Enterprise AI Solutions Architect

Stevens is a strategic advisory and technology firm that partners with companies on high-impact transformation and technology initiatives. We work closely with executive and technology leaders to solve complex problems, identify opportunities, and turn strategy into working solutions.

Our engagements often sit at the intersection of business strategy, enterprise architecture, and emerging technology. We help customers identify where AI can create meaningful business value, determine what should actually be built, and provide the technical leadership needed to move from concept to production.

We’re looking for an experienced Enterprise AI Solutions Architect to join us on a contract basis and help lead the technical direction of enterprise AI engagements.

This is a senior, highly customer-facing role. You’ll work directly with customer technology leaders, engineering teams, and Stevens delivery teams to understand complex business problems, shape AI use cases, design solutions, guide proofs of concept, and establish the architecture required to take successful solutions into production.

We’re specifically looking for someone who understands enterprise application development and architecture, not simply AI models or cloud infrastructure. The model is one part of the system. You should be comfortable thinking across applications, APIs, data, integrations, identity, security, cloud infrastructure, AI services, and production operations to design a complete solution.

Your work may include:

• Leading technical discovery and architecture sessions with enterprise customers.
• Translating business problems and AI opportunities into practical solution architectures and implementation plans.
• Designing enterprise AI applications using LLMs, RAG, agents, tool use, structured and unstructured data, APIs, and modern cloud services.
• Designing applications that integrate AI capabilities into existing enterprise systems, data platforms, SaaS applications, and business workflows.
• Architecting solutions primarily within AWS, including Amazon Bedrock and SageMaker.
• Evaluating models, platforms, frameworks, and architectural approaches based on the requirements of each use case.
• Helping customers make build-vs-buy decisions across a rapidly evolving AI technology landscape.
• Designing rapid proofs of concept while ensuring successful POCs have a realistic path to production.
• Defining architecture across application services, APIs, data, model infrastructure, integrations, identity, observability, and cloud infrastructure.
• Accounting for enterprise requirements including security, privacy, governance, scalability, reliability, performance, and cost.
• Establishing appropriate approaches to AI evaluation, guardrails, monitoring, and production operations.
• Working closely with engineers throughout implementation to ensure architectural decisions translate into high-quality working software.
• Reviewing technical approaches, identifying risks, and helping engineering teams navigate architectural tradeoffs.
• Presenting architecture recommendations and technical decisions to engineering teams, technology leaders, and senior customer stakeholders.

This isn’t a role where you’ll create an architecture diagram and hand it to someone else. We want architects who stay close to implementation, understand the consequences of their decisions, and can help a team navigate the difficult decisions that emerge as a solution gets built.

You’ll have significant autonomy and ownership. A successful architect at Stevens can walk into an ambiguous problem, quickly understand the customer’s business and technology environment, identify the decisions that actually matter, develop a point of view, and confidently guide the customer and delivery team toward a solution.

Requirements

• U.S. citizenship is required.
• 7+ years of relevant experience across software architecture, solutions architecture, application development, engineering, or technical consulting.
• Significant experience designing and delivering enterprise applications, platforms, or distributed systems.
• Hands-on experience architecting and implementing generative AI applications beyond basic prototypes or isolated model integrations.
• Experience taking applications or technical initiatives from discovery and proof of concept through production.
• Strong understanding of modern AI application patterns including RAG, agents, tool use, embeddings, vector s…