Solution Architect (AWS / AI)

Accountabilities

You will take ownership of end-to-end solution architecture, ensuring that client requirements are translated into robust technical designs and actionable engineering specifications. Your responsibilities will include:

Lead solution architecture for client engagements, defining technical approaches, technology choices, integrations, security requirements, and cost considerations.

Design cloud-native applications on AWS, including serverless, event-driven, and container-based architectures with integrated generative and agentic AI capabilities.

Develop end-to-end AWS architectures covering compute, data, networking, security, and AI services, ensuring alignment with the AWS Well-Architected Framework.

Translate business requirements into technical designs, implementation roadmaps, and clear architectural recommendations.

Lead client discovery sessions to assess existing systems, business requirements, technical constraints, integrations, and potential risks.

Produce comprehensive technical documentation, including solution architecture documents, architecture decision records, non-functional requirements, and technical diagrams.

Define technical specifications and architectural standards that engineering teams use to validate and implement solutions.

Partner with Lead Engineers, establishing architectural direction while allowing engineering teams to determine implementation approaches.

Design AI-powered capabilities, including retrieval systems, AI agents, evaluation frameworks, and appropriate security guardrails.

Define the agentic engineering delivery approach, including agent roles, conversion tools, templates, workflows, and validation checkpoints.

Use AI development tools such as Claude Code and Kiro to prototype architectural decisions, generate reference implementations, and validate technical assumptions.

Assess where AI can effectively improve solution delivery and where human judgment remains essential, considering integration, data, security, and cost implications.

Establish architectural quality standards and ensure AI-generated outputs and technical implementations meet production requirements.

Support pre-sales activities by developing solution designs, effort estimates, technical proposals, and statements of work.

Lead technical presentations, demonstrations, and proof-of-concept development to communicate solution capabilities to prospective clients.

Partner with Client Leaders on business opportunities, taking ownership of solution design and technical estimates while commercial pricing and contract negotiations remain separate.

Mentor engineers and promote architectural best practices, technical knowledge sharing, and sound engineering judgment.

Requirements:

The ideal candidate combines extensive software and cloud architecture experience with hands-on development expertise and a strong understanding of generative and agentic AI. You should be comfortable working directly with clients, leading technical discussions, and making architecture decisions that balance business objectives with technical quality.

10+ years of experience in software engineering, infrastructure, or data, including significant experience in solution architecture.

5+ years of experience designing and delivering production architectures on AWS.

Current AWS Certified Solutions Architect – Professional certification.

Strong experience designing end-to-end technical solutions across application architecture, data, infrastructure, networking, and security.

Hands-on background developing full-stack, cloud-native applications with integrated AI capabilities.

Familiarity with technologies such as React or Angular, Python or TypeScript services, and Amazon Bedrock.

Experience designing serverless, event-driven, and container-based cloud architectures.

Practical experience with generative AI and agentic AI capabilities, including retrieval, AI agents, evaluation, and guardrails.

Hands-on experience prototyping or testing architectural designs using AI development tools such as Claude Code or Kiro.

Strong understanding of the limitations and risks of AI-generated code and the ability to evaluate its correctness in production environments.

Ability to assess AI integration opportunities and understand their implications for data management, security, scalability, and cost.

Proven experience translating business requirements into technical architectures, specifications, and implementation plans.

Experience leading client discovery workshops and managing technical discussions with both executive stakeholders and engineering teams.

Previous consulting or pre-sales experience involving solution proposals, technical estimates, demonstrations, and proof-of-concept development.

Strong written and verbal communication skills, with the ability to produce clear technical documentation and deliver compelling executive presentations.

Solid business acumen and the ability to connect architectural decisions to cost, risk, delivery timelines, and business value.

Strong mentoring and collaboration skills, with the ability to guide engineering teams and establish high technical standards.

Comfortable working in a fast-paced consulting environment that values continuous learning, adaptability, and cross-functional collaboration.

Must currently reside in the United States and be authorized to work there.

Preferred qualifications:

AWS Certified Generative AI Developer – Professional (AIP-C01).

AWS Certified Security – Specialty.

Experience collaborating with AWS Professional Services teams during client discovery, solution design, or delivery engagements.

Previous experience in the retail industry.

Benefits:

Full-time employment opportunity.

Medical insurance coverage.

Dental insurance coverage.

401(k) retirement plan.

Additional employee benefits and support.

Remote working arrangement within the United States.

Opportunity to work on innovative cloud-native and AI-powered solutions.

Exposure to advanced agentic engineering practices and cutting-edge AWS technologies.

Continuous learning and knowledge-sharing culture.

Opportunity to collaborate with experienced cloud architects, engineers, and technology professionals.

Professional growth within a consulting environment focused on innovation, scalability, and high-quality delivery.