01Overview
Job Responsibilities
Own an entire mid-size engagement or lead a major workstream within a strategic transformation program.
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 program 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 modernization 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 organizational best practices.
Required 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, Cloud Run)
Harness CI/CD
SonarQube
Vertex AI
IBM Watsonx for Z (preferred)
Terraform
Camunda or Appian
Retrieval-Augmented Generation (RAG)
Agentic AI Frameworks
Model Context Protocol (MCP)
Preferred Skills
Experience leading application modernization and workflow transformation programs.
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.
Company
Webside - https://cogniify.ai/
Linkedin - https://www.linkedin.com/company/cogniify-ai/ originalSubdomain=in .
