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 recent 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

📌 Staff FDE (Telangana)
🏢 Consultbae India
📍 Telangana