United Airlines
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Gurugram · On-site · 3-6 Yrs · Aug 25
Airlines, Airports & Air Transportation · 10000+ Employees · Chicago, US
We're connecting people and uniting the world. We've paired the world's most comprehensive route network with our modern fleet, the most fuel-efficient among U.S. network carriers (when adjusted for cabin size). We have seven US hub locations, including hubs in the four largest cities in the United States and almost 90,000 employees residing in every U.S. state and in countries around the world. We also host an industry-leading loyalty program that provides more opportunities to earn and redeem miles worldwide and are leading the industry in our environmental initiatives. The time is right to join United. We're reinventing our company from the ground up, and opportunities exist for all experience levels. If you are a dedicated individual who is ready to move your career in a positive new direction, United Airlines is the place for you.
Hiring: Engineering
What employees say
+ Nice Company, Great Benefits, Good Management
− No Major Cons in United Airlines
More reviews on the company profile.
Interview experience · Associate Analyst
Round 1 (Initial Screening Call): A phone call with HR/recruiter. This was a smooth discussion covering my background, resume details, work experience, standard situational questions, and overall fit for the company and
Average difficulty · India · 99 reports
More interview insightsJob description
Overview
Achieving our goals starts with supporting yours. Grow your career, access top-tier health and wellness benefits, build lasting connections with your team and our customers, and travel the world using our extensive route network.
Responsibilities
- Design, develop, and deploy AI-native applications and services leveraging Generative AI and LLMs
- Build and maintain end-to-end solutions across backend (Python), middleware, and frontend layers
- Develop scalable APIs and microservices to enable AI-driven capabilities across platforms
- Implement and operationalize LLM-based workflows, including prompt orchestration, RAG pipelines, and agent frameworks
- Contribute to architecture design and system decomposition, ensuring scalability, resilience, and extensibility
- Build and manage cloud-native solutions on AWS, leveraging services such as Lambda, ECS/EKS, S3, and API Gateway
- Establish and maintain MLOps practices, including CI/CD pipelines, model deployment, versioning, and monitoring
- Implement observability and telemetry frameworks (logging, tracing, metrics) to ensure reliability and performance of AI systems
- Collaborate with cross-functional teams to translate business requirements into scalable technical solutions
- Continuously optimize performance, cost, and latency of AI workloads and services
Qualifications
- 3–5 years of experience in software engineering with strong hands-on development skills and exposure to system design
- Proficiency in Python for backend development
- Strong understanding of API design, middleware, and microservices architecture
- Hands-on experience with Generative AI technologies (LLMs, prompt engineering, RAG, vector databases)
- Familiarity with MLOps practices and tools for model lifecycle management
- Working knowledge of observability and telemetry (e.g., OpenTelemetry, Prometheus, Grafana, CloudWatch)
- Understanding of data storage and retrieval systems (relational, NoSQL, and vector databases)
- Exposure to platform engineering concepts such as control plane and application plane architectures
- Familiarity with lightweight SDKs and developer enablement tools
- Knowledge of AI evaluation, governance, and responsible AI practices
- Strong problem-solving and analytical thinking
- Ability to operate across multiple layers of the technology stack
- Balance of execution excellence and architectural thinking
- Effective collaboration and communication skills
- Continuous learning mindset in a rapidly evolving AI ecosystem
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