Gurugram, Haryana, India
Open 4 months, first seen by us 144 days agoExpatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded
Experience building AI agents or autonomous systems • 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 • Experience optimizing LLM performance, scalability, and cost efficiency
Open 4 monthsWe first saw this posting 144 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 144
Up longer than most. Similar jobs usually come down between day 7 and day 72.
Well past United Airlines’s usual: its jobs come down by about day 10.
From 4,735 similar postings that came down, and 221 of United Airlines’s. Coming down is not always a hire.
13 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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We are seeking a Generative AI Engineer to build and scale AI-native platforms and services. This role requires a strong full-stack engineering foundation combined with hands-on experience in Generative AI, cloud-native architectures, and MLOps. You will contribute to the design and development of intelligent systems, AI agents, and reusable platforms, working across backend, frontend, and middleware layers. The ideal candidate brings both hands-on delivery capability and architectural awareness to build robust, scalable, and observable AI solutions. • 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 This position is offered on local terms and conditions. Expatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded. This position is for United Airlines Business Services Pvt. Ltd - a wholly owned subsidiary of United Airlines Inc.
What’s needed to succeed (Minimum 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 • Experience with frontend frameworks (e.g., React, Angular, or equivalent) • Strong understanding of API design, middleware, and microservices architecture • Hands-on experience with Generative AI technologies (LLMs, prompt engineering, RAG, vector databases) • Experience working with AWS cloud infrastructure and building cloud-native applications • 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) What will help you propel from the pack (Preferred Qualifications):
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.
Job overview and responsibilities
We are seeking a Generative AI Engineer to build and scale AI-native platforms and services. This role requires a strong full-stack engineering foundation combined with hands-on experience in Generative AI, cloud-native architectures, and MLOps.
You will contribute to the design and development of intelligent systems, AI agents, and reusable platforms, working across backend, frontend, and middleware layers. The ideal candidate brings both hands-on delivery capability and architectural awareness to build robust, scalable, and observable AI solutions.
• 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
This position is offered on local terms and conditions. Expatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded. This position is for United Airlines Business Services Pvt. Ltd - a wholly owned subsidiary of United Airlines Inc.
• 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
• Experience with frontend frameworks (e.g., React, Angular, or equivalent)
• Strong understanding of API design, middleware, and microservices architecture
• Hands-on experience with Generative AI technologies (LLMs, prompt engineering, RAG, vector databases)
• Experience working with AWS cloud infrastructure and building cloud-native applications
• 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)
• Experience building AI agents or autonomous systems
• 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
• Experience optimizing LLM performance, scalability, and cost efficiency
Key Competencies
• 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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Gurugram, Haryana, India
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