Senior AI Software Engineer

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 ,  asynchronous services, and event-driven architectures  3+ years of experience integrating with AI, LLM-based systems, agent platforms, or AI APIs  3+ years of experience with React and TypeScript for building frontend applications  3+ years of experience with   authentication, authorization, and access control patterns, including SSO, OAuth 2.0, API keys, token-based access, RBAC, and scopes  3+ years of experience building or integrating with MCP servers &   understanding of MCP protocol, including tool registration, schemas, message flows, clients, servers, and lifecycle patterns  3+ years of experience developing agent-driven workflows using frameworks such as LangChain, Google ADK, or similar orchestration frameworks  3+ years of experience frontend fundamentals, including HTML, CSS, JavaScript, browser rendering, DOM APIs, and performance tuning .   3+ years of experience with automated testing with   Playwright ,  performance testing, code reviews, and CI/CD practices  3+ years of experience building secure, scalable, maintainable applications aligned with enterprise platform standards  Desired qualifications  Experience building MCP servers using FastMCP or similar Python-based MCP frameworks  Experience designing MCP-compatible tools, reusable skills, and modular agent capabilities  Familiarity with tool schema design and structured output validation using tools such as Pydantic, JSON Schema, or Zod  Experience with long-running autonomous agents that support retries, state persistence, error recovery, graceful termination, and multi-step workflow execution. Experience with RAG-based retrieval systems ,  vector search, embeddings, or enterprise knowledge retrieval patterns  Experience with agent observability and tracing tools such as LangSmith, Open Telemetry, Arize, or similar platforms  Exposure to Splunk or enterprise observability frameworks  Experience with Docker, OpenShift, Kubernetes,