., Azure, AWS, Databricks/Snowflake, MLflow, feature stores, CI/CD).
Deep experience with Agile at scale and TBM/portfolio practices; adept at structuring multi horizon investment cases and benefits realization.
Payments/financial services experience preferred (PCI, data privacy, model risk management, compliance).
Bachelor’s degree in Computer Science, Engineering, or related; Master’s preferred—or equivalent practical experience.

Benefits

insurance (including medical, prescription drug, dental, vision, disability, life insurance)
flexible spending account and health savings account
paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave)
80 hours of Paid Sick and Safe Time
25 days of vacation time and 5 personal days, pro-rated based on date of hire
10 annual paid U.S. observed holidays
401k with a best-in-class company match
deferred compensation for eligible roles
fitness reimbursement or on-site fitness facilities
eligibility for tuition reimbursement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

AIdata engineeringsolution architectureLLMsRAGagentic automationanalyticsML modelingPythonAgile

Soft skills

leadershipcommunicationstorytellinginfluencingalignmentcollaborationproblem-solvingrelationship buildingchange managementtransparency

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in EngineeringMaster’s degree in related field