Lead Solution Architect with AI Experience
Indexed description
Recruiting for this role ends on 11/01/2026.
Work you'll do
As a Lead Solution Architect you will be responsible for...
- Leading solution architecture and engineering efforts for client engagements involving generative artificial intelligence, Amazon Web Services cloud services, data platforms, and enterprise application modernization
- Translating business, functional, and technical requirements into scalable architecture designs, reference patterns, implementation roadmaps, and delivery plans
- Guiding engineering teams through solution design, Amazon Bedrock integration, Anthropic Claude implementation, application programming interface strategy, security controls, and production deployment across complex enterprise environments
- Collaborating with client stakeholders, product owners, data scientists, and delivery leaders to manage priorities, risks, dependencies, and quality throughout the delivery lifecycle
- Driving engineering-led innovation by identifying opportunities to modernize platforms, operationalize artificial intelligence capabilities, improve operational performance, and accelerate digital product and platform outcomes
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to mentor and provide clear guidance to others
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.
Qualifications
Required:
- Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, Electrical Engineering, or Mathematics
- 8+ years of experience in software engineering, application architecture, or solution architecture
- 5+ years of experience leading engineering teams, projects, or workstreams for enterprise technology implementations
- Experience designing and implementing cloud-based solutions using Amazon Web Services, including Amazon Bedrock, AWS Lambda, Amazon SageMaker, Amazon API Gateway, or container-based services
- Experience architecting generative artificial intelligence solutions using large language models, prompt orchestration, retrieval-augmented generation, vector databases, and enterprise integration patterns
- Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
- Master's degree in Computer Science, Software Engineering, Information Systems, Data Science, Electrical Engineering, or Mathematics
- Experience delivering technology transformation programs in a consulting or professional services environment
- Experience implementing Anthropic Claude through Amazon Bedrock or application programming interface integration in enterprise environments
- Experience with model evaluation, observability, guardrails, and security controls for production artificial intelligence deployments
- AWS certification such as AWS Certified Solutions Architect, AWS Certified AI Practitioner, or AWS Certified Machine Learning Engineer
- Experience presenting architecture recommendations, delivery status, and technical tradeoffs to executive stakeholders
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
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