Tech Lead Software Engineer - AI Ops/Support

About Us

• At Southwest Airlines, we believe that flying should feel like freedom. For over 50 years,we’vebeen connecting people to what matters most with low fares, legendary hospitality, and a heart for service. Our culture is built on the principles of fun, friendliness, and family, making us one of the most admired workplaces in the world.

  Ifyou’repassionate about making a difference, love working in a fast-paced environment, and want to help millions of travelers reach their destinations with a smile, Southwest Airlines is the place for you. Here, your career can truly takeflight.

Job Summary

• The AI Ops & Support Pod partners with the AI Platforms team to operate, monitor, and support Southwest's AI and agentic capabilities around the clock. The team manages these solutions from an SLA and outcomes-based perspective — ensuring reliability, performance, and effectiveness, and retraining models when needed to keep results on target.
• As Tech Lead Software Engineer – AI Ops/Support, you'll set the technical bar for how Southwest's enterprise AI and agentic platforms are supported in production. You'll lead L2/L3 engineering, drive SRE practices at scale, and build an automation-first culture that turns every recurring incident into a permanent improvement. You'll also help shape a growing engineering community in our Hyderabad office focused on production reliability for one of the most complex and fast-evolving domains in technology.
• Lead and motivate a Team of developers in the planning, delivery, and operation of highly reliable software. Accountable for the technical quality of the software that the Development Team produces and closely collaborates with the Business and other Stakeholders to ensure software meets functional and non-functional expectations. Act as an interface between the Development Team and Leadership, ensuring capacity and skillsets are aligned to meet ongoing delivery expectations. Time is allocated across Project Leadership, Technical Leadership/Mentoring, and Software Development/System Engineering.

• Provide accurate development estimates in support of feasibility assessments and planned development activities
• Create, maintain, review and approve application designs in collaboration with Solution Architects and shared services Teams, ensuring alignment to the appropriate solution architectures and taking tradeoffs into account
• Develop, maintain, and review software with a focus on quality and maintainability
• Develop, maintain, review, and execute unit, functional, and integration tests with a focus on automation and test-driven development
• Provide technical oversight for performance testing, ensuring plan and outcomes align to expected non-functional requirements
• Plan and oversee application deployment activities and sequencing in non-production and production environments
• Investigate new technologies that could improve the applications and development activities
• Identify and resolve technical debt as appropriate, weighing the development effort against the value returned
• Mentor and coach Development Team on relevant architecture, design, development, and operations topics
• Evaluate code to ensure that it is valid, is properly structured, meets industry standards, and is compatible with browsers, devices, or operating systems
• May perform other job duties as directed by Employee's Leaders

• Advanced knowledge of software development methodologies, practices, concepts, and technologies
• Advanced knowledge of at least one programming language and at least general knowledge of one or more additional programming languages
• Knowledge of project management methodology and principles
• Ability to demonstrate strong analytical and problem-solving abilities with a proactive mindset to get ahead of issues
• Skilled in communication with ability to articulate a clear direction and priorities on ideas, approaches, concepts, options, risks, impacts, and recommendations to technical, non-technical, and Leadership audiences with ability to adapt the message accordingly
• Ability to articulate the technical implementation and how it provides business value
• Ability to lead ideation, presentation, and group-thinking sessions
• Ability to influence effectively without authority up through Senior Leadership levels to achieve desired business outcomes
• Ability to lead multiple efforts concurrently, whether administrative or project related, while maintaining a successful level of completion in their own work
• Ability to work in a fast-paced, Team-based, Customer service-oriented environment

• Preferred:

  • End-to-end ownership of production support or SRE for cloud-based AI, agentic, or ML systems
  • SRE patterns at scale — SLOs, error budgets, blameless post-mortems, MTTR reduction
  • Advanced AWS for AI workloads (EKS, ECS, Lambda, API Gateway, IAM, VPC, CloudWatch)
  • Observability tooling for distributed systems (Datadog, CloudWatch, OpenTelemetry, Prometheus)
  • MLOps/AIOps and AI eval/drift monitoring (MLflow, SageMaker, Bedrock, Ragas, TruLens, Evidently)
  • Runbook and playbook authorship for consistent resolution and shift-left knowledge transfer
  • Balancing L2 support with L3 enhancement delivery so the team owns durable improvement work
  • Broad technical fluency across cloud, data, and AI/agentic stacks

• Required: Bachelor's degree in Computer Science, Engineering, Information Systems or related field and/or equivalent formal training

• Required:

  • Expert level experience, expansive and far reaching knowledge in software engineering, including 8+ years of relevant work-related experience.

• Preferred:

  • Production AI on AWS Bedrock or SageMaker — model hosting, embeddings, vector DBs

  • Agentic frameworks (LangChain, LangGraph, CrewAI) in a support or reliability context

  • L3 enhancements measured by MTTR reduction, SLA attainment, or ticket deflection

  • L1/L2/L3 operating models, runbooks, and 24/7 on-call across a global team

  • Multi-region DR and chaos engineering for cloud-native workloads

  • FinOps for AI inference (GPU utilization, batching, quotas)

  • Model retraining loops and feedback pipelines in production

  • Cross-functional partnership with peer Tech Leads across Technology

  • Large enterprise support environments

• Must meet confidentiality expectations as to confidential, proprietary and sensitive Company information
• Ability to work extended hours as needed