Java AI Lead

About Position:

We are looking for an experienced Java AI Lead with 14 to 17 years of expertise in designing, architecting, and delivering scalable enterprise solutions across large transformation programs. The ideal candidate will possess strong experience in Java, Spring Boot, Microservices, Kafka, Cloud Technologies, AI-enabled Software Development Lifecycle (AIDLC), and Enterprise Modernization initiatives.

• Role: Java AI Lead
• Location: Hyderabad
• Experience: Between 14-17 Years
• Job Type: Full Time Employment

What You’ll Do:

• Define and lead enterprise architecture strategies for large-scale modernization and digital transformation programs.
• Architect and deliver scalable applications using Java, Spring Boot, Microservices, and Kafka.
• Design target-state architectures for enterprise transformation initiatives including PCF to GCP, COBOL to Java, and IBM MQ to Kafka migrations.
• Lead development of complex distributed systems, event-driven architectures, and cloud-native solutions.
• Establish cross-program technical standards, reference architectures, and engineering frameworks.
• Drive AI-enabled Software Development Lifecycle (AIDLC) adoption across engineering teams.
• Design and implement Agentic AI architectures, evaluation frameworks, and productivity measurement models.
• Define enterprise integration strategies ensuring scalability, resiliency, security, and regulatory compliance.
• Collaborate with Enterprise Architects to align technology roadmaps with business objectives.
• Provide technical leadership across multiple workstreams, programs, and engineering teams.
• Own delivery governance, project health, risk management, KPIs, and operational metrics.
• Lead staffing strategy, workforce planning, demand forecasting, and business continuity planning.
• Drive engineering excellence through architecture reviews, code reviews, and technical governance processes.
• Build and maintain executive-level client relationships and act as a trusted technical advisor.
• Lead modernization, automation, and cloud adoption initiatives.
• Mentor architects, technical leads, and engineering teams across programs.
• Define best practices for cloud-native development, DevOps, security, and quality engineering.
• Support strategic proposals, solution design workshops, and technology roadmap discussions.
• Drive measurable business outcomes through engineering productivity improvements and AI-driven delivery practices.

Expertise You’ll Bring:

• 14 to 17 years of experience in Enterprise Application Development, Architecture, and Technology Leadership.
• Strong expertise in Java, Spring Boot, and Microservices architecture.
• Extensive experience designing and delivering large-scale distributed systems.
• Deep understanding of Kafka and event-driven architecture patterns.
• Proven experience leading enterprise modernization and transformation programs.
• Strong expertise in cloud-native architectures with Google Cloud Platform (GCP).
• Experience with GKE, Cloud Run, Cloud SQL, Pub/Sub, and related Google Cloud services.
• Hands-on experience with Docker, Kubernetes, and containerized deployments.
• Strong knowledge of PostgreSQL and enterprise database design principles.
• Experience defining enterprise architecture frameworks and technology governance models.
• Expertise in AI-enabled Software Development Lifecycle (AIDLC) implementation.
• Experience designing Agentic AI solutions, evaluation frameworks, and context-engineering strategies.
• Knowledge of MCP integrations and enterprise AI orchestration frameworks.
• Experience leveraging GitHub Copilot and AI-assisted engineering tools to improve productivity.
• Strong understanding of software engineering metrics, developer productivity measurement, and value realization frameworks.
• Experience with DevOps, CI/CD pipelines, release automation, and platform engineering.
• Expertise with Maven, GitHub, Jira, Confluence, SonarQube, and modern development platforms.
• Experience with Harness and advanced deployment orchestration platforms.
• Knowledge of Terraform and Infrastructure as Code practices.
• Experience with workflow and business process platforms such as Camunda and Appian.
• Exposure to Vertex AI and enterprise AI platforms.
• Familiarity with IBM Watsonx for Z and modernization strategies.
• Strong understanding of architecture patterns, resiliency engineering, scalability, and security principles.
• Exceptional…