Job Responsibilities

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

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

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

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

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

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

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

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

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

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

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

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

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

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Influence engineering practices and architectural decisions across multiple engagements.

Management Responsibilities (Engagement Lead)

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Lead multiple workstreams, PODs, or strategic engagements simultaneously.

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

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Own project planning, staffing,



demand forecasting, and resource allocation.

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

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

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Lead estimation, delivery planning, and engineering pyramid optimization.

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

Required Technical Skills

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Java and Spring Boot

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Microservices Architecture

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GitHub and GitHub Copilot

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Maven

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PostgreSQL

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Docker

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Jira and Confluence

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Google Cloud Platform (GCP)

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Google Kubernetes Engine (GKE)

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Cloud Run

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Cloud SQL

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Pub/Sub

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Apache Kafka

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SonarQube

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Harness CI/CD

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Terraform

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Camunda or Appian

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Vertex AI

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IBM Watsonx for Z (preferred)

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Agentic AI Frameworks (Agents & Skills)

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Model Context Protocol (MCP)

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Retrieval-Augmented Generation (RAG)

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Enterprise Integration Patterns

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AI Evaluation Frameworks

Leadership & Preferred Qualifications

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Proven experience defining enterprise architecture and technical strategy across multiple programs.

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

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Experience driving AI adoption and engineering productivity initiatives at scale.

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Excellent stakeholder management and executive communication skills.

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

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

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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 (Madhavaram)
🏢 Leading
📍 Madhavaram