Principal Engineer, IT Machine Learning

ANSR is hiring for one of its clients.

About American Airlines:

To Care for People on Life's Journey®. Together with our American Eagle regional partners, we offer thousands of flights daily to more than 350 destinations in more than 60 countries.

American Airlines is transforming the way it delivers technology to its customers and team members worldwide.

American's Tech Hub in Hyderabad, India, is our latest technology office location and home to team members who drive technical innovation and engineer unrivalled digital products to best serve American's customers and team members. With U.S. tech hubs in Dallas-Fort Worth, Texas and Phoenix, Arizona, our new team in Hyderabad, India enables better support of our 24/7 operation and positions American to deliver industry-leading technology solutions that create a world-class customer experience.

We are excited to announce an opening for Principal Engineer, IT Machine Learning at American Airlines. Please find below the details of the role and its responsibilities.

Experience Range:

• 9- 12 Years

Skills Required:

Generative AI, Gen AI, LangChain, Langraph, Semantic Kernel, Crew AI, Open AI, MLOps, Machine Learning, ML, Python

Intro:

Are you ready to explore a world of possibilities, both at work and during your time off Join our American Airlines family, and you'll grow your expertise to become the best version of you. As you embark on a new journey, you'll tackle challenges with flexibility and grace, learning new skills and advancing your career while having the time of your life. Feel free to enrich both your personal and work life and hop on board!

Why you'll love this job:

As one diverse, high-performing team dedicated to technical excellence, you will focus relentlessly on delivering unrivaled digital products that drive a more reliable and profitable airline. The application of algorithms and models to enable computers to learn from and make predictions or decisions based on data. This domain is generally a subset of the AI or Data Domain.

What you'll do:

As noted above, this list is intended to reflect the current job but there may be additional functions that are not referenced. Management will modify the job or require other tasks be performed whenever it is deemed appropriate to do so, observing, of course, any legal obligations including any collective bargaining obligations.

• Writes, tests, and documents technical work products (e.g., code, scripts, processes) according to organizational standards and practices
• Devotes time to raising the quality and craftsmanship of products and systems
• Conducts root cause analysis to identify domain level problems and prescribes action to mitigate
• Designs self-contained systems within a team's domain, and leads implementations of significant capabilities in existing systems
• Coaches team members in the execution of techniques to improve reliability, resiliency, security, and performance
• Decomposes intricate and interconnected designs into implementations that can be effectively built and maintained by less experienced engineers
• Anticipates trouble areas in systems under development and guides the team in instrumentation practices to ensure observability and supportability
• Defines test suites and instrumentation that ensures targets for latency and availability are being consistently met in production
• Leads through example by prioritizing the closure of open vulnerabilities
• Evaluates potential attack surfaces in systems under development, identifies best practices to mitigate, and guides teams in their implementation
• Leads team in the identification of small batches of work to delivery the highest value quickly
• Ensures reuse is a first-class consideration in all team implementations and is a passionate advocate for broad reusability
• Formally mentors teammates and helps guide them to and along needed learning journeys
• Observes their environment and identifies opportunities for introducing new approaches to problems.

All you'll need for success:

Minimum Qualifications- Education & Prior Job Experience:

• Bachelor's degree in computer science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training
• 8+ years of experience designing, developing, and implementing large-scale solutions in production environments.

Preferred Qualifications- Education & Prior Job Experience:

• Master's degree in computer science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training
• Airline Industry experience.

Skills, Licenses & Certifications:

Proficiency and demonstrated experience in the following technologies/frameworks:

Programming & Backend Development:

• Python (backend services/APIs, automation, testing)
• SQL (advanced querying, window functions, optimization, data meling (fundamentals)
• REST APIs, JSON, service integration patterns

AI Agents / Agent Frameworks (Must-have):

• Hands-on experience with at least one enterprise-grade agent framework such as:
• LangGraph/Crew AI/ Autogen (or equivalent agent orchestration frameworks)
• Copilot Studio agents /Open AI agents (or equivalent)
• Agent orchestration, tool/function calling, structured outputs, evaluation and iteration patterns

Analytics, Reporting & Dashboards:

• Power BI and/or Tableau
• Metrics definition, reporting automation, executive-ready dashboards

Cloud Platforms:

• Microsoft Azure or AWS
• Experience deploying data/AI workloads in cloud environments

Data & Integration:

• Data pipelines/ELT concepts, dataset curation for analytics
• Integration with an enterprise risk assessment & governance workflow platform (tool-agnostic)

AI/ML Fundamentals:

• Applied understanding of ML lifecycle concepts
• Familiarity with LLM concepts like prompting, context handling, grounding patterns like RAG, Evals, Agent Behavior Monitoring etc.

Governance, Risk & Regulatory Knowledge:

• Working awareness of AI/data regulations and governance expectations such as GDPR, EU AI Act, and similar privacy/AI governance frameworks
• Understanding of governance controls: evidence capture, auditability, traceability, Observability, exception management, and reporting

Software Engineering Practices:

• Object-oriented design and clean coding principles
• Version control (Git) and CI/CD fundamentals
• Testing practices (unit/integration), documentation, logging/monitoring, operational readiness.

Licenses & Certifications (Preferred, not required):

• Microsoft Certified: Azure Data Engineer Associate / Azure Developer Associate / Azure AI Engineer Associate
• AWS Certified Developer – Associate / AWS Certified Data Engineer – Associate (or equivalent AWS certifications)
• Power BI or Tableau certification (if applicable/available)
• Any relevant certifications in data privacy or AI governance/risk (e.g., privacy fundamentals, responsible AI).

Methodologies & Tools (Preferred):

• Experience working in Agile (Scrum/Kanban) environments
• Familiarity with DevOps toolchains (e.g., CI pipelines, code quality checks, artifact repos)

Language, Communication Skills, & Physical Abilities

Ability to effectively communicate both verbally and written with all levels within the organization Physical ability necessary to safely and successfully perform the essential functions of the position, with or without any legally required reasonable accommodations that do not pose an undue hardship.