Solutions Architect , AWS Enterprise Industries

DESCRIPTION

Join the AWS Enterprise team as a Solutions Architect for Engineering, Construction, Real Estate, and Transportation (ECRT) customers. You will define and prove technical direction for major industrial operators by combining architectural reasoning and strategic advisory with hands-on validation in customer environments. You build working prototypes, proof-of-concepts, and AI-driven solutions that accelerate customer decisions and remove the gap between architectural recommendation and validated proof.

You operate where the path forward may be is undefined and must be defined by you. Your ECRT customers have business objectives (reduce project delivery risk, optimize fleet operations, modernize asset management) but may not have defined technology strategy or solution design. You create and adapt approaches for situations where established patterns are insufficient, applying contextual judgment about your customers’ operational constraints, regulatory environment, and competitive dynamics.

You will be the primary technical partner for major US construction, real estate, and transportation operators. You lead with Agentic AI and AI-assisted development to solve customer problems, and you steer customers away from where hype outpaces practical value for their operational context. You maintain technical currency so customers receive guidance based on current capability, not outdated expertise. You build deep relationships with customers’ senior technical leaders to enable them to be cloud advocates.

You are technically self-sufficient, yet you know when to seek help: you are capable of using AI tools and delivering directly in customer sandbox environments. You drive the architectural decisions that downstream teams (customer engineering, ProServe, partners) build against, and you own the consequences with the customer when those decisions need revisiting.

Key job responsibilities
Technical Proof & Validation

• Build working prototypes in customer non-production sandbox environments using AI-augmented development tools (Kiro, Claude Code, Bedrock) to validate architectural recommendations and accelerate customer adoption
• Implement directly to unblock customer decisions: build PoCs for digital twins (IoT TwinMaker), fleet IoT, predictive maintenance, and agentic AI, proving architectural approaches that conversations alone cannot validate
• Deploy infrastructure using IaC (CDK, Terraform) in customer sandboxes, demonstrating scalability and security patterns
• Apply GenAI and agentic systems (multi-agent orchestration, RAG pipelines, foundation model integration) where they solve ECRT customer problems

Architectural Reasoning & Decision Ownership

• Frame and resolve technical trade-offs involving multiple competing concerns (security vs. cost vs. operational burden vs. time-to-market vs. industry compliance), bringing a clear recommendation with alternatives articulated
• Make cross-cutting architectural decisions that ensure coherence across systems, teams, and workstreams; flag decisions that are difficult to reverse before the customer commits
• Diagnose non-obvious architectural issues including resilience gaps, failover weaknesses, scaling bottlenecks, and security vulnerabilities specific to industrial IoT and construction technology environments
• Own the architectural decisions that downstream teams build against and own the consequences with the customer when those decisions need revisiting
• Stay engaged through implementation to ensure the architecture holds against the reality of the customer’s environment; know when accumulated context warrants a revised approach.

Strategic Advisory & Customer Influence

• Own the end-to-end technical strategy for assigned ECRT customers, maintaining the current view of their technical landscape, industry context, and competitive dynamics
• Partner with the sales team, formulate and execute a sales strategy to exceed revenue objectives through the adoption of AWS
• Influence senior leaders’ technology direction by connecting short-term AI and cloud decisions to long-term business outcomes; earn trust through guidance that consistently delivers the outcomes they expected
• Challenge customer direction when evidence indicates a better path; customers avoid costly rework because you identify risk early and bring considered alternatives
• Shape AI and cloud strategy for major operators — translating complex capabi…