AI Software Engineer

We are seeking an AI Engineer to help design, build, and deliver next-generation AI-enabled applications and agentic systems. This role combines hands-on engineering across frontend applications, Python backend services, MCP infrastructure, agent workflows, and secure enterprise integrations.

As an AI Engineer, you will build user-facing applications and backend services that integrate with Model Context Protocol (MCP) servers, LLM-based applications, RAG-based retrieval systems, and agent orchestration platforms. You will work closely with AI developers, platform engineers, product teams, and other stakeholders to deliver scalable, secure, observable, and production-ready AI solutions.

This engineering role is suited for candidates who can contribute across the full stack while also helping shape reusable patterns for MCP-enabled tools, skills, and agent-driven workflows.

• Design, build, and maintain AI-enabled applications using React, TypeScript, Python, and modern API frameworks.
• Develop  frontend applications aligned with enterprise UI standards and reusable component patterns.
• Build and maintain Python backend services, APIs, MCP services, and integration layers using frameworks such as MCP, FastAPI & Flask.
• Design, implement, and integrate with MCP servers and MCP clients that enable secure context sharing between models, tools, applications, and agent runtimes.
• Develop and support agentic workflows that execute complex, multi-step tasks using frameworks such as LangChain Deep Agents, Google ADK, or similar agent frameworks.
• Build skill-based and modular agents that decompose capabilities into reusable, composable, and versioned skills.
• Build reusable components, services, tool schemas, and integration patterns that can be shared across enterprise AI applications.
• Integrate logging, tracing, and observability frameworks, including Arize & Splunk compatible logging and agent observability tooling.
• Ensure applications and services are ready for deployment on enterprise container platforms such as OpenShift or Kubernetes.
• Collaborate with AI developers, platform engineers, product teams, and architecture partners to deliver robust and scalable AI solutions.
• Deliver end-to-end AI application features using MCP services, and agent orchestration layers.
• Own and contribute to MCP service implementations, including tool schema design, tool registration, API integration, authorization enforcement, and deployment readiness.
• Build and maintain MCP-compatible tools, skills, APIs, and UI components for use across AI applications and agent runtimes.
• Integrate AI-powered user interfaces with backend APIs, MCP servers, RAG systems, and agent workflows.
• Implement RBAC policies governing which users, agents, clients, and applications can invoke specific tools or services.
• Develop agent workflows that support complex user objectives through mcp & skill orchestration.
• Align solutions with enterprise platform standards, including application scaffolding, security, observability, logging, testing, and deployment practices.
• Ensure frontend applications are performant, accessible, maintainable, and aligned with reusable design patterns.
• Ensure backend and AI services are scalable, observable, secure, and ready for deployment on OpenShift or Kubernetes-based environments.
• Write and maintain technical documentation, integration guides, API specifications, and operational runbooks.
• Contribute to engineering best practices, including code reviews, automated testing, CI/CD, monitoring, and production support readines

Job Expectations:

Posting End Date:

29 Oct 2026

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