AI Engineer

The AI Engineer, People Technology is responsible for designing, developing, and deploying AI-powered solutions that transform work across the People Organization. This role combines software engineering, AI development, and HR domain expertise to build intelligent applications, automations, and agents that improve employee experiences, increase operational efficiency, and accelerate workforce transformation. The ideal candidate is a hands-on builder with demonstrated experience using AI Assisted Software Development Platforms to develop enterprise AI solutions. You must have successfully designed and deployed AI agents that collaborate across multiple platforms, systems, and business functions while operating within enterprise governance, security, and compliance standards. This role requires deep knowledge of HR technologies, including Workday, ServiceNow, and the Microsoft Copilot ecosystem, along with a passion for applying AI to solve complex business challenges. Key Responsibilities AI Product & Solution Development • Experience with the end-to-end product lifecycle turning a vision into a roadmap while driving adoption and value delivery • Design, develop, test, and deploy AI-powered products, applications, and intelligent workflow solutions • Utilize AI Assisted Development Tools to accelerate software development, solution design, and deployment activities • Support subject matter experts in translating business needs into designs and prototypes • Develop reusable frameworks, services, and components (such as AI Skills) that enable scalable AI adoption across the People Organization AI Agent Engineering • Design and build AI agents capable of making business-context-aware decisions, taking actions across enterprise systems and workflows, and operating autonomously within defined guardrails. • Develop multi-agent systems that coordinate work across functions and platforms. • Implement agent orchestration, memory, tool integration, and workflow management capabilities. Cross-Platform Collaboration & Integration • Build AI solutions that integrate and collaborate across multiple enterprise platforms. • Develop integrations utilizing APIs, event-driven architectures, and enterprise services. • Enable seamless interactions between agents, data sources, and systems to automate end-to-end business processes. • Create solutions that leverage enterprise knowledge, workflows, and operational data securely and responsibly. Technology Innovation • Partner with leaders, process owners, and technology teams to identify AI transformation opportunities. • Apply HR domain knowledge to improve recruiting, onboarding, learning, employee services, talent management, workforce planning, and people analytics processes. • Drive innovation by rapidly prototyping, testing, and scaling AI solutions that create measurable business value. Governance & Responsible AI • Ensure solutions comply with enterprise standards for security, privacy, compliance, and responsible AI. • Implement monitoring, observability, testing, and evaluation frameworks for AI systems. • Support the development of AI governance standards, best practices, and development guidelines. Required Qualifications Minimum Qualifications & Experience • Bachelor’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related technical discipline. • Hands-on experience delivering production software applications using Python-based backend technologies and modern software engineering practices. • Experience designing, developing, and deploying enterprise-grade Generative AI or Large Language Model (LLM) solutions. • Experience owning the end-to-end software development lifecycle, including solution architecture, development, testing, deployment, and production support. • Experience building cloud-native applications in distributed and microservices-based environments. • Experience developing AI-powered applications focused on workflow automation, conversational search, document intelligence, or knowledge retrieval. Must-Have Technical Skills • Advanced Python development experience, including building scalable backend services and REST APIs using FastAPI or equivalent frameworks. • Hands-on experience with Large Language Models (LLMs), prompt engineering, model integration, and AI application development. • Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions, vector databases, embeddings, semantic search, and knowledge retrieval systems. • Experience developing production-grade AI agent systems using both LangChain and LangGraph. • Experience implementing multi-agent architectures, agent orchestration frameworks, tool-calling capabilities, reasoning workflows, and human-in-the-loop AI systems. • Experience designing and implementing Model Context Protocol (MCP) solutions, including MCP servers, MCP clients/hosts, tool registration, runtime tool discovery, and agent integration. • Experience integrating AI agents with enterprise APIs, databases, business applications, and external service ecosystems. • Experience deploying self-hosted open-source LLMs in Kubernetes environments using technologies such as KServe, vLLM, or equivalent model-serving platforms. • Experience deploying AI solutions using Kubernetes, Docker, Helm, GitOps, Argo CD, and CI/CD pipelines in production environments. • Experience with LLMOps or MLOps practices, including model serving, inference optimization, AI platform operations, and production AI lifecycle management. • Experience with distributed systems, asynchronous processing, workflow orchestration platforms, event-driven architectures, and message-queuing technologies. Preferred Qualifications • Experience deploying and operating open-source foundation models in enterprise or production environments. • Experience with KServe, vLLM, Hugging Face, PyTorch, Temporal, RabbitMQ, Neo4j, or vector database technologies. •…