AI Solutions Architect (AWS)

6–8+ years of demonstrated experience in ML or data science roles

Proven track record in client-facing technical roles, including leading pre-sales or discovery engagements

Portfolio of successfully architected and delivered ML solutions with a history of winning business through technical leadership

Deep understanding of the full ML lifecycle from data ingestion through production deployment

Experience designing scalable, production-grade ML architectures across multiple ML domains (RAG, Computer Vision, Time Series, Recommendation Systems, and others)

Strong experience architecting LLM-based applications, including agentic systems

Proficiency with agent design patterns, state management, and orchestration frameworks (LangGraph, LangChain agents, multi-agent systems)

Hands-on experience with the Claude ecosystem: Claude Code, Claude Agent SDK, and Anthropic's tool ecosystem

Working knowledge of Model Context Protocol (MCP) architecture for designing client integrations

Demonstrated use of AI-assisted development tools (Cursor, GitHub Copilot, Claude Code) for rapid prototyping and POC development

Advanced knowledge of AWS ML and data services including SageMaker, Bedrock, Lambda, and ECS

Deep understanding of Amazon Bedrock agents, knowledge bases, and model hosting options

Experience with serverless architectures (Lambda, API Gateway, Step Functions) for agentic workflows

Knowledge of MLOps, LLMOps, and AgentOps practices including monitoring, evaluation, and cost optimization

Ability to design cost-effective solutions with clear TCO analysis and trade-off assessment

Understanding of data security, privacy, and compliance requirements

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent experience with a demonstrable technical foundation