Artificial Intelligence

• Turn AI transformation ambition into adoption that sticks
• Operationalize the business case, outcomes, and partnerships
• Partner closely with technical leads to ensure adoption
• Build change narratives for affected stakeholders
• Own the initiative plan and track progress against goals
• Produce clear, honest status for stakeholders and governance forums

Director, AI Change Adoption

• Maintain strong awareness of the rapidly evolving AI ecosystem
• Translate new AI capabilities into practical engineering patterns
• Accelerate adoption of the enterprise AI platform across engineering teams
• Ensure experimentation leads to reusable capabilities rather than isolated prototypes
• Provide a clear feedback loop to the AI Platform organization on emerging needs
• Continuously evaluate emerging AI technologies and techniques that can meaningfully improve enterprise AI systems
• Develop prototypes and reference implementations that validate new AI approaches
• Translate experimentation into practical assets that accelerate the development of production AI systems across the organization
• Help engineering teams adopt AI capabilities effectively

VP, AI Innovation – Enablement

• Own internal adoption of Claude Enterprise and every custom workflow our specialist partners ship. Train users across the firm, both the technically fluent and the technically reluctant, on what is available, how to use it well, and where AI fits in their day.
• Bridge technical and non-technical team members. Help senior team members who do not write code see how AI can change their workflows. Help technical team members get past the rough edges and into productive use.
• Operate the workflows in production: monitor usage, gather user feedback, triage bugs and feature requests, surface them to our specialist partners with the context they need, and close the loop with users when fixes ship.
• Light technical work: write small Python scripts and Excel automations where they bridge a gap or unblock a workflow. Debug AI skills when they misbehave. Maintain the shared workspace structures the AI tools depend on.
• Manage the Claude Enterprise account: seat management, settings, billing reconciliation, access controls, security policy compliance with our IT partners, and quarterly platform reviews with our specialist partners.
• Surface the next wave of opportunities by being embedded with the team long enough to see where time is being wasted. Propose ideas; help scope and prioritize them.
• Represent Bridgepoint in working sessions with our outside AI specialists: translate business needs into technical asks, and translate technical proposals back into business outcomes.
• (For the right candidate) coordinate with firm leadership and the AI specialists to help build and implement new workflows, not as the lead developer, but as the connective tissue between what the firm needs and what gets built.

AI Operations Manager

• Scope and lead AI-driven strategic projects across growth and case automation workstreams
• Translate complex operational workflows into structured, executable plans — from diagnosis through delivery
• Partner with product, engineering, and SMEs to identify and prioritize high-leverage automation opportunities
• Build the analytical and operational frameworks that help the team measure what's working
• Serve as a key interface between execution teams and senior business stakeholders — translating between the two without losing fidelity in either direction
• Drive cross-functional alignment on initiatives that don't fit neatly into a single team's roadmap

AI Strategic Projects

• Lead the execution of Guardian’s AI governance program across analytics, AI, and agentic use cases.
• Implement enterprise AI governance policies, standards, and guardrails in alignment with defined risk appetite and regulatory expectations.
• Own the AI governance operating model, including intake, review, escalation, monitoring, and change management processes.
• Govern AI model lifecycles and AI system behaviors across models, copilots, agents, and RAG workflows, including retrieval strategies, tool use, actions, and human ‑ in ‑ the ‑ loop requirements.
• Operationalize governance standards for AI development, deployment, monitoring, and retirement.
• Serve as the primary AI governance partner to data science, analytics, engineering, and product teams.
• Define and track operational KPIs for AI governance execution, including coverage, exceptions, monitoring effectiveness, and remediation trends.
• Provide leadership to AI governance practitioners and analysts; set priorities, manage workload, and build governance expertise.

Head of AI Governance

• 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

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Vice President, AI & Data Strategy

• Serve as a dedicated resource for Banking & Credit lawyers by providing responsive, high-touch support in building, refining and optimizing AI prompts and workflows tailored to practice-specific transactions and workstreams
• Proactively identify, evaluate and guide the adoption of AI-enabled workflows tailored to practice-specific needs and desired outcomes; educate lawyers on where and how AI can add value to their practice
• Partner with the KM Counsel and the practice’s AI Partner Champion to develop and execute change management strategies to drive sustained adoption of AI within the practice group
• Collaborate with technical team members to articulate and translate legal reasoning and practice-specific logic into executable AI workflows
• Review and evaluate AI outputs using legal first principles; refine prompts and workflow steps to improve quality and alignment with practice expectations
• Support adherence to the Firm’s AI policies and applicable professional responsibility standards by advising lawyers on ethical and risk considerations in AI use including confidentiality, privilege, data privacy and output reliability
• Build and maintain datasets, test sets, and evaluation frameworks for use in POCs and pilots and ongoing solution development
• Conduct structured testing to ensure accuracy, consistency, and defensibility of AI‑enabled workflows
• Develop, implement and maintain procedures for the consistent review, documentation and dissemination of use cases and prompts
• Oversee the governance and lifecycle management of AI knowledge assets including prompts, prompt libraries, workflows, document collections and vaults by establishing and enforcing quality standards, conducting periodic reviews to ensure accuracy and relevance, and coordinating the retirement or updating of outdated materials
• Collaborate with other support professionals within K&I and the Legal Talent team to design, prepare, and deliver the Firm’s AI curriculum, including trainings, workshops, and best‑practice resources (e.g., prompt libraries, tip sheets, and use‑case guides)
• Share successful use cases, prompt templates and best practices across other practice groups to promote firm-wide consistency, reduce duplication of effort and accelerate AI adoption across the Firm
• Evaluate, test, and provide structured feedback on new AI technologies being considered by the Firm, including participating in demonstrations, proof of concepts, and pilots; assess vendor tools against practice-specific criteria and communicate findings to the Applied Analytics & AI and/or Practice Solutions teams and relevant stakeholders
• Monitor developments in AI, legal technology, and the Banking & Credit practice area and continuously identify opportunities to leverage AI for process improvement, matter efficiency and enhanced client service
• Provide additional knowledge support to the practice as assigned by the Practice Group Co‑Chairs, Chief Knowledge & Innovation Officer, Knowledge Management Director or KM Counsel/Senior KML

Knowledge Management AI Lawyer – Banking, Credit

• End-to-end AI deployments — design, test, and roll out browser/phone agents and document extraction (OCR + agentic AI) that automate authorization, verification, and intake workflows
• Workflow-to-spec translation — turn complex payer and clinical workflows into clear technical specs the AI can execute
• Output quality — measure accuracy, find where deployments fail, and drive them toward reliability ruthlessly
• Playbooks — document prompt and deployment strategies so they're reproducible and scale across states and payers
• The AI roadmap — prioritized, defended, and executed with conviction
• Metrics — define what "working" means and prove it

AI Deployment Manager

• Lead delivery of CHAI’s AI clinical decision support and agentic healthcare delivery initiatives end-to-end
• Own the program's forward view: track the frontier of clinical and agentic AI
• Forge and maintain relationships with the Ministry of Health
• Evaluate adjacent health system factors affecting initiative’s impact
• Directly manage at least one Senior Associate / Manager / Sr. Manager
• Own status reporting and stakeholder communications for senior CHAI leadership and external partners
• Anticipate and prepare for scale: regulatory pathways, infrastructure dependencies, workforce readiness
• Provide informed technical support as needed
• Travel internationally as needed (25-40% annually) and regularly within the US

Associate Director – AI Clinical Decision Support

• Lead discovery workshops to clarify business objectives, constraints, and measurable success criteria for AI/ML initiatives
• Translate requirements into end-to-end target-state architectures across data, ML/AI, application integration, security, and governance
• Define pragmatic tradeoffs across accuracy, latency, cost, reliability, privacy, and risk—and communicate decisions to exec and engineering audiences
• Design the data + model lifecycle and the required MLOps/LLMOps foundations
• Establish integration patterns with enterprise systems
• Partner with security, privacy, and risk teams to embed controls into solution designs
• Produce core delivery artifacts and drive architecture reviews
• Mentor teams and build reusable assets/accelerators

AI-ML Director

• Own the client-CEO relationship and the executive steering committee — as a peer, with real decision rights.
• Run the transformation cadence: weekly reviews, monthly finance-verified value reviews, and quarterly business reviews.
• Drive a fast, fixed-scope first win on the client's real data, then lead the full rollout (leadership first, then the wider team).
• Translate client problems into crisp, build-ready specs for remote engineers; own adoption and sign-off.
• Be personally accountable for a finance-verified outcome the client can see in their P&L.
• Build a portfolio of 2–3 marquee CEO accounts as each engagement matures.
• Own end-to-end rollout management — from kick-off through adoption, sign-off, and handover — ensuring every phase lands on time and to a measurable outcome.
• Codify the method after each deployment so the next one requires less ramp-up.

Client Deployment Lead, AI

• Work directly with customers to design, build, and deploy AI-powered planning solutions using Pigment.
• Translate business problems into models, deploy agentic AI solutions in production.
• Shape how organizations leverage Pigment to transform their planning processes.
• Collaborate closely with Customer Success, Solutions Architects, and Product teams.
• Train users and teams on Pigment features, modeling best practices, and scalable system design.

AI Deployment Strategist

• Drive the adoption and deployment of Mistral’s AI solutions, working closely with customers from strategic vision to production implementation.
• Partner with senior executives to design AI roadmaps and collaborate with the Applied AI team to deliver solutions in production.
• Ensure seamless transitions from presales to postsales, directly contributing to customer success.
• Lead executive-level workshops to identify business challenges and opportunities for AI improvements.
• Co-create AI adoption roadmaps with customers and collaborate with Account Executives to develop business cases.
• Architect end-to-end AI solutions and partner with the Applied AI team for successful deployment.
• Monitor key performance indicators tied to business outcomes and proactively identify expansion opportunities.

• Define and ship differentiated product capabilities for a prioritized set of customer and business use cases, with clearly documented success metrics (customer impact, adoption, revenue, efficiency, and risk reduction).
• Own the end-to-end product strategy and roadmap across platforms, applications, and AI-enabled capabilities, aligning firm-wide priorities and measurable outcomes.
• Establish scalable product operating models, including discovery, prioritization, roadmap governance, and delivery cadences across multiple product teams.
• Partner with Engineering and Architecture to ensure products are built on secure, resilient, and extensible platforms with clear technical and data foundations.
• Operationalize product lifecycle management including launch readiness, telemetry, adoption tracking, feedback loops, and continuous improvement.
• Hire, mentor, and lead a high-performing team of Product Managers across core platforms, workflows, and emerging AI capabilities.
• Partner with Knowledge Management, Data, and Engineering teams to translate domain workflows into product requirements, roadmaps, and prioritization frameworks.
• Work closely with Legal, Privacy, Security, and Compliance teams to ensure products meet confidentiality, regulatory, and risk management standards.
• Lead the full product lifecycle including problem framing, user research, requirements definition, delivery, launch, measurement, and iteration.
• Drive alignment across stakeholders including partners, business leaders, engineering leaders, and go-to-market teams.
• Establish and own product success metrics tied to customer outcomes, operational efficiency, and business performance.
• Lead change management and adoption efforts including training plans, playbooks, communications, and executive reporting.
• Publish and maintain product standards, decision frameworks, roadmap artifacts, and internal product guidance.

Director, Product AI – Platforms

• Translate strategic intent and architectural patterns into working AI solutions and platforms
• Own the end-to-end architecture and implementation shape of major solutions
• Lead technical design and execution across complex initiatives as architect, tech lead, and delivery driver
• Ensure seamless integration across platforms and services, data systems, AI models, and business workflows
• Direct day-to-day technical execution, review work to Pfizer's quality and security bar
• Identify and challenge incomplete or fragile architectures, solutions that are not production-ready
• Translate business problems into feasible, high-impact technical solutions

Director, Applied AI

• Shape and evolve enterprise or domain-level AI strategy, grounded in clear business value and transformation outcomes.
• Connect AI initiatives explicitly to measurable impact, and influence leadership on where AI should be applied and how it should reshape processes and operating models.
• Design and evolve enterprise AI operating models, the target technology landscape, and the relationships between platforms, capabilities, and embedded solutions.
• Create decision frameworks and architectural principles that drive consistent decisions across teams.
• Drive portfolio-level architectural decisions across initiatives, platforms, and reusable capabilities.
• Define and steward 'what good looks like' across AI architecture, solution design, and operational execution.
• Stay hands-on where it matters — architecture and code review with modern AI and agent frameworks.
• Lead a mixed team of full-time engineers, contractors, and vendor partners across one or more initiatives.
• Continuously assess emerging technologies, the vendor landscape, industry trends, and research.

Senior Director, Applied AI

• Provide critical expertise in AI-driven workforce development
• Act as the primary AI subject matter resource for the Responsible Business group
• Conduct assessments to identify job training needs related to AI fluency
• Curate, vet, and validate educational programs and external partner curriculums
• Collaborate with external partners for accurate delivery of AI skilling content
• Analyze performance toward defined goals and recommend changes
• Partner with internal Business Intelligence team for measurement framework
• Continuously monitor the field for emerging gaps in AI education
• Represent Verizon in external engagements or partnerships

Senior Manager, AI Workforce Development

• Lead end-to-end development for our AI platform and customer experiences, from initial roadmap to rollout.
• Partner with engineers to design prompt strategies, evaluation frameworks, and guardrails—balancing latency, cost, and accuracy.
• Serve as the technical translator between engineering and the broader organization, establishing AI best practices and platform standards.
• Drive systematic improvement in answer quality, customer satisfaction, and automation rates through rigorous experimentation.
• Work with partners at OpenAI to evaluate and deploy the next generation of voice models and workflow automation.

Manager, AI Agents and Platform

• Identify, prospect, and close new business opportunities.
• Sell our comprehensive suite of AI data solutions—including data collection, annotation, and generative AI services.
• Drive New Revenue: Exceed annual sales targets and expand TransPerfect’s AI footprint.
• Act as a subject matter expert, guiding clients through the complexities of AI data preparation.

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Director, AI Change Adoption

VP, AI Innovation – Enablement

AI Operations Manager

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Head of AI Governance

AI Engagement Manager

Vice President, AI & Data Strategy

Knowledge Management AI Lawyer – Banking, Credit

AI Deployment Manager

Associate Director – AI Clinical Decision Support

AI-ML Director

Client Deployment Lead, AI

AI Deployment Strategist

AI Deployment Strategist

Director, Product AI – Platforms

Director, Applied AI

Senior Director, Applied AI

Senior Manager, AI Workforce Development

Manager, AI Agents and Platform

Enterprise Solutions AI Consultant