Senior Director, AI Deployment

Adelphi Group•New York, NY

2d•Hybrid

About The Position

Omnicom Health is seeking a highly technical, client-oriented Senior Director, AI Deployment to lead implementation and scaling of AI-enabled solutions across its healthcare agencies and clients. The role sits at the intersection of AI, technology, data, creative, and client delivery, translating business and client needs into practical AI solutions, architectures, workflows, and implementation plans. It supports AI initiatives from prototype through production and adoption. Working in a highly matrixed organization, this position partners across Omnicom Health agencies and capabilities to assemble technical, strategic, creative, data, and client expertise for each engagement. It also helps establish deployment standards and governance aligned with Omnicom’s operating model, healthcare-industry requirements, and individual client policies and technology environments. The role calls for strong technical fluency, pragmatic delivery leadership, and comfort working with engineers, agency teams, client technology organizations, and senior business stakeholders. The Senior Director leads deployments of generative AI, agentic AI, machine learning, advanced analytics, and AI-enabled workflows; provides technical and delivery leadership; supports governance and responsible AI practices; and serves as a senior partner to clients and cross-functional teams. Success includes moving priority initiatives into scalable production, establishing repeatable deployment practices, balancing enterprise and client requirements, and delivering measurable adoption, workflow improvement, and business value.

Requirements

At least 7 years of experience across AI engineering, software engineering, data science, machine learning, solution architecture, technical consulting, or related disciplines.
At least 3 years leading complex technology implementations or multidisciplinary technical teams.
Demonstrated experience moving AI or machine learning solutions from prototype into production.
Strong working knowledge of generative AI and LLMs, agentic architectures, RAG, knowledge systems, APIs and integrations, cloud architectures, MLOps, data engineering, and AI evaluation.
Experience with Azure, AWS, Google Cloud, or multi-cloud environments.
Strong technical proficiency with Python and modern software development practices.
Experience operating within complex, matrixed organizations and influencing teams without direct reporting authority.
Strong client-facing, stakeholder-management, problem-solving, and communication skills.

Nice To Haves

Experience in pharmaceutical, biotechnology, healthcare, or life sciences.
Experience deploying technology within regulated or highly governed environments.
Familiarity with healthcare data, privacy, medical/legal/regulatory review, and responsible AI considerations.
Experience with healthcare marketing, commercial strategy, omnichannel engagement, content operations, personalization, or customer experience.
Consulting, professional services, agency, systems integration, or forward-deployment experience.
Experience scaling AI capabilities across multiple business units, agencies, brands, or clients.

Responsibilities

Lead end-to-end deployment of generative AI, agentic AI, machine learning, advanced analytics, and AI-enabled workflows from discovery and prototype through production.
Translate business and client requirements into solution architectures, implementation roadmaps, integration requirements, and operating models.
Guide deployment of AI agents, copilots, knowledge systems, decision-support tools, and workflow automation.
Provide hands-on technical leadership across architecture reviews, model evaluation, integrations, testing, troubleshooting, and production readiness.
Partner with platform, engineering, data, security, and infrastructure teams to leverage shared capabilities and accelerate deployment.
Develop reusable architectures, components, playbooks, and deployment approaches that can scale across agencies and clients.
Coordinate cross-agency teams across technology, data, strategy, creative, analytics, product, operations, account management, and client leadership.
Balance enterprise standards and reusable capabilities with the distinct needs of individual agencies, brands, and client organizations.
Build relationships with agency and enterprise leaders to identify dependencies, resolve challenges, and accelerate adoption.
Translate AI governance, security, privacy, and technology standards into practical requirements for deployments.
Work with legal, privacy, security, compliance, medical/regulatory, and technology stakeholders to establish governance throughout the solution lifecycle.
Adapt implementation and governance approaches to healthcare and pharmaceutical requirements, including regulated data, content, workflows, and medical/legal/regulatory considerations.
Reconcile Omnicom standards with client requirements, technology environments, policies, and risk tolerances.
Establish evaluation, testing, documentation, monitoring, human oversight, and escalation processes for deployed AI solutions.
Serve as a senior technical and delivery partner to clients, explaining complex AI concepts and technical trade-offs in clear business terms.
Lead discovery sessions, solution workshops, technical reviews, implementation planning, and deployment workstreams.
Coordinate multidisciplinary teams, including solution architects, engineers, data scientists, creative technologists, product teams, and delivery leads.
Manage dependencies, risks, resources, and priorities across concurrent AI initiatives.
Define success measures and ensure deployments are designed for adoption and measurable business impact.
Support business development by assessing opportunities, shaping solutions, and defining scopes, resource needs, and deployment approaches.