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Open nowPosted 3 days ago

Solution Architect (AWS / AI)

CapNexus1 open role

Where
USA
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Your applicationOpen nowSolution Architect (AWS / AI)CapNexus · USA

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The clock on this job

Early applications get read.

13.7% of postings close within 7 days. Measured by our own scanner across the market. CapNexus postings stay open a median of 25 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.8%3 days
  3. 13.7%7 days
  4. 22.1%14 days
  5. 37.6%30 days
  6. 59.1%60 days
This job: posted 3 days ago

CapNexus median: 25 days open

The posting

Specialization: Cloud-Native & AI

Platform focus: AWS Deep

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

CapNexus 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 CapNexus works fluently inside our delivery system, which combines agentic tooling, spec-driven development, evidence-based quality, and AI-augmented delivery governance.

Who You Are and What You'll Do:

CapNexus 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.

Responsibilities:

  • 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.

How You'll Work: Agentic Engineering:

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.

What doesn't change at any level: judgment over correctness, the ability to tell when confident, plausible-looking AI output is quietly wrong. Tooling does the mechanical work; you're accountable for whether it's right.

Qualifications:

  • 10+ years of software, infrastructure, or data experience, including significant solution architecture work.
  • Experience designing end-to-end solutions across application, data, infrastructure, and security.
  • Strong client communication: you can run an architecture review with executives and engineers in the same room.
  • Hands-on experience prototyping or testing designs with AI development tools such as Claude Code or Kiro, and a clear view of what AI tooling can and can't be trusted with in a production architecture.
  • A hands-on background building full-stack, cloud-native applications with AI features (for example, React or Angular front ends, Python or TypeScript services, and Amazon Bedrock) before moving into architecture.
  • 5+ years designing production architectures on AWS, with a working understanding of cost, scaling, security, and failure modes.
  • A current AWS Certified Solutions Architect – Professional certification.
  • Strong written and verbal communication: clear design documents, proposals, and executive presentations.
  • Solid business acumen: you connect architecture choices to cost, risk, time to value, and the client's business case.
  • Proven experience scoping systems and producing architectures and design documents that teams build from.
  • Pre-sales or consulting experience: discovery workshops, solution proposals, estimates, and demos.

Nice to Have:

  • AWS Certified Generative AI Developer – Professional (AIP-C01).
  • AWS Certified Security – Specialty.
  • Experience engaging AWS Professional Services during scoping.
  • Background in retail.

Our Culture:

Four keystones guide how we work:

  • Customer obsessed, delivery focused. We deliver what we promise. Trust = consistency × time.
  • Learning and sharing. We hire lifetime learners, and teaching others matters as much as knowing.
  • Growth and scalability. We value cross-functional skills over role boundaries, and simple solutions over clever ones.
  • All work is strategic. Every engagement, big or small, is a chance to earn trust that lasts.

We offer:

Job Type: Full-time

Benefits: Medical, dental, 401(k), and more

CapNexus is an equal opportunity employer. We embrace and celebrate diversity and are committed to creating an inclusive and safe environment for all employees. Experience comes in many forms, and we’re dedicated to adding new perspectives to the team. We encourage you to apply even if your experience doesn’t perfectly align with what we have listed. We look forward to hearing from you.

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