Job Responsibilities

- Operate as either a Staff Full Stack Development Engineer (Individual Contributor) or an Engagement Lead (Management Track).

- Own and deliver complex technical initiatives across multiple engagements or strategic programs.

- Lead the design and implementation of enterprise-scale architectures and modernization initiatives.

- Solve complex engineering challenges, including agentic AI architectures, evaluation frameworks, and COBOL-to-Java modernization.

- Define and drive cross-program technical strategy, reference architectures, and engineering standards.

- Collaborate with Enterprise Architecture teams to align target-state solutions with business objectives.

- Design scalable, resilient, and high-performance enterprise integration solutions.

- Lead cloud transformation initiatives, including PCF-to-GCP migrations and IBM MQ-to-Kafka modernization.

- Establish and drive AI-Driven Software Development Lifecycle (AIDLC) standards across engagements.

- Design and implement Agentic AI architectures, Small Language Model (SLM) strategies, and Retrieval-Augmented Generation (RAG) solutions.

- Define AI evaluation frameworks and governance standards for enterprise AI applications.

- Present AI productivity metrics, ROI, and value realization frameworks to client engineering leadership.

- Serve as a trusted technical advisor to senior client stakeholders and engineering leaders.

- Influence engineering practices and architectural decisions across multiple engagements.

Management Responsibilities (Engagement Lead)
- Lead multiple workstreams, PODs, or strategic engagements simultaneously.

- Manage and mentor a team of 3–6 engineers, fostering technical growth and career development.

- Own project planning,



staffing, demand forecasting, and resource allocation.

- Drive delivery governance, business continuity planning (BCP), and program health.

- Monitor project KPIs, delivery metrics, risks, and overall client satisfaction.

- Lead estimation, delivery planning, and engineering pyramid optimization.

- Coach engineering managers and technical leads while promoting team health and engagement.

Required Technical Skills
- Java and Spring Boot

- Microservices Architecture

- GitHub and GitHub Copilot

- Maven

- PostgreSQL

- Docker

- Jira and Confluence

- Google Cloud Platform (GCP)

- Google Kubernetes Engine (GKE)

- Cloud Run

- Cloud SQL

- Pub/Sub

- Apache Kafka

- SonarQube

- Harness CI/CD

- Terraform

- Camunda or Appian

- Vertex AI

- IBM Watsonx for Z (preferred)

- Agentic AI Frameworks (Agents & Skills)

- Model Context Protocol (MCP)

- Retrieval-Augmented Generation (RAG)

- Enterprise Integration Patterns

- AI Evaluation Frameworks

Leadership & Preferred Qualifications
- Proven experience defining enterprise architecture and technical strategy across multiple programs.

- Robust expertise in cloud-native application modernization and legacy system transformation.

- Experience driving AI adoption and engineering productivity initiatives at scale.

- Excellent stakeholder management and executive communication skills.

- Demonstrated ability to mentor senior engineers and build high-performing teams.

- Strong delivery ownership with a focus on quality, scalability, and business outcomes.

- Recognized as a trusted advisor to client engineering leadership with impact beyond a single engagement.

https://www.linkedin.com/company/cogniify-ai/?originalSubdomain=in

📌 Staff FDE / Engagement Lead (Telangana)
🏢 Consultbae India
📍 Telangana