AI Platform Architect

Role Overview

• Lead technical workshops to identify, refine, and prioritize high-impact AI and GenAI use cases aligned with business objectives.
• Translate business problems into system design requirements and AI workflows.
• Assess existing data platforms, pipelines, governance, and accessibility for AI workloads.
• Evaluate data quality, lineage, security, and suitability for training, RAG, and inference patterns.
• Design AI architectures that comply with enterprise security, privacy, and regulatory constraints (PII, PHI, internal policies).
• Evaluate and design integrations across APIs, event streams, and existing systems.
• Evaluate and recommend foundation models and AI services, including Amazon Bedrock, Amazon Nova, and open-source models.
• Analyze tradeoffs across cost, latency, accuracy, and scalability.
• Design GenAI patterns such as RAG, agent workflows, and inference pipelines.
• Produce high-level and detailed AWS reference architectures for prioritized AI use cases.
• Define phased implementation roadmaps that balance speed, risk, and long-term maintainability.
• Identify PoC scope that can be executed within a short engagement.
• Partner with stakeholders to develop ROI and TCO models for AI initiatives.
• Provide cost modeling for model usage, data pipelines, infrastructure, and operations.
• Deliver AI assessment findings and recommendations.
• Create target-state AI platform architecture diagrams.
• Summarize data readiness and compliance assessments.
• Provide model evaluation and selection rationale.
• Define phased implementation roadmap.
• Design and validate PoC.
• Prepare executive-ready presentations and documentation.

Requirements

• 8+ years in Cloud, Platform, SRE, or Infrastructure Engineering roles
• Proven experience operating at an Architect level
• Strong client-facing and consultative experience
• Deep hands-on experience with AWS, including multi-account architectures and governance
• Strong knowledge of infrastructure as code (Terraform preferred)
• Experience designing secure, scalable platforms in AWS Organizations environments
• Practical experience with AI/ML platforms, preferably AWS-native (Bedrock, SageMaker, Glue, Athena, OpenSearch)
• Experience with GenAI architectures (RAG, embeddings, vector stores, agent frameworks)
• Familiarity with model evaluation, prompt engineering, and inference optimization
• Understanding of AI cost drivers and scaling considerations
• Strong grounding in SRE principles, observability, reliability, and operational excellence
• Experience designing production-ready systems with monitoring, alerting, and security baked in
• Ability to lead workshops, whiteboard architectures, and influence senior stakeholders
• Comfortable translating complex technical concepts into business-level narratives
• Strong written documentation and presentation skills
• Experience delivering AI assessments or AI strategy engagements
• Background in regulated industries (Healthcare, Fintech, Enterprise SaaS)
• AWS Certified Solutions Architect – Professional
• Experience building internal platforms or AI enablement frameworks

Tech Stack

• AWS
• Cloud
• Terraform

Benefits

• Health insurance
• 401(k) matching
• Paid time off
• Remote work options
• Professional development opportunities