JD – This role specifically requires Full Stack Leads with Airport Systems
development exp
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.
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
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.
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)
Cross-functional collaboration (Product, UX, DevOps, Data Science)
Ability to move from prototype to production-grade solutions
Hiring and team capability building
Educational and Experience Requirements
Minimum Education Requirements
Bachelor’s degree in computer science, Software Engineering, or
related technical field OR equivalent practical experience with
10+ years in software development
Minimum Requirement
Desired
Experience
13+ 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)