We are seeking an Senior 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.
In this role you will
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.
Key responsibilities
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
Required qualifications
4+ years engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
3+ years strong proficiency in Python with experience building services using frameworks such as Fast MCP , FastAPI & Flask
3+ years of experience developing and integrating with REST APIs ,…