The Role
Build, deploy, and operate production-grade AI agents, LLM-powered features, and enterprise automations across JSSI SaaS platforms. Direct coding agents using Claude Code, develop multi-agent workflows and MCP integrations, and own reliability, observability, testing, security, and business outcomes. Translate product specifications into working software, maintain context and coding standards, and collaborate with architects, product teams, stakeholders, and engineers to deliver responsible AI solutions through rapid iterative cycles.
Summary Generated by Built In
About JSSI
Founded in 1989 and headquartered in Chicago, Jet Support Services, Inc. (JSSI) is the largest independent provider of hourly cost maintenance programs for business aviation. JSSI delivers comprehensive coverage for engines, airframes, and auxiliary power units (APUs) across more than 300 different aircraft makes and models, helping owners and operators stabilize maintenance budgets, maximize aircraft availability, and protect asset value throughout the lifecycle of ownership. JSSI has built a portfolio of complementary business lines designed to simplify the economic and technical complexity of business aviation; these include Maintenance teams, Traxxall maintenance tracking software, Parts & Engines, Conklin aircraft cost and performance data, and Aviation Capital asset-based financing solutions. Together, these offerings support owners, operators, and maintenance providers with integrated tools spanning ownership and maintenance planning, execution, and financial management. With more than 6,500 aircraft supported through programs and software platforms, JSSI leverages its unique independence, unmatched scale, and data-driven insight to deliver customized solutions and support models aligned to the interests of each client — regardless of aircraft platform. JSSI is backed by leading institutional investors GTCR, Genstar Capital, and Blackstone. Learn more at jetsupport.com.
POSITION SUMMARY
The AI Engineer is a hands-on builder at the core of JSSI’s AI First engineering transformation,
designing, shipping, and operating production-grade AI systems from prototype to production.
Reporting to the Director of Engineering, you will work alongside the AI Solution Architect (who
sets architecture standards and direction) and the AI Verification Architect (who builds the testing
and verification frameworks your work is validated against), partnering closely with an AI First
Product team to drive the evolution of JSSI’s SaaS platforms.
This is a distinct role that supersedes the traditional Senior Developer position at JSSI. In an AI
First Agentic Operating model, "senior developer" is no longer a job a person holds: it is a
capability the AI Engineer directs, exercised by coding agents under their guidance. The AI
Engineer orchestrates that agentic development capability rather than performing hands-on
coding as the primary activity, owning outcomes across building, shipping, and operating AI
systems. It is designed for accomplished software engineers ready to make that shift, from writing
the code themselves to directing the agents that write it.
First Agentic Operating model, "senior developer" is no longer a job a person holds: it is a
capability the AI Engineer directs, exercised by coding agents under their guidance. The AI
Engineer orchestrates that agentic development capability rather than performing hands-on
coding as the primary activity, owning outcomes across building, shipping, and operating AI
systems. It is designed for accomplished software engineers ready to make that shift, from writing
the code themselves to directing the agents that write it.
You will turn product specifications and Agile artifacts into working AI agents, LLM-powered
features, and automation; integrate them with JSSI’s enterprise systems; and own their reliability,
accuracy, and business impact in production. You will use Claude Code as your primary
development tool, working in tight build-measure-learn cycles. Success is measured by what you
ship and the outcomes it produces, not by activity. Strong written and verbal communication
matters as much as technical depth: you will collaborate daily with product, business
stakeholders, and your engineering peers to translate real needs into reliable solutions.
features, and automation; integrate them with JSSI’s enterprise systems; and own their reliability,
accuracy, and business impact in production. You will use Claude Code as your primary
development tool, working in tight build-measure-learn cycles. Success is measured by what you
ship and the outcomes it produces, not by activity. Strong written and verbal communication
matters as much as technical depth: you will collaborate daily with product, business
stakeholders, and your engineering peers to translate real needs into reliable solutions.
Position Responsibilities
AI First Engineering & Delivery
• Drive continuous refinement of the AI agentic pipeline and its iterative development loop,
informing architectural direction in partnership with the AI Solution Architect. Apply
context engineering, enforce human-in-the-loop governance, and hold final accountability
for all software delivered under your direction.
• Direct the design, build, and delivery of production-grade AI features and agents across
JSSI’s SaaS platforms, working within the architecture standards and spec-driven delivery
models set by the AI Solution Architect.
JSSI’s SaaS platforms, working within the architecture standards and spec-driven delivery
models set by the AI Solution Architect.
• Implement and integrate AI tools, agents, agent skills, and services across the delivery
lifecycle: specification, development, review, testing, documentation, and release.
lifecycle: specification, development, review, testing, documentation, and release.
• Build multi-agent workflows (orchestration, reasoning, planning, autonomous task
execution) on distributed patterns such as queues, caching, and scalable APIs, and
operate them with other coding agents.
execution) on distributed patterns such as queues, caching, and scalable APIs, and
operate them with other coding agents.
• Translate Agile artifacts and product inputs into structured, agent-ready specifications,
implement them through coding agents, and build and consume MCP servers that expose
JSSI enterprise systems as model-ready tools, following the criteria defined by the AI
Solution Architect.
implement them through coding agents, and build and consume MCP servers that expose
JSSI enterprise systems as model-ready tools, following the criteria defined by the AI
Solution Architect.
• Use Claude Code as your primary enablement tool to develop, review, test, and document
software in tight, iterative cycles, adopting spec-driven delivery models and bringing AI
agents into day-to-day engineering, with a stated goal of 100% AI-generated code.
software in tight, iterative cycles, adopting spec-driven delivery models and bringing AI
agents into day-to-day engineering, with a stated goal of 100% AI-generated code.
• Serve as the primary steward of the context store, the coding standards, patterns, domain
knowledge, and project memory that ground every agent session, capturing each lesson
and production insight back into it to continuously improve the pipeline.
knowledge, and project memory that ground every agent session, capturing each lesson
and production insight back into it to continuously improve the pipeline.
• Bridge spec-driven and test-driven practices: derive tests directly from the spec’s
acceptance criteria before directing agent implementation, making the spec executable,
structurally constraining agent output, and giving the AI Verification Architect a reliable
contract to validate against.
acceptance criteria before directing agent implementation, making the spec executable,
structurally constraining agent output, and giving the AI Verification Architect a reliable
contract to validate against.
Enterprise Automation
• Build, operate, and maintain agent-based automation that coordinates LLMs, tools, APIs,
and enterprise data (Fabric, Salesforce, D365 F&O, and JSSI proprietary platforms) into
cohesive, production-grade workflows, following the automation patterns and standards
established by the AI Solution Architect.
and enterprise data (Fabric, Salesforce, D365 F&O, and JSSI proprietary platforms) into
cohesive, production-grade workflows, following the automation patterns and standards
established by the AI Solution Architect.
• Own agent reliability, observability, fallback behavior, and lifecycle management in
production, keeping automations dependable as they scale.
production, keeping automations dependable as they scale.
• Direct coding agents to build enterprise-grade internal and external applications and
services (dashboards, microservices) that operationalize and extend automation
initiatives.
services (dashboards, microservices) that operationalize and extend automation
initiatives.
• Create and refine the AI prompts, agent skills, and context packages that drive automation
quality, then monitor, troubleshoot, and optimize for accuracy, performance, and
measurable business value.
quality, then monitor, troubleshoot, and optimize for accuracy, performance, and
measurable business value.
• Partner with cross-functional stakeholders to identify and prioritize the automation
opportunities that deliver the highest business impact.
opportunities that deliver the highest business impact.
Collaboration & Partnership
• 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.
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 the AI Solution Architect to apply engineering-practice standards,
governance, and metrics, and surface improvements from what you learn building in
production.
governance, and metrics, and surface improvements from what you learn building in
production.
• Work closely with the AI Verification Architect to make your work testable, building
features against the verification frameworks and acceptance criteria that validate quality
and behavior.
features against the verification frameworks and acceptance criteria that validate quality
and behavior.
• Collaborate daily with engineering peers and the AI First Product team to refine
specifications, resolve dependencies, and ship product increments that move agreedupon metrics.
specifications, resolve dependencies, and ship product increments that move agreedupon metrics.
• Partner with citizen developers and engineering peers to share knowledge, reusable
patterns, and AI First best practices, providing the guidance and insight their teams need
to succeed.
patterns, and AI First best practices, providing the guidance and insight their teams need
to succeed.
• Follow responsible AI practices in everything you build: fairness, explainability, model
monitoring, ethics, and regulatory alignment
monitoring, ethics, and regulatory alignment
Required Qualifications
Core Experience
• 4–8 years of professional software engineering experience building and shipping
production SaaS, including time as a senior developer or equivalent hands-on engineering
role.
production SaaS, including time as a senior developer or equivalent hands-on engineering
role.
• Strong software engineering fundamentals: production-level, cloud-native development in
the Microsoft stack (C#/.NET, React/TypeScript, RESTful Web APIs, SQL Server / Azure
SQL) and familiarity with distributed-systems patterns such as queues, caching, and
scalable APIs.
the Microsoft stack (C#/.NET, React/TypeScript, RESTful Web APIs, SQL Server / Azure
SQL) and familiarity with distributed-systems patterns such as queues, caching, and
scalable APIs.
• Experience building, deploying, and maintaining production services through CI/CD, testdriven development, and rapid, iterative release cycles, not just prototypes.
• Proven AI First delivery record: production systems built and shipped using agentic
workflows and spec-driven development, with demonstrable business outcomes.
workflows and spec-driven development, with demonstrable business outcomes.
• Hands-on experience designing and operating multi-agent systems, including
orchestration, planning, and observability in production environments.
orchestration, planning, and observability in production environments.
• Comfort owning features end to end, from specification through deployment and
operation, and iterating based on measured outcomes.
operation, and iterating based on measured outcomes.
• Excellent written and verbal communication skills; able to collaborate with product and
business stakeholders and explain technical trade-offs to non-technical audiences.
AI & Claude Ecosystem Proficiency (Claude Strongly Preferred)
business stakeholders and explain technical trade-offs to non-technical audiences.
AI & Claude Ecosystem Proficiency (Claude Strongly Preferred)
• Hands-on production experience with Claude Code as a primary development tool,
including AI coding agents, agentic workflows, CLI-based development, and directing
coding agents to ship production software.
including AI coding agents, agentic workflows, CLI-based development, and directing
coding agents to ship production software.
• Prompt engineering skills, including context engineering, structured outputs, and retrievalaugmented prompting applied in production agent systems.
• Production experience with the Claude API: tool use, document processing, streaming,
rate-limit management, and vision.
rate-limit management, and vision.
• Hands-on experience with multi-agent design patterns (planning, orchestration,
observability) and building and consuming MCP servers that expose enterprise data
sources as model-ready tools.
observability) and building and consuming MCP servers that expose enterprise data
sources as model-ready tools.
• Applied software engineering discipline in AI systems: version control, testing, and
deployment pipelines for agent-based and model-dependent services; evaluation
frameworks that measure AI quality, cost, and latency; and responsible-AI design aligned
with Anthropic's principles.
deployment pipelines for agent-based and model-dependent services; evaluation
frameworks that measure AI quality, cost, and latency; and responsible-AI design aligned
with Anthropic's principles.
HIGHLY DESIRED QUALIFICATIONS:
• Experience operating AI workflows in production, including agent observability and
debugging live systems.
debugging live systems.
• Experience with Azure cloud infrastructure and integrations with enterprise systems such
as Dynamics 365 F&O and Salesforce or equivalent CRM.
as Dynamics 365 F&O and Salesforce or equivalent CRM.
• Bachelor’s degree in Computer Science, Information Systems, or equivalent professional
experience.
experience.
At JSSI, we are committed to rewarding our team members with competitive and comprehensive compensation packages that reflect their contributions and talent.
For this role, the annual base pay generally ranges from $160,000 to $230,000, with the final offer determined by variable factors including but not limited to market location, job-specific knowledge, skills, education, and experience. In addition, your total rewards package may include an annual discretionary bonus plan, incentive or sales bonus plan, or other form of additional compensation, based on your role.
Additionally, for full-time employees based in the USA, Canada, or the Philippines, we are proud to offer a robust suite of benefits. This ranges from insurance offerings such as medical, dental, vision, retirement savings programs, among others, starting day one of employment. For a full overview of our offerings, visit the JSSI Benefits Page on our company website.
JSSI is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or other characteristic protected by law.
JSSI does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or Recruiting Team.
Skills Required
- 4-8 years of professional software engineering experience building and shipping production SaaS, including senior developer or equivalent hands-on engineering experience
- Production-level cloud-native development experience with C#/.NET, React/TypeScript, RESTful Web APIs, SQL Server/Azure SQL, and distributed systems patterns
- Experience building, deploying, and maintaining production services through CI/CD, test-driven development, and rapid iterative release cycles
- Production systems built and shipped using agentic workflows and spec-driven development, with demonstrable business outcomes
- Hands-on experience designing and operating multi-agent systems, including orchestration, planning, and observability in production
- Experience owning features end to end from specification through deployment, operation, and measured iteration
- Excellent written and verbal communication skills with the ability to collaborate with product and business stakeholders
- Hands-on production experience with Claude Code, including AI coding agents, agentic workflows, CLI-based development, and directing coding agents
- Prompt engineering skills including context engineering, structured outputs, and retrieval-augmented prompting in production agent systems
- Production experience with the Claude API, including tool use, document processing, streaming, rate-limit management, and vision
- Experience with multi-agent design patterns and building and consuming MCP servers exposing enterprise data sources as model-ready tools
- Software engineering discipline in AI systems, including version control, testing, deployment pipelines, evaluation frameworks, and responsible-AI design
- Experience operating AI workflows in production, including agent observability and debugging live systems
- Experience with Azure cloud infrastructure and integrations with Dynamics 365 F&O, Salesforce, or equivalent CRM
- Bachelor's degree in Computer Science, Information Systems, or equivalent professional experience
Similar Jobs
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
For more than 30 years, Jet Support Services, Inc. (JSSI), has been the leading independent provider of maintenance support and financial services to the business aviation industry. JSSI is responsible for maintaining in excess of 2,000 business jets, regional jets and helicopters across the globe and serves customers through an infrastructure of certified technical advisors. JSSI leverages this technical knowledge, experience, buying power and data to provide support at every stage of the aircraft life cycle; from aircraft acquisition to aircraft teardown and part out. GTCR, a leading private equity firm, is a majority investor in JSSI.
