AI Solution Architect

AI First Architecture & Delivery

• Own the AI First architecture for JSSIs software delivery lifecycle rolling out spec-driven delivery models and bringing AI agents into day-to-day engineering across teams working toward a target of 100% of all code being generated by AI.
• Lead integration and adoption of AI tools agents agent skills and services across specification development review testing documentation and release driving both technical connection and day-to-day uptake by engineering teams.
• Build and maintain AI frameworks enabling scalable fine-tuning and prompt engineering pipelines inference experiment tracking observability and model governance.
• Architect multi-agent systems (orchestration reasoning planning autonomous task execution) on layered distributed architectures (queues caching APIs database schemas) operated by teams of coding agents.
• Translate Agile artifacts (epics user stories acceptance criteria) and product inputs into structured agent-ready specifications that coding agents implement.
• Set technical standards for API design and interoperability along with the guardrails evaluation frameworks and agent behavior boundaries that ensure responsible predictable AI deployment.
• Design build and evaluate MCP servers that expose JSSI enterprise systems as model-ready tools and define criteria for assessing third-party MCP integrations for security reliability and production readiness.

Enterprise Automation

• Design build and maintain agent-based automation that coordinates LLMs tools APIs and enterprise data (Salesforce email BI tools data lakes) into cohesive production-grade workflows.
• Establish patterns for agent reliability observability fallback behavior and lifecycle management in production.
• Develop enterprise-grade internal and external applications and services (dashboards microservices) that operationalize and extend automation initiatives.
• Create and refine AI prompts then monitor troubleshoot and optimize automations for accuracy performance and business value.
• Build trusted relationships with cross-functional stakeholders develop deep business insights and understanding and translate them into a prioritized pipeline of high-impact value-added opportunities.
• Support infrastructure teams in building CI/CD pipeline automation security scanning and policy-enforcement agents providing reusable patterns and ongoing architectural support so they can extend and maintain it.

Engineering Leadership & Standards

• Operate on the front line of AI delivery building enterprise-class products firsthand and treating rapid experimentation as an operational-excellence discipline deploying and learning in tight cycles toward a future state of deploying to production many times per day.
• Partner with engineering teams and leadership to shape engineering-practice standards governance and metrics that improve speed quality consistency and business impact.
• In a fast-moving AI landscape partner with Engineering Product and Executive leadership to refine processes define metrics that quantify impact scale proven workflows into repeatable delivery models and manage dependencies and technical risk across concurrent efforts.
• Guide and mentor AI Engineers and AI Verification Architects through technical leadership and influence rather than direct people management fostering a calm supportive and solution-oriented culture.
• Recognize the growing importance of citizen developers to the business and provide the guidance partnership best practices and insight that help their teams succeed.
• Ensure responsible AI practices: fairness explainability model monitoring ethics and regulatory alignment.

Core Experience

• 610 years of overall software engineering experience including 35 years in a Solution Architect Staff/Principal Engineer or equivalent senior technical role with ownership of system design for production SaaS platforms.
• Demonstrated experience designing and implementing AI First spec-driven (SDD) workflows across the software delivery lifecycle
• Production-level cloud-native development in the Microsoft stack (C#/.NET React/TypeScript RESTful Web APIs SQL Server / Azure SQL Managed Instances) and distributed-systems patterns such as queues caching and scalable APIs.
• Experience building deploying and maintaining production services through CI/CD and rapid iterative release cycles not just prototypes.
• Proven ability to mentor engineers and guide multiple teams through influence rather than direct people management.
• Excellent written and verbal communication skills; able to translate technical concepts for non-technical audiences.

AI & Claude Ecosystem Proficiency (Claude Strongly Preferred)

• Hands-on experience with AI coding agents and agentic workflows (Claude Code strongly preferred; also GitHub Copilot Codex or equivalent) including CLI integration and multi-agent development pipelines.
• Strong prompt engineering skills including structured outputs and retrieval-augmented prompting.
• Production expertise with LLM APIs (Claude API preferred): tool use computer use vision document processing streaming and rate-limit management.
• Hands-on experience with multi-agent design patterns (planning orchestration observability) and MCP server implementation against enterprise data sources.
• Software engineering best practices (version control testing deployment pipelines) evaluation frameworks that measure AI quality cost and latency and responsible-AI design aligned with Anthropics principles.

Highly Desired Qualifications

• Experience rolling out and scaling AI workflows across teams including agent observability and debugging in production.
• Experience with Azure cloud infrastructure and integrations with enterprise systems such as Dynamics 365 F&O and Salesforce or equivalent CRM.
• Bachelors degree in Computer Science Information Systems or equivalent professional experience.