AI Engineer – GenAI Tools, MCP, and Agent Development

We are seeking a talented AI Engineer with hands-on experience in generative AI tools, Model Context Protocol (MCP), and intelligent agent development. The role involves designing, building, and deploying AI solutions with advanced context management and agent orchestration capabilities. You will collaborate across teams to translate AI research into scalable production systems that solve complex business problems. Key Responsibilities • Collaborate with Client Architect, product managers, and engineers to identify, prioritize, and shape AI use cases, translating them into solution architectures and roadmaps. • Define and evolve enterprise architectures and standards for AI-powered agents, MCP-based services, and GenAI workflows, ensuring security, compliance, and scalability. • Design reusable reference patterns for MCP Servers, Agent, agent orchestration, tool integration, RAG, and multi-agent workflows that teams can adopt consistently. • Guide the design of AI/ML pipelines for context-aware model deployment, evaluation, and monitoring in partnership with ML and platform engineers. • Architect and oversee the integration of intelligent agents with enterprise systems (APIs, data platforms, identity, observability) for secure automation and advanced reasoning. • Define and enforce non-functional requirements for AI solutions, including latency, reliability, cost, safety guardrails, and explainability. • Prototype and evaluate emerging GenAI tools, models, APIs, and MCP-based capabilities, producing recommendations and reference implementations. • Establish and maintain governance guardrails for model and agent usage, including data access patterns, safety policies, observability, and evaluation standards. • Review production AI deployments for architectural quality, robustness, and operational readiness, including monitoring, testing, rollback, and incident handling patterns. • Document architectural decisions, integration blueprints, and best practices in clear, reusable formats for delivery teams. • Provide technical leadership and enablement through design reviews, guidelines, templates, and knowledge sharing to drive consistent, high-quality AI agent solutions. Required Qualifications • Bachelor’s or Master’s degree in Computer Science, AI, or related field. • 3+ years of software development experience with AI/ML systems. • Proficiency with generative AI frameworks (e.g., OpenAI, LangChain, LangGraph, Semantic Kernel, CrewAI). • Experience with Model Context Protocol (MCP) Server development or similar context-aware architectures. • Strong programming skills in Python, TypeScript, or equivalent languages. • Solid understanding of prompt engineering, retrieval augmentation (RAG), and memory management in AI systems. • Familiarity with cloud platforms (AWS, Azure, GCP) and container technologies (Docker, Kubernetes). • Strong problem-solving skills and the ability to balance research with production requirements. Preferred Qualifications • Experience with multi-agent systems, orchestration, or knowledge graphs. • Familiarity with cloud platforms (AWS, Azure, GCP) and container technologies (Docker, Kubernetes). • Contributions to AI or agent development open-source projects. • Strong problem-solving skills and the ability to balance research with production requirements.