About the job

Job Title: Senior Technical Lead (Java + AI)

Experience: 10 - 18 years

Location: Bengaluru/Greater Noida

Notice Period: Immediate/ Serving Notice/ Max 30 Days

We at Coforge are hiring Senior Technical Lead (Java + AI) with the following skillset:

JD: Senior Generative AI Architect

We are seeking a highly capable, hands-on Senior Technical Developer to contribute to a large-scale technology modernisation programme. The role requires deep Java/J2EE engineering expertise, strong cloud-native development skills, and the ability to use both AI-assisted tools and AI-agentic engineering approaches to accelerate delivery without compromising quality, security, compliance, maintainability or operational resilience.

The successful candidate will work with minimal supervision, take end-to-end ownership of assigned outcomes, and contribute across analysis, design, build, testing, deployment and production-readiness activities. Prior experience in airline, travel or GDS platforms is strongly preferred.

Key Responsibilities:

Java and Application Engineering: Java 11/17 or later; J2EE/Jakarta EE; Spring Boot; Spring Framework; Spring Data/JPA; Hibernate; REST/JSON/XML; Maven or Gradle; unit and integration testing.

Architecture and Integration: Microservices; API-first design; event-driven architecture; distributed systems; resilience patterns; domain-driven design; synchronous and asynchronous integration.

Cloud, Containers and DevOps: Google Cloud Platform; GKE; Docker; Kubernetes; Helm or equivalent; Git; CI/CD; infrastructure/configuration awareness; logging, monitoring and observability.

Data Engineering:



Strong SQL; relational databases such as Oracle or PostgreSQL; schema design; query optimisation; transaction management; exposure to NoSQL or messaging platforms is advantageous.

Engineering Quality: Test automation; code coverage; static analysis; dependency management; performance engineering; peer review; production troubleshooting and root-cause analysis.

Security and Compliance: OWASP Top 10; secure coding; IAM; secrets management; encryption; API security; vulnerability remediation; DevSecOps controls; audit and change-management discipline.

Hands-on Software Engineering

- Design, develop, test and maintain enterprise-grade applications using Java, J2EE, Spring Boot and related frameworks.
- Build secure, scalable and resilient microservices, REST APIs and event-driven components.
- Apply clean-code, SOLID, domain-driven design and twelve-factor application principles.
- Produce maintainable, testable and production-ready code with appropriate technical documentation.
- Perform code reviews, troubleshoot complex issues, optimise performance and reduce technical debt.

Modernisation Delivery
- Analyse and reverse engineer legacy applications, interfaces, data flows and business rules.
- Translate legacy functionality into modern service boundaries, APIs and cloud-native implementation patterns.
- Contribute to solution design, decomposition, dependency analysis,



migration planning and cutover readiness.
- Create reusable engineering accelerators, templates and reference implementations for modernisation squads.

GCP and GKE Engineering
- Develop, containerise and deploy workloads on Google Kubernetes Engine within Google Cloud Platform.
- Work with Docker, Kubernetes manifests or Helm, configuration management, secrets, service accounts, ingress and workload identity.
- Contribute to CI/CD pipelines, automated quality gates, observability, logging, monitoring and production support.
- Engineer for reliability, scalability, fault tolerance, cost awareness and operational supportability.

Security, Risk and Compliance
- Apply secure-by-design and privacy-by-design practices throughout the software development lifecycle.
- Follow OWASP guidance, secure coding standards, least-privilege access, secrets management, encryption and API security practices.
- Remediate vulnerabilities identified through SAST, DAST, software composition analysis, container scanning and penetration testing.
- Maintain traceability and evidence required for enterprise governance, audit, change management and regulatory compliance.
- Ensure AI-generated outputs are reviewed, validated and handled in accordance with data classification, intellectual-property and responsible-AI policies.

AI-related Skill Requirements
- Candidates should demonstrate practical capability in both AI-assisted engineering and AI-agentic engineering. Tool familiarity alone is not sufficient; the candidate must be able to apply these capabilities responsibly within an enterprise delivery setting.

📌 Java AI Lead (Bengaluru)
🏢 Coforge
📍 Bengaluru