About the role

Role Name : Airport System Development

Level : C2 ( Chief Manager)

Location : Gurgaon

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
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.

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. Behavioral & 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

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)
Relevant technology certifications (Java, Python, Cloud)