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
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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 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)
