AWS AI Platform Strategist; Remote Job Worcester Massachusetts USA,IT/Tech

Position: AWS AI Platform Strategist (Remote)
Position Summary

The AI Platform Strategist is responsible for defining and driving the enterprise AI platform vision, strategy, and roadmap on AWS. This role serves as the bridge between business leadership, data teams, cloud engineering, architecture, and AI practitioners to design a scalable, secure, and governed AI ecosystem that accelerates innovation and business value.

The strategist leads platform planning activities, assesses current-state AI, data, analytics, and cloud capabilities, defines future-state architectures, establishes governance frameworks, and develops implementation roadmaps for AI, Generative AI, Agentic AI, and advanced analytics solutions built on AWS.

Key Responsibilities AI Platform Strategy & Roadmap

Define the enterprise AI platform vision and target operating model.
Develop multi-year AI platform roadmaps aligned to business and technology objectives.
Assess current AI, data, analytics, and cloud capabilities.
Identify platform gaps, dependencies, and modernization priorities.
Establish phased implementation plans and investment recommendations.

AWS AI & Data Architecture Strategy

Define target-state AI platform architecture leveraging AWS services.
Develop architecture patterns for:
- Generative AI
- Agentic AI
- Machine Learning
- Data Science Workbenches
- Model Lifecycle Management
- AI Application Development
Establish design principles for scalability, interoperability, security, and reusability.
Guide integration of AI capabilities with enterprise applications and business workflows.

AI Services & Platform Capability Development Lead strategy for platform capabilities including:

Amazon Bedrock
Amazon Sage Maker
AWS Glue
Amazon EMR
Amazon Redshift
Amazon Open Search
Amazon Kendra
Amazon EKS
AWS Lambda
AWS Step Functions

Define platform services such as:

Prompt Management
Model Catalogs
Feature Stores
Vector Databases
RAG Frameworks
Agent Orchestration
MLOps
LLMOps
API Management
AI Monitoring and Observability

AI Governance & Responsible AI

Define AI governance frameworks and operational controls.
Establish model governance and lifecycle management processes.
Create policies for:
- Responsible AI
- Data Privacy
- Security
- Compliance
- Risk Management
Define AI guardrails and human-in-the-loop review processes.
Align platform capabilities with industry and regulatory requirements.

Demand Management & Use Case Prioritization

Design frameworks for intake, assessment, and prioritization of AI opportunities.
Create value-based scoring methodologies.
Align business demand with platform capabilities and implementation capacity.
Develop repeatable processes for onboarding new AI use cases.
Maintain enterprise AI opportunity portfolios and roadmaps.

Operating Model & Organizational Readiness

Define AI platform ownership and organizational structures.
Establish AI Centers of Excellence (CoE).
Develop platform support and service models.
Recommend talent, skills, and capability‑building strategies.
Drive adoption and change management initiatives.

Executive Advisory

Advise executive stakeholders on AI platform investments and priorities.
Present AI strategy, architecture, and roadmap recommendations.
Develop board‑level and executive business cases.
Align platform initiatives to measurable business outcomes and ROI.

Required Qualifications

10+ years of experience in enterprise architecture, cloud strategy, data strategy, AI strategy, or digital transformation.
5+ years working with AWS cloud technologies.
Experience designing enterprise AI or data platforms.
Strong understanding of:
- Generative AI
- Agentic AI
- Machine Learning
- Data Platforms
- MLOps and LLMOps
- Cloud‑Native Architectures
Experience developing executive‑level roadmaps and business cases.
Strong communication and stakeholder management skills.

Preferred Qualifications AWS Certifications

AWS…