AI Platform Architect
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Job Description
AI Platform Architect at EverOps guiding high-impact AI assessments and architectural designs. Collaborating with clients to deliver on AI initiatives and compliance frameworks.
Responsibilities:
- 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
Benefits:
- Health insurance
- 401(k) matching
- Paid time off
- Remote work options
- Professional development opportunities
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