Job Opportunities API

We are seeking a Lead AI Engineer with strong software engineering foundations and hands-on experience in Generative and Agentic AI. In this role, you will architect, design and build production-grade AI systems powered by large language models and intelligent agents. 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.