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United Airlines
Engineer - Generative AI
United Airlines
Gurugram•On-site•1-3 Yrs•Jun 25
Job description
Overview
As a Generative AI Engineer at United's Digital Technology team, your role will involve designing and scaling AI-native platforms and services.
Qualifications
- 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
- Designing, developing, and deploying AI-native applications and services leveraging Generative AI and LLMs
- Building and maintaining end-to-end solutions across backend (Python), middleware, and frontend layers
- Developing scalable APIs and microservices to enable AI-driven capabilities across platforms
- Implementing and operationalizing LLM-based workflows, including prompt orchestration, RAG pipelines, and agent frameworks
- Contributing to architecture design and system decomposition to ensure scalability, resilience, and extensibility
- Building and managing cloud-native solutions on AWS, leveraging services such as Lambda, ECS/EKS, S3, and API Gateway
- Establishing and maintaining MLOps practices, including CI/CD pipelines, model deployment, versioning, and monitoring
- Implementing observability and telemetry frameworks (logging, tracing, metrics) to ensure reliability and performance of AI systems
- Collaborating with cross-functional teams to translate business requirements into scalable technical solutions
- Continuously optimizing performance, cost, and latency of AI workloads and services
- 35 years of experience in software engineering with strong hands-on development skills and exposure to system design
- Proficiency in Python for backend development