AI Solution Architect

Jet Support Services • Chicago, IL

4d

About The Position

JSSI, a leading independent provider of hourly cost maintenance programs for business aviation, is seeking an AI Solution Architect to drive its AI First engineering strategy. This role is crucial for conceptualizing and implementing AI agents, spec-driven development (SDD), and enterprise automation across various departments including Engineering, Product, Sales, Finance, Customer Service, and Operations. It's a hands-on position requiring significant ownership, where you will design, build, and deploy AI systems rapidly, focusing on measurable impact. Success hinges on strong technical depth combined with excellent communication and influencing skills to translate business needs into scalable AI solutions and guide teams toward optimal outcomes.

Requirements

• 6–10 years of overall software engineering experience.
• 3–5 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).
• Experience with 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.
• 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.
• 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).
• Experience with evaluation frameworks that measure AI quality, cost, and latency.
• Experience with responsible-AI design aligned with Anthropic's principles.

Nice To Haves

• 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.
• Bachelor’s degree in Computer Science, Information Systems, or equivalent professional experience.

Responsibilities

• Own the AI First architecture for JSSI's software delivery lifecycle, implementing spec-driven delivery models and integrating AI agents into daily engineering tasks.
• Lead the integration and adoption of AI tools, agents, agent skills, and services across the software development lifecycle (specification, development, review, testing, documentation, release).
• Build and maintain AI frameworks for scalable fine-tuning, prompt engineering, inference, experiment tracking, observability, and model governance.
• Architect multi-agent systems (orchestration, reasoning, planning, autonomous task execution) on distributed architectures.
• Translate Agile artifacts and product inputs into structured, agent-ready specifications for coding agents.
• Set technical standards for API design, interoperability, guardrails, evaluation frameworks, and agent behavior boundaries for responsible AI deployment.
• Design, build, and evaluate MCP servers to expose JSSI enterprise systems as model-ready tools and assess third-party MCP integrations.
• Design, build, and maintain agent-based automation coordinating LLMs, tools, APIs, and enterprise data into 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 that operationalize and extend automation initiatives.
• Create and refine AI prompts, monitor, troubleshoot, and optimize automations for accuracy, performance, and business value.
• Build trusted relationships with cross-functional stakeholders, gain business insights, and translate them into high-impact opportunities.
• Support infrastructure teams in building CI/CD pipeline automation, security scanning, and policy-enforcement agents.
• Operate on the front line of AI delivery, building enterprise-class products and treating rapid experimentation as an operational-excellence discipline.
• Partner with engineering teams and leadership to shape engineering-practice standards, governance, and metrics.
• Refine processes, define metrics, scale proven workflows, and manage dependencies and technical risk.
• Guide and mentor AI Engineers and AI Verification Architects through technical leadership and influence.
• Provide guidance, partnership, best practices, and insight to citizen developers.
• Ensure responsible AI practices: fairness, explainability, model monitoring, ethics, and regulatory alignment.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Retirement savings programs
• Annual discretionary bonus plan
• Incentive or sales bonus plan
• Other forms of additional compensation

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree