Live opening · Posted 2 days ago
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Description supplied by the original job listing.
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.
Experience
5-8 yrs
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