VP, Solutions Architect - AWS
Robots and Pencils1 day ago
Remote, United StatesStaff+
Responsibilities
- Lead generative and agentic AI architecture for strategic clients from discovery through production deployment.
- Design AWS-native RAG, Agentic RAG, and multi-agent systems using Amazon Bedrock, AgentCore, serverless services, databases, and orchestration platforms.
- Produce reference architectures, architecture decision records, and implementation roadmaps aligned with business objectives.
- Validate architecture feasibility through hands-on Python prototyping with Bedrock SDKs, SageMaker, and serverless services.
- Own architectural integrity, security, governance, compliance, reliability, performance, sustainability, and cost optimization across AWS solutions.
- Create reusable AWS accelerators, infrastructure modules, and CI/CD automation using infrastructure-as-code tools.
- Provide architectural oversight to Forward Deployed Engineers and AWS delivery teams and mentor engineers on AWS AI integrations and distributed systems.
- Establish AWS MLOps, model lifecycle, monitoring, observability, responsible AI, and multi-account security practices.
- Advise clients and executives on model selection, latency, cost, governance, compliance, and AWS migration strategy.
- Support pre-sales workshops, solution scoping, and collaboration with product, engineering, research, customer success, and client stakeholders.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
- 10+ years of experience in software engineering or cloud architecture with deep AWS ownership.
- Deep expertise in Amazon Bedrock, Bedrock AgentCore, AWS Strands Agents, AgentCore Gateway, and related AWS AI services.
- Strong familiarity with SageMaker training, deployment, pipelines, deep learning fundamentals, and model fine-tuning strategies.
- Experience architecting RAG, multi-agent, orchestration, distributed, event-driven, and serverless systems.
- Proficiency with AWS CDK, CloudFormation, Terraform, Python, and AWS SDKs.
- Experience implementing AWS observability and monitoring strategies and leading enterprise-scale AWS transformations.
- Strong knowledge of AWS security, multi-account strategies, governance, privacy, compliance, and cost optimization.
- Exceptional communication skills for technical and executive audiences.
- AWS Professional Certifications are highly preferred, including AWS Solutions Architect – Professional and AWS DevOps Engineer – Professional.
- Preferred qualifications include AWS Machine Learning – Specialty or Security – Specialty certifications, experience with ReAct, Chain-of-Thought, and Tree-of-Thoughts patterns on Bedrock, AWS Control Tower, Glue, Redshift, Lake Formation, and consulting or professional services experience.
Benefits
- Opportunity to shape enterprise-scale generative and agentic AI platforms and influence the evolution of the company’s AWS AI practice.
- Work with distributed teams and client stakeholders across North America.