Lead AI Engineer

You will design scalable AI workflows, integrate autonomous agents into real-world applications, and help translate cutting-edge AI capabilities into reliable business solutions. • Architect and Design production-ready applications leveraging Generative AI and agentic AI frameworks. • Build, Deploy and Monitor intelligent workflows using LLMs, multi-agent coordination, and orchestration pipelines. • Integrate new AI applications with traditional pre-existing applications. • Implement prompt engineering strategies, retrieval-augmented generation (RAG), and contextual memory systems. • Implement various AI coding techniques (context-driven, spec-driven development etc.). • Architect and implement AI agents capable of reasoning, planning, and multi-step task execution. • Implement and utilize Model Context Protocol (MCP) patterns to enable structured communication between agents, tools, and systems. • Provide mentoring and technical guidance to developers and other AI Engineers. • Develop evaluation pipelines to measure accuracy, safety, and performance of AI systems. • Optimize latency, cost efficiency, and scalability of AI-powered workflows. • Collaborate with product managers, data teams, and software engineers to deliver AI features. • Ensure reliability through testing, logging, monitoring, and observability of AI behavior. • Own architectural decisions, coding standards, and best practices. • Act as an AI trailblazer for development teams by promoting best practices, reusable patterns, and adopting AI-driven engineering approaches. • Apply AI governance principles to ensure responsible model usage, auditability, and transparency in AI workflows. • Support implementation of governance controls related to data handling, model behavior monitoring, and risk mitigation. • Research emerging AI tools and frameworks to continuously improve system capabilities. • Document AI workflows and maintain reproducible engineering processes. • 6-8 years of professional software development experience (Dotnet/React/Full-stack) with mentorship/team leadership experience. • Minimum 2 years of hands-on experience building applications using Generative AI or agentic AI systems. • Strong proficiency in Python and backend engineering principles. • Experience designing RESTful APIs and scalable service architectures. • Practical experience with LLM APIs, embeddings, vector search, or RAG pipelines. • Working knowledge of AI governance principles, responsible AI practices, or compliance considerations. • Familiarity with agent frameworks and autonomous decision workflows. • Understanding of data structures, system design, and performance optimization. • Strong analytical thinking and problem-solving skills. ________________________________________ Preferred Qualifications • Experience deploying AI applications in cloud environments (preferably AWS). • Familiarity with vector databases and knowledge retrieval architectures. • Experience working with Git, CI/CD pipelines, and production deployments. • Exposure to containerization and orchestration tools (Docker, Kubernetes). • Experience implementing evaluation or monitoring pipelines for AI agents. • Knowledge of AI safety, guardrails, and responsible AI practices. • Knowledge of distributed systems or event-driven architecture.