Description

Are you passionate about Generative AI? In this role, you will help our customers build and deploy GenAI enabled applications using Amazon Bedrock and AgentCore and help enterprise customers leverage these models to power end applications. You will engage with product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services.

The ASPI Energy & Utilities Specialist Team is seeking an experienced and deeply technical Data and AI Solutions Architect to accelerate AI adoption across Global energy and power customers. This is a builder-first role. You will prototype, architect, and deliver production-grade AI solutions spanning agentic platforms, developer tools (Claude Code, Codex, Kiro), governance, and cybersecurity. You will bridge the gap between frontier AI capabilities (large language models, multimodal foundation models, retrieval-augmented generation, speech-to-speech models) and real-world energy environments, from operational productivity to developer platforms and real-time trading and utility operations centers.

As a trusted technical advisor, you will guide energy engineering and product teams through designing AI-native products and services: agentic systems for product development and real time operations, AI assistants that automate technician dispatch, and GenAI copilots for operations. You will work backwards from customer outcomes to define reference architectures that combine AWS AI services (Amazon Bedrock, AgentCore, Continuum, and others) with partner and open-source components in regulated industry deployments.

This role requires someone who builds. You will write code, construct proof-of-concept implementations, contribute to open-source projects, and develop reusable blueprints that accelerate GenAI adoption across the energy vertical. You will influence AWS product roadmaps by translating customer requirements into feature requests and working directly with service teams. You will publish your work through whitepapers, blog posts, reference architectures, and conference presentations.

The ideal candidate combines deep analytics and AI expertise with a passion for shipping AI products in complex, regulated environments. You are equally comfortable whiteboarding transformer architectures with ML engineers, designing multi-turn agentic workflows, and understanding the operational realities of energy customers.

Key job responsibilities

• Design and deliver generative AI solutions for energy customers across multiple industry domains.
• Architect end-to-end AI pipelines integrating foundation models, speech, vision, and tool-use agents with energy platforms and infrastructure.
• Build production-quality proof-of-concepts demonstrating agentic capabilities, AI developer and productivity tooling.
• Lead technical engagements with energy engineering teams on analytics and AI architectures.
• Provide strategic guidance on deploying AI agents into energy environments, addressing latency, reliability, compliance, and scale requirements.
• Develop reference architectures and reusable blueprints that accelerate GenAI adoption, combining Bedrock, AgentCore, Kiro/Claude Code/Codex, and partner ecosystem components.
• Influence AWS AI service roadmaps by capturing customer requirements and collaborating with service teams.
• Author whitepapers, blog posts, and reference implementations establishing AWS's point of view on GenAI for telecommunications.
• Drive customer growth through GenAI-focused sales strategies in partnership with AWS Sales teams.
• Build trusted advisor relationships with senior technical leaders (VP Eng, CTO, Chief AI Officer) at energy customers.
• Partner with SAs, Sales, Business Development, and the AI/ML Service teams to accelerate customer adoption and providing guidance on their customer engagements.
• Develop and support an AWS internal community of Data and AI related subject matter experts worldwide.
• Create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services AI solutions into customer architectures.