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Airport Systems - Tech Lead

Location:  Gurugram
|
May 25, 2026
  1. Job Purpose

The Full Stack Tech Lead builds and scales modern digital products across Air India. This role requires strong full-stack engineering expertise with the ability to integrate AI capabilities such as personalization, chatbots, and intelligent automation into production applications.

The focus is on taking ideas from prototype to production. The Tech Lead also defines the technical architecture, makes sure systems are scalable and reliable, and guides engineering teams while pushing innovation in AI-powered products.

 

  1. Key Accountabilities

 

Strategic Activities

  • Define full-stack architecture for digital platforms with AI capabilities
  • Integrate AI/ML services into customer and operational platforms
  • Collaborate with AI/ML teams to embed AI features into production systems
  • Ensure AI integrations follow enterprise architecture and security standards
  • Balance AI feature experimentation with full-stack reliability
  • Drive technical debt management and code quality initiatives
  • Define development standards and best practices

Technical Execution

i.  Full Stack Development

  • Build and ship core product features from prototype to production in short cycles
  • Design scalable frontend systems using Angular/React/TypeScript
  • Develop high-performance backend services (Java/Spring Boot and/or Python)
  • Own BFF layers where required
  • Integrate AI services into frontend and backend applications
  • Implement AI feature UI/UX (streaming responses, loading states, error handling)
  • Collaborate with AI/ML teams on prompt optimization and performance
  • Monitor AI feature performance and collaborate on debugging with AI specialists

ii. Engineering Excellence

  • Design real-time AI features with scalable data pipelines
  • Implement strong automated testing practices
  • Drive performance optimization across UI, API, and AI layers
  • Ensure production stability and fast incident resolution

Team Management

  • Lead and mentor full-stack and AI-focused engineers
  • Foster a culture of rapid prototyping with strong engineering rigor
  • Conduct architecture, design, and code reviews focused on performance, reliability, and scalability
  • Drive engineering excellence in AI feature development and system integration with measurable business impact
  • Guide teams in writing concise design documents outlining trade-offs and technical decisions
  • Promote “mentor by code” culture — hands-on technical leadership
  • Collaborate with Data Science, Product, UX, and DevOps teams
  • Support hiring and capability building in AI engineering and modern full-stack practices

Any other additional responsibility could be assigned to the role holder from time to time, as a standalone project or regular work. The same would be suitably represented in the Primary responsibilities and agreed between the incumbent, reporting officer, and HR.

 

 

  1. Skills Required for the Role

a. Technical Skills

i. Backend

  • Strong expertise in Java (17+) with Spring Boot 3.x
  • OR strong expertise in Python (3.9+) with FastAPI/Flask
  • RESTful API design and microservices architecture
  • Event-driven systems (Kafka, RabbitMQ, or similar)
  • Database design: PostgreSQL, MongoDB, Redis
  • API security: OAuth2, JWT, API gateways
  • Performance optimization and caching strategies
  • Unit testing, integration testing (JUnit, Pytest, etc.)

ii. Frontend

  • Proven experience with Angular OR React with TypeScript
  • Modern JavaScript/TypeScript (ES6+)
  • State management (Redux, NgRx, Context API)
  • Responsive design and CSS frameworks (Tailwind, Material UI)
  • Frontend build tools (Webpack, Vite)
  • Performance optimization techniques
  • Testing frameworks (Jest, Cypress, Playwright)

iii. AI Enablement

  • Experience integrating AI/ML APIs into applications
  • Familiarity with LLM service consumption (OpenAI, Azure OpenAI, AWS Bedrock)
  • Understanding of prompt engineering basics
  • Awareness of AI UX patterns (streaming, loading, errors, feedback)
  • Knowledge of AI costs and latency considerations
  • Ability to collaborate with data science/ML teams
  • Understanding of when to use AI vs traditional approaches

iv. Architecture & Cloud

  • Cloud-native design patterns (AWS, Azure, or GCP)
  • Microservices and BFF architectures
  • Containerization (Docker) and orchestration basics (Kubernetes)
  • CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI)
  • Observability: logging, metrics, tracing (Datadog, New Relic, ELK)
  • Scalable distributed system design
  • Infrastructure as Code (Terraform, CloudFormation) awareness

b. Core Engineering Competencies

  • Strong computer science fundamentals (algorithms, data structures)
  • 8+ years full-stack development experience
  • Proven track record in shipping production systems end-to-end
  • Experience with high-scale, real-time systems
  • Strong debugging and troubleshooting skills
  • Translating business requirements into technical solutions
  • Performance optimization across the stack

c. Behavioural & Leadership Skills

  • Technical leadership and team mentorship
  • Clear communication of technical decisions and trade-offs
  • Design documentation (RFCs, architecture diagrams)
  • Ownership and accountability mindset
  • Comfortable with ambiguity and rapid iteration
  • Cross-functional collaboration (Product, UX, DevOps, Data Science)
  • Ability to move from prototype to production-grade solutions
  • Hiring and team capability building
  1. Educational and Experience Requirements

 

Minimum Education Requirements

Bachelor’s degree in computer science, Software Engineering, or related technical field OR equivalent practical experience with 7-10 years in software development

 

Minimum Requirement

Desired

Experience
  • 7+ years of full-stack software development experience
  • 3+ years in technical leadership or senior engineering roles
  • Proven experience with production systems at scale
  • Experience with both frontend and backend technologies
  • Demonstrated ability to integrate third-party services and APIs
  • 10+ years in full-stack development
  • Experience in airline, travel, or e-commerce industries
  • Prior experience integrating AI/ML services or features
  • Experience with high-traffic, mission-critical systems
  • Track record of mentoring and growing engineering teams

 

Certifications

  • Azure Solutions Architect Expert
  • Azure AI Engineer Associate (AI-102) (nice to have)
  • Relevant technology certifications (Java, Python, Cloud)

 

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