Full Stack Leads with Airport Systems development experience

Seven N Half; Gurugram District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Air India seeks a Full Stack Tech Lead to build and scale modern digital products with AI capabilities, including personalization, chatbots, and intelligent automation. The role focuses on moving ideas from prototype to production, defining technical architecture, and ensuring scalable, reliable systems while guiding engineering teams toward AI-powered innovation.

Responsibilities include defining full-stack architecture, integrating AI/ML services, collaborating with AI/ML teams, and

Qualifications

• Proven track record of leading full-stack teams
• Experience turning prototypes into production-grade systems
• Strong ability to define scalable full-stack architectures for AI-enabled platforms
• Excellent collaboration with AI/ML, Product, UX, and DevOps teams

Responsibilities

• Define full-stack architecture for AI-enabled platforms
• Collaborate with AI/ML teams to embed AI features in production systems
• Lead and mentor full-stack and AI-focused engineers
• Drive engineering excellence, code quality, and performance
• Promote rapid prototyping with engineering rigor
• Oversee architecture reviews and trade-off analyses
• Ensure security, reliability, and scalability in production

Skills

Technical leadership

Mentorship

Prototype to production

Communication

AI integration

Tools

Docker

Kubernetes

GitHub Actions

Jenkins

Terraform

Datadog

Job description

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.

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

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