Artificial Intelligence Engineer - Manager

Role & responsibilities

AI Engineering Manager (Full Stack)

Team leadership, architecture ownership, and delivery for GenAI agent products

Experience: 8+ years (incl. 2+ years leading teams)

About the Role

We are hiring an AI Engineering Manager to lead a team of full-stack AI engineers delivering GenAI-powered agents and applications built on React and Python (FastAPI). You will own technical architecture and delivery, grow and manage the team, and partner with product and business stakeholders to set direction for automation across HR, Payroll, SAP, and Client Delivery. This is a hands-on leadership role you will still review designs and guide complex technical decisions, but your primary leverage is through your team.

Key Responsibilities

• Lead, mentor, and grow a team of full-stack AI engineers; own hiring, onboarding, performance management, and career development
• Own the technical architecture for agent platforms spanning React front-ends, Python/FastAPI services, and LLM orchestration layers
• Drive delivery planning, prioritization, estimation, and execution across multiple workstreams
• Set and uphold engineering standards for code quality, testing, security, observability, and deployment
• Partner with Product Managers, SMEs, and business leaders to shape the roadmap and turn business processes into an agentic automation strategy
• Make build-vs-buy and framework decisions (LangChain, LangGraph, CrewAI, etc.) and guide RAG, multi-agent, and integration patterns
• Ensure scalable, secure, and reliable systems integrating with enterprise platforms (Workday, SAP, Salesforce)
• Remove blockers, manage technical risk and debt, and report progress and outcomes to leadership
• Stay hands-on enough to review architecture and code and to guide the hardest technical decisions

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field
• 8+ years in software/AI engineering, including 2+ years leading or managing engineering teams
• Proven delivery of production full-stack systems (React + Python) and AI/ML or GenAI solutions
• Strong architectural judgment across front-end, back-end, and LLM/agent orchestration
• Deep familiarity with agentic frameworks (LangChain, LangGraph, CrewAI, ReAct) and LLM orchestration
• Experience with enterprise integrations, distributed systems, cloud (Azure / AWS / GCP), containers/Kubernetes, and security best practices
• A track record of hiring, mentoring, and growing high-performing engineering teams
• Excellent stakeholder management and communication skills

Nice to Have

• Experience scaling GenAI / agent platforms in production
• Background in enterprise-scale business process or workflow automation
• Open-source leadership or active community contributions
• Experience defining MLOps / LLMOps and observability practices