About the role
Responsibilities:
- Own an entire mid-size engagement or lead a major workstream within a strategic transformation programme.
- Serve as the primary technical point of contact for clients at the module/workstream level.
- Lead the design, architecture, and end-to-end delivery of assigned programme modules.
- Define coding standards, architecture guidelines, and engineering best practices.
- Translate high-level business requirements into scalable technical solutions and execution plans.
- Scope and estimate new workstreams while driving technical solutioning.
- Drive AI-Driven Software Development Lifecycle (AIDLC) adoption and measure productivity improvements using AI tools such as GitHub Copilot and Speckit.
- Conduct architecture reviews, code reviews, and pull request (PR) reviews to ensure code quality.
- Mentor and guide junior and mid-level engineers, fostering technical excellence.
- Manage client technical relationships through design discussions, demos, and solution presentations.
- Build and maintain high-performance, resilient, and regulatory-compliant enterprise applications.
- Design and implement event-driven architectures using Kafka.
- Develop and maintain applications using Java, Spring Boot, and microservices architecture.
- Work with GCP services including GKE, Cloud SQL, Pub/Sub, Cloud Run, and Vertex AI.
- Design coexistence and modernisation strategies for mainframe-to-Java transformations.
- Develop Retrieval-Augmented Generation (RAG) and Agentic AI solutions.
- Design advanced context engineering strategies for enterprise AI applications.
- Integrate enterprise systems using Model Context Protocol (MCP).
- Define AI model evaluation strategies and improve developer productivity through AI-enabled engineering practices.
- Collaborate with cross-functional teams to deliver scalable and secure enterprise solutions.
- Contribute reusable assets, engineering playbooks, and organisational best practices.
Requirements:
- Technical Skills: Java and Spring Boot, microservices architecture, event-driven architecture (Kafka), GitHub, GitHub Copilot, Maven, PostgreSQL, Docker, Jira and Confluence, Google Cloud Platform (GKE, Cloud SQL, Pub/Sub, and Cloud Run), Harness CI/CD, SonarQube, Vertex AI, IBM Watsonx for Z (preferred), Terraform, Camunda or Appian, retrieval-augmented generation (RAG), agentic AI frameworks, and Model Context Protocol (MCP).
Preferred Skills:
- Experience leading application modernisation and workflow transformation programmes.
- Strong understanding of cloud-native architecture and distributed systems.
- Experience implementing AI-powered software development practices.
- Excellent client-facing communication and stakeholder management skills.
- Proven technical leadership with mentoring and team development experience.
- Ability to drive engineering excellence, innovation, and delivery ownership.