Solutions Architect

Location:

Remote (US), with travel to client sites as needed

Cap Nexus is an AWS consulting partner specializing in AI and cloud engineering. We build and deliver software through agentic engineering: we build and operate the systems that produce code, direct AI tooling to accelerate delivery, and exercise the judgment that keeps AI-generated work correct. Everyone at Cap Nexus works fluently inside our delivery system, which combines agentic tooling, spec-driven development, evidence-based quality, and AI-augmented delivery governance.

Cap Nexus is looking for a Solutions Architect to translate client problems into technical solutions and own the architecture the engineering team builds against.

In this role, you'll focus on cloud-native applications with AI built in: serverless and container services, APIs, front ends, and the generative and agentic AI features inside them.

Your time splits evenly. About half is billable client delivery as the architect on an engagement. The other half is pre-sales, where you scope the opportunity and design the solution before the work is sold.

• Lead solution design for an engagement: architecture, technology choices, integration, security, and cost.
• Author the technical specifications the engineering team validates and builds from.
• Translate business requirements into designs and roadmaps, and explain trade-offs in business terms.
• Partner with the Lead Engineer as a peer: you decide the architecture, and they decide the implementation approach.
• Support pursuits with solution design, estimates, and technical credibility.
• Mentor engineers on design patterns and architectural thinking.
• Design cloud-native application architectures on AWS (serverless, event-driven, and container-based) with generative and agentic AI features built in, including retrieval, agents, evaluation, and guardrails.
• Design end-to-end AWS architectures across compute, data, networking, security, and AI services, and review them against the AWS Well-Architected Framework.
• Lead discovery with client stakeholders and scope the systems involved: current state, requirements, constraints, integrations, and risks.
• Produce the architecture and design documents an engagement is built from: solution architecture documents, architecture decision records, non-functional requirements, and diagrams.
• Turn a scoped design into effort estimates and the technical content of proposals and statements of work.
• Lead technical presentations, demos, and proof-of-concept builds that show clients how the solution works.
• Partner with the Client Leader on pursuits. You own the solution and the estimate; pricing and contract terms are handled separately.

You translate client problems into technical solutions and own the architecture the team builds against.

• Solution design through agentic delivery. Design solutions that assume agentic engineering as the delivery model: account for what AI tooling accelerates, what it can't do, and where human judgment gates belong.
• Delivery-approach design. Specify the delivery tooling for the engagement: the agent roles, conversion tools, templates, and validation gates the team builds through.
• Agentic tooling fluency. Use Claude Code and Kiro to prototype architecture decisions, generate reference implementations, and test design assumptions before committing the team.
• AI integration judgment. Decide where AI fits in the solution, and where it doesn't, and own the integration, data, security, and cost implications.
• Quality standard ownership. Define the architecture quality bar the team builds against. The Lead Engineer executes to your standard; you own the standard.

judgment…