Agentic AI Engineer

Cybage Software; Pune District; Hybrid; INR 2,400,000 - 4,200,000; Full time

Job summary

Cybage Software in Pune, India seeks a self-directed senior engineer to architect and build secure enterprise applications and AI-enabled workflows, with strong full‑stack skills and hands‑on MCP integrations.

This role involves designing reusable components, implementing authentication and RBAC, mentoring engineers, and guiding technical direction across teams in a hybrid work environment (3 days in office per week).

Qualifications

• Bachelor's in CS/Software Engineering or related STEM field.
• 5+ years software development experience or equivalent demonstrated skill.
• Strong React, API development, application architecture, automated testing, CI/CD.
• Experience building AI-assisted apps, agentic workflows, or tool-calling solutions.
• Experience with MCP, structured outputs, context management, or comparable frameworks.
• Experience with auth/authz, RBAC, and secure coding practices.

Responsibilities

• Architect and develop secure enterprise applications (React, TypeScript, Python, API services).
• Build agentic workflows and MCP-based integrations connecting AI applications to enterprise data/tools.
• Implement structured outputs, workflow state management, human-approval steps, and error recovery.
• Build authentication, authorization, RBAC, and audit logging.
• Implement AI evaluation, guardrails, tracing, and monitoring (quality/safety/performance/cost).
• Partner with domain experts and PMs to translate requirements into scalable solutions.
• Design reusable, configuration-driven components for cross-team use.
• Own production-quality code, tests, and documentation.
• Mentor other engineers; guide technical direction across teams.

Skills

React

TypeScript

Python

API development

Automated testing

CI/CD

AI-enabled apps

Agentic workflows

MCP

Auth RBAC security

Secure coding

Education

Bachelor's in CS/Software Engineering

Bachelor's + Master's in STEM

Tools

Databricks

Unity Catalog

Data Lake

GitLab CI/CD

Policy-as-code

Infrastructure-as-code

Job description

Self-directed senior engineer to architect and build secure enterprise applications and AI-enabled/agentic workflows, with strong full-stack skills and hands-on experience integrating AI agents via Model Context Protocol (MCP).

Work Mode :-Hybrid (3 days/ week from office)

Notice Period :-Immediate Joiner to 15 days.

Key Responsibilities

• Architect and develop secure enterprise applications (React, TypeScript, Python, API services)
• Build agentic workflows and MCP-based integrations connecting AI applications to enterprise data/tools
• Implement structured outputs, workflow state management, human-approval steps, and error recovery
• Build authentication, authorization, RBAC, and audit logging
• Implement AI evaluation, guardrails, tracing, and monitoring (quality/safety/performance/cost)
• Partner with domain experts and PMs to translate requirements into scalable solutions
• Design reusable, configuration-driven components for cross-team use
• Own production-quality code, tests, and documentation
• Mentor other engineers; guide technical direction across teams

Must-Have Qualifications

• Bachelor's in CS/Software Engineering/related STEM (or Bachelor's + Master's/higher in STEM)
• 5+ years software development experience (or equivalent demonstrated skill)
• Strong React, API development, application architecture, automated testing, CI/CD
• Experience building AI-assisted apps, agentic workflows, or tool-calling solutions
• Experience with MCP, structured outputs, context management, or comparable frameworks
• Experience with auth/authz, RBAC, and secure coding practices

Nice-to-Have Qualifications

• Databricks, Unity Catalog, Data Lake, or comparable
• GitLab CI/CD or comparable
• Policy-as-code, infrastructure-as-code, configuration-driven platforms
• Experience building data marketplaces, governance platforms, or internal developer platforms
• Familiarity with privacy/security/regulatory/AI governance controls
• Experience in regulated or risk-sensitive environments