Lead AI Software Engineer

About this role:
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.
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
Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Strong proficiency in Python with experience building services using frameworks such as Fast MCP, FastAPI & Flask.
Experience developing and integrating with REST APIs, asynchronous services, and event-driven architectures.
Experience integrating with AI, LLM-based systems, agent platforms, or AI APIs.
Experience with React and TypeScript for building frontend applications.
Experience with authentication, authorization, and access control patterns, including SSO, OAuth 2.0, API keys, token-based access, RBAC, and scopes.
Experience building or integrating with MCP servers & understanding of MCP protocol, including tool registration, schemas, message flows, clients, servers, and lifecycle patterns.
Experience developing agent-driven workflows using frameworks such as LangChain, Google ADK, or similar orchestration frameworks.
Experience frontend fundamentals, including HTML, CSS, JavaScript, browser rendering, DOM APIs, and performance tuning.
Experience with automated testing with Playwright, performance testing, code reviews, and CI/CD practices.
Experience building secure, scalable, maintainable applications aligned with enterprise platform standards.
Desired