Senior Specialist Solutions Architect, Applied AI Solutions Architect - Public Sector (Amazon Connect)

Amazon • Arlington, VA

5d

About The Position

This position is part of the AWS Specialist and Partner Organization (ASP).
Specialists own the end-to-end go-to-market strategy for their respective
technology domains, providing the business and technical expertise to help our
customers succeed. Partner teams own the strategy, recruiting, development, and
growth of our key technology and consulting partners. Together they provide our
customers with the expertise and scale needed to build innovative solutions for
their most complex challenges.

The Area Specialist Team is made up of deep domain experts who work directly
with our customers to solve their most complex challenges. We are part of the
Account Team, responsible for account planning, opportunity identification, and
pursuit. We stay closely connected to our customers and bring valuable data and
insights to our product teams, strengthening the product roadmap. Our team is at
its best when a customer is thinking big and needs specialized experience to
innovate for their business.

The Amazon Connect Specialist Team is made up of deep CX and Enterprise Contact
Center domain experts who work directly with our customers to solve their most
complex challenges. We stay closely connected to our customers and bring
valuable data and insights to our product teams, strengthening the product
roadmap. Our team is at its best when a customer is thinking big and needs
specialized experience to innovate for their business.

Amazon Connect was designed from the ground up to be omnichannel, it provides a
seamless experience across voice and chat for your customers and agents
leveraging AWS. This is a highly technical position for someone who can dive
deep, build complex, AWS-optimized architectures, and help customers accelerate
their adoption of AWS services. Your broad responsibilities include: owning the
technical engagement and ultimate success around specific implementation
projects. You should be as comfortable discussing complex technical details with
a room full of engineers as you are briefing an executive audience. In addition,
you will engage with other AWS solutions architects, partner and professional
services organizations to drive large and highly complex sales opportunities to
closure.

Requirements

• 3+ years of design, implementation, or consulting in applications and infrastructures experience
• 7+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• 7+ years of IT development or implementation/consulting in the software or Internet industries experience
• Experience with Amazon Connect or other enterprise contact center platforms (Genesys, Avaya, Cisco, NICE, Five9, etc.)
• Hands-on experience with Amazon Bedrock, including model invocation, agent creation, knowledge base configuration, and guardrails

Nice To Haves

• 5+ years of infrastructure architecture, database architecture and networking experience
• Experience with agentic AI patterns — multi-agent orchestration, tool use, function calling, chain-of-thought reasoning, and autonomous agent workflows .
• Hands-on experience building and deploying MCP servers — exposing enterprise tools and APIs via Model Context Protocol for dynamic agent tool discovery and invocation
• Experience designing A2A (Agent-to-Agent) architectures — enabling specialized agents to collaborate across domains (e.g., billing, logistics, IT) through standardized agent communication protocols
• Proficiency with agentic IDEs such as Kiro, Cursor, or similar AI-assisted development environments, including experience with agent hooks, agent steering, MCP server configuration, and spec-driven development
• AWS certifications (Solutions Architect Professional, AI Practitioner, Machine Learning Specialty)

Responsibilities

• Customer Engagement: Lead technical discovery sessions with customer teams to understand business requirements, existing contact center architecture, and AI readiness. Translate findings into actionable implementation plans.
• Customer Data Readiness: Conduct data readiness assessments to evaluate the quality, accessibility, structure, and governance of customer data assets (CRMs, knowledge bases, ticketing systems, order management, etc.). Identify data gaps, recommend remediation strategies, and help customers build the data foundation required for effective AI agent tool use and RAG-powered responses.
• Agentic AI Implementation: Design and configure agentic AI solutions within Amazon Connect, including AI agent creation, AI prompt engineering, model selection, guardrail configuration, and tool/action integration.
• MCP Server Configuration: Design and deploy Model Context Protocol (MCP) servers that expose customer tools, data sources, and APIs in a standardized format — enabling AI agents to dynamically discover and invoke capabilities across the customer's technology stack.
• A2A (Agent-to-Agent) Integration: Architect Agent-to-Agent communication patterns that allow Amazon Connect AI agents to collaborate with specialized agents across the enterprise (e.g., billing agents, order management agents, IT support agents), enabling multi-agent workflows that span organizational boundaries.
• Integration Development: Build serverless integrations using AWS Lambda, API Gateway, Step Functions, and scripting (Python, Node.js) to connect Amazon Connect AI agents with customer data systems (CRMs, ERPs, databases, knowledge bases).
• Cloud Data Access: Architect secure access patterns to cloud-based data systems (Amazon DynamoDB, Amazon RDS, Amazon S3, Amazon OpenSearch, Amazon Kendra/Knowledge Bases for Bedrock) to power AI agent tool use and retrieval-augmented generation (RAG).
• Agentic IDE Proficiency: Leverage agentic development environments such as Kiro (and similar AI-assisted IDEs) to accelerate development workflows, including spec-driven development, agent hooks, MCP server configuration, and AI-assisted code generation.
• Pre-Production Validation: Guide customers through testing, evaluation, and validation of AI agent performance against defined success criteria before production deployment.
• Knowledge Sharing: Create reusable artifacts (reference architectures, implementation guides, sample code, prompt libraries, data readiness checklists) that scale best practices across the Connect SA community and partner ecosystem.
• Service Team Collaboration: Provide feedback to Amazon Connect and Amazon Bedrock product teams based on real-world customer implementations, contributing to product roadmap prioritization.
• Field Enablement: Contribute to the ACE (Amazon Connect Enablement) program by sharing learnings, delivering technical deep-dives, and mentoring field SAs on agentic AI implementation patterns.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed