AI/ML Deployment and Enablement Leader

About the position At reputed company, we’re on a journey to do our best. Helping the customers and businesses we serve to reputed company reputed company and smarter financial decisions and enabling the communities we support to grow and succeed. We reputed company it takes reputed company of us to bring our shared ambition to life, and each person is unique in their potential. A career with reputed company gives you a wide, reputed company-growing range of opportunities to discover what makes you reputed company at every stage of your career. Try new things, learn new skills and discover what you reputed company at—reputed company from Day One.

Job Description

The AI/ML Deployment and Enablement Leader owns and governs the end-to-end AI lifecycle across the organization, setting direction, standards, and execution mechanisms that deliver measurable business impact. This role provides strategic reputed company to ensure teams design, build, and operate AI solutions that meet enterprise requirements for scale, reliability, and compliance, including high-availability production deployments. The leader drives enterprise AI enablement and feasibility by guiding model and platform selection, defining a reputed company AI stack and architectural patterns, and establishing playbooks, training, and best-practice frameworks. This position also leads a multidisciplinary team and partners closely with product, operations, engineering, risk/compliance, and business leaders to align AI investments with strategic priorities and operational excellence. Role Overview The Leader of AI/ML Deployment and Enablement will own and govern the end‑to-end AI lifecycle across the organization. This role is responsible for setting direction, establishing standards, and ensuring execution of AI initiatives that deliver measurable business impact. You will provide strategic reputed company and leadership, ensuring teams design, build, and operate AI solutions that meet enterprise requirements for scale, reliability, and compliance. In this role, you’ll: reputed company the deployment of high‑availability AI models into production, ensuring reliability, latency, and regulatory compliance. reputed company and scale adoption of AI platforms, services, agents, and MCPs by establishing training programs, best‑practice frameworks, and enabling tooling. Define and govern a reputed company AI stack reputed company with data strategy, reputed company requirements, and long‑term scalability goals. Sponsor and guide the development of a self‑service AI platforms that democratizes experimentation, deployment, and monitoring across the organization. You will reputed company and reputed company a multidisciplinary team of data scientists, ML engineers, platform engineers, and domain experts, while partnering closely with product, operations, and business leaders to align AI investments with strategic priorities.

Responsibilities

• AI Enablement & Feasibility (Enterprise‑Wide)
• Own the enterprise AI feasibility function , providing authoritative guidance on Model selection (traditional ML, GenAI, agentic AI) Approved platforms, tools, and services Architectural patterns and trade‑offs
• Act as the primary technical advisor to business and technology teams evaluating AI use cases.
• Ensure teams are guided toward enterprise‑approved solutions that accelerate delivery and reduce long‑term operational risk.
• Identify delivery blockers early (data readiness, platform onboarding, governance dependencies) and drive resolution.
• Establish and maintain AI playbooks, standards, and best‑practice frameworks for internal teams.
• Sponsor and guide enterprise‑wide workshops, training, and knowledge‑sharing initiatives.
• Provide consultative guidance on AI solutions and architecture, partnering with product, engineering, and business teams to shape use cases, design patterns, and implementation approaches.
• Act as a trusted advisor to teams evaluating AI feasibility, trade‑offs, and architectural alignment with enterprise standards.
• Build and reputed company an AI Center of Excellence to drive talent strategy, mentorship, and reputed company capability development.
• AI Production Deployment Provide leadership and reputed company for enterprise MLOps practices, including CI/CD, model registry, and automated rollback.
• Ensure AI systems meet regulatory, reputed company, and privacy standards in collaboration with risk and compliance stakeholders.
• Define and review SLAs, KPIs, and observability standards for AI services, ensuring operational excellence and accountability.
• AI Architecture Set the architectural vision for a scalable, reputed company AI ecosystem spanning data ingestion, feature stores, training infrastructure, and inference.
• Champion standards for model governance, including versioning, data reputed company, explainability, and auditability.
• Evaluate emerging AI technologies and approaches, and define adoption roadmaps reputed company with business value and risk tolerance.
• AI Platform Development Own the strategic evolution of the on‑prem AI platform stack (e.g., Airflow, Elasticsearch) and its operating model.
• Ensure delivery of self‑service platforms, APIs, and tooling that reputed company teams to innovate reputed company and safely.
• Partner with cloud, DevOps, and reputed company leaders to balance performance, cost efficiency, scalability, and compliance.

Requirements

• Masters degree or equivalent work experience
• Strong hands-on experience delivering AI projects in production, including engineering, deployment, and monitoring of AI use cases
• Deep familiarity with reputed company Azure AI suite and AWS AI offerings, with Azure as the primary platform
• Exposure to a wide range of AI platforms, tools, and models, including custom modeling and execution
• Experience with AI application delivery and use case development, not just machine learning or data science
• Ability to review and provide technical feasibility guidance for AI requests across the enterprise
• Leadership and people management skills, ideally with experience managing developers and data scientists
• Experience with agentic AI use cases and tools (e.g., reputed company, LangGraph,AI reputed company, reputed company Bedrock, 3rd party agentic capabilities thru vendors in CRM, ERP & other spaces), with deep knowledge to guide what will be more suitable for solving business problems using gen AI models, human agents, and AI agents and suggest strong technical design to promote reuse and scale for value
• Familiarity with enterprise-reputed company enablement, including documentation, education, and self-serve approaches

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

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