Artificial Intelligence

• Lead the enterprise AI Program Office within the Office of the CTO
• Orchestrate enterprise-wide AI adoption, governance, risk assurance, and cost management
• Architect, operationalize, and maintain the enterprise AI governance framework
• Author and maintain the AI Acceptable Use Policy, SOPs, data-handling guardrails, and role-based permissions
• Translate policy into automated technical guardrails using API gateways, connector permissions, endpoint access rules, and usage quotas
• Monitor AI governance frameworks and legal mandates and adapt internal compliance controls
• Own the registry of sanctioned AI models, platforms, and API connectors
• Manage intake and evaluation of new AI tools and capabilities
• Identify and mitigate unsanctioned shadow AI tools and integrations
• Run risk assessments for AI use cases, prompts/fine-tunes, and third-party integrations
• Maintain governance artifacts including impact assessments, model cards, audit logs, and exception approvals
• Partner with Information Security, Legal, Privacy, and Quality/Regulatory Affairs
• Validate control effectiveness, address audit findings, and support customer and regulatory inquiries
• Define AI usage thresholds, token quotas, and department-level spend caps
• Build enterprise AI visibility reporting for usage, token efficiency, licenses, and latency
• Operate cross-business-unit chargeback and showback mechanisms
• Lead enterprise AI adoption programs and prioritize high-ROI use cases
• Define KPIs and report program health to the CTO and executive leadership
• Manage strategic technology and AI vendor relationships, agreements, renewals, and performance reviews
• Negotiate BAAs, zero-data-retention terms, license tiers, and performance SLAs
• Drive AI fluency through role-based curricula, prompt-engineering playbooks, and office hours
• Advise department heads and product teams on practical, compliant AI implementations
• Promote responsible AI adoption with change management and communications teams
• Follow safety, privacy, compliance, confidentiality, and attendance standards

Associate Director, AI Program Office – AI Office Lead

• Lead the enterprise AI Program Office within the Office of the CTO
• Orchestrate enterprise-wide AI adoption, governance, risk assurance, and cost management
• Architect, operationalize, and maintain the enterprise AI governance framework
• Author and maintain the enterprise AI Acceptable Use Policy, SOPs, data-handling guardrails, and role-based permissions
• Translate policy into automated technical guardrails using API gateways, connector permissions, model endpoint access rules, and usage quotas
• Monitor AI frameworks and legal mandates and adapt internal compliance controls
• Own and curate the registry of sanctioned AI models, platforms, and API connectors
• Manage intake and evaluation of new AI tools and capabilities
• Identify, monitor, and mitigate unsanctioned shadow AI tools and integrations
• Run risk assessments for AI use cases, internal prompts/fine-tunes, and third-party AI integrations
• Maintain governance artifacts including algorithmic impact assessments, model cards, audit logs, and exception approvals
• Validate control effectiveness, address audit findings, and support customer and regulatory inquiries
• Define token allocation quotas, usage thresholds, and department-level spend caps
• Build AI visibility reporting for usage, token efficiency, license utilization, and latency metrics
• Design and operate cross-business-unit chargeback and showback mechanisms
• Lead enterprise AI adoption programs and prioritize use cases across clinical operations, corporate functions, and engineering
• Define KPIs, measure outcomes, and report program health to the CTO and executive leadership
• Manage strategic technology and AI vendor relationships, enterprise agreements, BAAs, data-retention terms, license tiers, and performance SLAs
• Manage contract renewals and vendor performance reviews
• Drive enterprise AI fluency through role-based curricula, prompt-engineering playbooks, and office hours
• Advise department heads and product teams on practical, compliant AI implementations
• Promote responsible AI adoption with change management and communications teams

• Define and own a 5+ year enterprise applied AI vision, strategy, capability roadmap, and investment portfolio
• Set enterprise priorities across patient engagement, customer service, sales operations, marketing effectiveness, provider engagement, market access, digital, operations, and enterprise productivity
• Translate enterprise challenges into AI opportunities, investment theses, product portfolios, experiments, MVPs, and scaled capabilities
• Present AI strategy, portfolio choices, investment recommendations, value realization, and risk assessments to the CTO, ELT, and senior business leaders
• Establish portfolio-level value cases and outcome measures with Finance and business executives
• Own applied AI products and capabilities from discovery and prioritization through deployment, adoption, and lifecycle management
• Establish product operating mechanisms, decision rights, roadmaps, funding priorities, and governance
• Scale reusable AI capabilities including recommendations, segmentation, forecasting, copilots, AI agents, and workflow automation
• Drive AI integration into CRM, service platforms, field tools, dashboards, digital experiences, and business operating rhythms
• Lead responsible AI deployment, governance, risk assessment, human oversight, auditability, output validation, content safety, escalation, and accountability
• Build, lead, and develop a multi-layer organization across product, data science, AI engineering, analytics, and cross-functional delivery
• Define the operating model, organizational capabilities, talent strategy, workforce plan, and leadership structure
• Influence enterprise business and technology strategy with executive and cross-functional leaders
• Lead enterprise change and adoption strategies embedding AI into workflows, leadership routines, capability building, and decision-making

Senior Director, Applied AI

• Own the design, development, operation, and continuous improvement of strategic sales intelligence products and solutions
• Translate business strategies into requirements, priorities, metrics, business rules, and data model designs
• Analyze sales performance to identify opportunities, risks, root causes, and recommended actions
• Build or guide scalable analytics solutions, dashboards, semantic models, and automated reporting capabilities
• Establish validation, documentation, monitoring, and change controls
• Manage product roadmaps and multiple initiatives while balancing immediate business needs with long-term scalability
• Drive implementation, adoption, feedback collection, and continuous enhancement of capabilities
• Contribute directly to analysis and solution development while providing leadership across major initiatives
• Coach and mentor analysts, data scientists, developers, and project contributors
• Partner with Sales, Strategy, Operations, Data, and Technology teams
• Present complex insights, recommendations, and requirements to technical, business, and executive audiences
• Evaluate and apply emerging analytical methods, automation technologies, and AI capabilities

Manager, Sales Intelligence – AI Strategy

• Gather client networking requirements and design optimized solutions using diverse vendors and technologies
• Design, implement, and maintain high-throughput, low-latency network architectures for HPC and AI clusters
• Deploy new HPC/AI solutions or augment existing solutions from the ground up
• Maintain knowledge of multiple Network Operating Systems, such as Cumulus Linux and SONIC
• Configure and optimize switches, routers, and firewalls for HPC and AI workloads
• Monitor network performance and troubleshoot connectivity, latency, and security problems
• Implement and maintain network security measures, including firewalls, intrusion detection systems, and secure access protocols
• Document network configurations, procedures, and troubleshooting steps
• Consult on and assist with day-to-day management of clients’ research computing infrastructure
• Maintain HPC and AI infrastructure in Linux-based environments
• Lead technical discussions and represent Cambridge Computer to clients during engagements
• Validate solution designs, meet client requirements, and confirm technical feasibility and deployability
• Scope professional services deliverables and set clear client expectations
• Build documentation and provide client knowledge transfer
• Advise on networking, storage, data protection, digital archiving, and other infrastructure technologies
• Develop advanced expertise in and certifications from vendors used in Cambridge Computer’s solution stack

HPC / AI Network Technologist

• Lead a multidisciplinary team of scientists and engineers developing real-time computer vision and deep learning solutions for X-ray imaging on constrained hardware
• Own delivery of the Expedite ML roadmap, including technical direction, execution, team development, and stakeholder representation
• Explore Expedite sensors, algorithms, product architecture, and data pipeline
• Establish execution cadence through sprint planning, milestone tracking, and risk management
• Gather product requirements and translate them into derived requirements for ML development
• Provide hands-on technical guidance on X-ray computer vision, deep learning, model architecture, and evaluation
• Assess team structure and skills and propose hiring and development plans
• Deliver roadmap milestones with production models deployed at the edge
• Manage, mentor, recruit, interview, onboard, and develop ML scientists and engineers
• Own project planning, scheduling, resourcing, risk management, and delivery for Expedite ML workstreams
• Lead stakeholder meetings with product, hardware, software engineering, regulatory, and executive audiences
• Coordinate cross-functional dependencies with product, hardware, software engineering, and SQA
• Enable rapid development through prioritization, planning, and automation
• Engage in customer demonstrations and proof-of-concept exercises
• Set technical direction for X-ray computer vision and machine learning initiatives
• Guide novel algorithms using X-ray imagery and multi-sensor inputs
• Recommend and implement model training, validation, and deployment best practices for production edge systems
• Review technical designs and results and unblock the team on key decisions
• Stay current with ML developments and improve X-ray sensing capabilities
• Inform AI and sensor initiatives at the executive level
• Report directly to the VP of ML and Sensors and interface with cross-disciplinary R&D teams

Senior Manager – AI/ML, Sensors

• Own Merlin's foundation and world-model technical strategy, including architecture selection, build-vs-adapt decisions, post-training approach, and capability roadmap
• Lead and mentor a small team of world-model and post-training engineers
• Set the technical bar and review culture for model work across AI Core
• Design the model interface to the autonomy stack using structured, schema-constrained plan outputs accepted or rejected by a deterministic verifier
• Define evaluation criteria before training begins
• Build the evaluation harness, capability taxonomy, and regression suite for model releases
• Establish uncertainty quantification and out-of-distribution detection as first-class model outputs
• Deliver reproducible comparisons between learned planning and current rule-based behavior planning across representative mission profiles
• Partner with Systems Engineering, Certification, and the Chief Architect on regulator-defensible model design
• Track external research and decide what Merlin adopts, builds, or ignores

Senior Manager, AI Foundation Model

• Assist Relationship Sales Managers with daily tasks
• Research hardware, software, and services offerings
• Write quotes, build proposals, and manage statements of work to maximize company profit
• Communicate with vendors and clients
• Coordinate online meetings, technical demonstrations, and conferences
• Manage sales and order logistics
• Recommend products and upsell solutions
• Populate and maintain CRM tools with accurate and timely information
• Manage positive vendor relationships
• Drive lead generation through prospecting, client calls, and follow-up on marketing initiatives
• Participate in trade shows and act as a company representative
• Liaise between the corporate office and remote employees
• Gain vendor product knowledge and certifications
• Build familiarity with storage, networking, data protection, digital archiving, and infrastructure technology trends
• Understand high-performance computing, machine learning, artificial intelligence, bioinformatics, and life sciences solutions
• Execute corporate and sales management goals and objectives

Sales Support – Enterprise Technology, HPC, AI, ML

• Own the AI use-case agenda, including identifying and analyzing high-value business problems and assessing their suitability for AI-driven solutions
• Lead intake, review, prioritization, and governance of AI use cases
• Design and refine a standardized AI enablement framework to scale experimentation into enterprise execution
• Establish repeatable processes that accelerate delivery while maintaining rigor and governance
• Coordinate and lead AI, digital, and automation initiatives across Alpha Services
• Run proofs of concept and shepherd ideas through real-world implementation
• Partner with senior management and product leadership to shape AI strategy and investment priorities
• Distill complex technical and analytical topics into actionable insights for executive audiences
• Own and grow relationships with internal and external partners
• Craft strategic alliances to expand Alpha’s AI capabilities and speed to market
• Define methods to track execution and outcomes
• Capture lessons learned and embed feedback loops
• Maintain deep knowledge of State Street’s end-to-end product offerings
• Provide consultative guidance across the organization
• Partner with Sales to lead go-to-market efforts for new AI-enabled solutions

AI Initiatives Lead, VP

• Oversee and manage change management processes for AI, digital, and technology advances across Project & Portfolio Management and the Development Asset Leads organization
• Develop and implement change management strategies for AI initiatives, Planisware enhancements, workflow automation, and process and resource changes
• Collaborate with IT and business units to assess impacts on roles, handoffs, decision points, and data-entry expectations
• Lead stakeholder engagement, communications, role-based training, job aids, office hours, and communities of practice
• Monitor change impact and organizational readiness and address resistance to change
• Build and manage change champion networks across Program Management, Program Planning, Development Asset Leads, and broader Development functions
• Define, monitor, and report adoption metrics, user engagement indicators, value realization measures, and solution performance KPIs to leadership
• Promote responsible AI adoption by explaining appropriate use, limitations, human review requirements, governance expectations, and compliance obligations
• Coordinate user acceptance testing, release readiness, go-live support, and post-implementation adoption monitoring
• Translate AI-enabled capabilities into measurable business value across drug development operations

Artificial Intelligence jobs in Massachusetts

Associate Director, AI Program Office – AI Office Lead

Associate Director, AI Program Office – AI Office Lead

Senior Director, Applied AI

Manager, Sales Intelligence – AI Strategy

HPC / AI Network Technologist

Senior Manager – AI/ML, Sensors

Senior Manager, AI Foundation Model

Sales Support – Enterprise Technology, HPC, AI, ML

AI Initiatives Lead, VP

AI Adoption, Change Management Specialist