Hands-On Development and Technical Leadership
Personally design, write, test, deploy, and support software for AI agents, agent workflows, tool integrations, and supporting services.
Build reusable tools and APIs that expose existing business capabilities to authorized AI agents and applications.
Implement agent capabilities such as tool selection and execution, context management, workflow state, error recovery, and appropriate human approval.
Develop production-ready integrations with existing systems, applying authentication, authorization, data protection, input validation, and transaction safeguards.
Own assigned capabilities through the full development lifecycle, including automated testing, deployment, monitoring, troubleshooting, and ongoing improvement.
Establish technical patterns through working implementations; conduct code reviews and mentor developers to improve engineering quality and delivery.
Measure and optimize reliability, response quality, latency, scalability, and operating cost.
Applied Innovation and Engineering Improvement
Evaluate emerging AI models, agent frameworks, and integration protocols through focused, hands-on experiments.
Build proofs of technology to validate feasibility, expose limitations, and inform implementation decisions.
Translate successful experiments into reusable engineering components and maintainable production solutions.
Develop evaluation approaches that measure agent behavior, tool execution accuracy, security, and business outcomes.
Recommend technology choices based on demonstrated results, integration needs, maintainability, and cost.
Technical Collaboration and Delivery Alignment
Work with product and engineering partners to translate business needs into clear technical requirements, acceptance criteria, and deliverable increments.
Collaborate with architecture, security, platform, and application owners to resolve integration dependencies and implement agreed standards.
Participate in design discussions, backlog refinement, and sprint planning, bringing implementation experience and practical technical recommendations.
Communicate progress, technical tradeoffs, risks, and decisions clearly to technical and nontechnical stakeholders.
Document interfaces, implementation decisions, and operational guidance so other teams can adopt and support delivered capabilities.
Qualifications
What’s needed to succeed (Minimum Qualifications)
Bachelor's degree
Computer Science, Information Technology, Engineering, or related field preferred
Seven years of software development experience, including substantial hands-on experience building APIs, distributed services, and enterprise integrations, with at least three years performing senior or principal-level development responsibilities.
Demonstrated hands-on experience building and deploying LLM-based applications or AI agents that invoke tools and integrate with business systems.
Strong software engineering skills, with proficiency in Python and experience with enterprise development technologies such as C#/.NET.
Practical experience implementing AI agents, tool/function calling, agent workflows, and integration with enterprise APIs.
Ability to translate technical designs into tested, deployable, maintainable code and independently troubleshoot complex issues.
Experience designing and building APIs, microservices, and distributed systems.
Experience with cloud services, preferably AWS, and automated build, test, and deployment pipelines.
Understanding of AI-specific risks, including prompt injection, unintended tool execution, sensitive data exposure, and unreliable model outputs, with experience implementing appropriate controls.
Experience with automated testing, agent evaluations, observability, performance tuning, and production support.
Ability to provide technical direction through implementation, code reviews, and mentoring.
Strong problem-solving and communication skills, including the ability to explain technical tradeoffs and collaborate across teams.
What will help you propel from the pack (Preferred Qualifications)
Experience implementing Model Context Protocol (MCP) servers or comparable standards for connecting AI applications to enterprise tools.
Experience with agent orchestration frameworks, model providers, and evaluation tooling.
Experience with OAuth/OIDC, API gateways, rate limiting, idempotency, and secure transaction processing.
Experience with airline shopping, retail, cart, booking, servicing, or comparable transactional systems.
Experience progressing AI experiments into supported production capabilities.
- The base pay range for this role is $140,600.00 to $183,108.00.
- The base salary range/hourly rate listed is dependent on job-related, factors such as experience, education, and skills. This position is also eligible for bonus and/or long-term incentive compensation awards.
You may be eligible for the following competitive benefits: medical, dental, vision, life, accident & disability, parental leave, employee assistance program, commuter, paid holidays, paid time off, 401(k) and flight privileges.
United Airlines is an Equal Opportunity Employer. We recruit, employ, train, compensate, and promote without regard to race, color, religion, national origin, gender identity, sexual orientation, disability, age, veteran status, or any other protected category under applicable law. We provide reasonable accommodations for applicants and employees with disabilities. To request an accommodation, contact JobAccommodations@united.com
