Job Description

Overview:

As an Engineering Manager - Agentic & AI Systems at JAGGAER, you will lead a high-performing engineering team responsible for building, scaling, and operating production-grade, AI-native platforms for enterprise procurement. This is a hands-on leadership role where you will actively contribute to design and development while managing people, execution, and delivery.

You will be expected to drive innovation through proof-of-concepts (POCs), guide the team from experimentation to production, and confidently demo work-in-progress features to stakeholders. Success in this role requires strong technical depth, excellent people management skills, and the ability to balance strategic thinking with execution.
Principal Responsibilities:

Team Leadership & People Management

Lead, mentor, and manage a cross-functional engineering team (backend, AI/ML, and frontend engineers). Foster a high-performance culture by setting clear goals, conducting regular 1:1s, and supporting career development. Motivate the team to deliver high-quality outcomes while maintaining strong engineering standards. Conduct and lead daily standups, weekly, bi-weekly, and monthly meetings to track progress, share updates, and address risks.

Hands-On Technical Leadership

Remain hands-on with architecture, design, and critical code paths, especially for AI and agentic systems. Lead and actively participate in POC efforts, evaluating new ideas, tools, frameworks, and AI capabilities. Drive POCs to successful production-ready solutions with clear success metrics. Review architecture and code to ensure high standards of quality, security, scalability, and reliability. Be prepared to demo work-in-progress features, technical solutions, and POCs to internal and external stakeholders.

Delivery & Execution

Own end-to-end delivery of AI initiatives, ensuring timelines, scope, and quality expectations are met. Identify technical and delivery risks early, communicate them clearly, and drive mitigation plans. Ensure predictable and on-time delivery through strong planning, prioritization, and execution. Provide regular status updates, progress reports, and technical insights to leadership.

AI & Platform Engineering

Lead the design and delivery of LLM-powered, agentic AI systems at enterprise scale. Identify, evaluate, and implement cutting-edge techniques in Generative AI, agentic systems, and LLM architectures. Establish best practices for LLM evaluation, observability, reliability, and performance in collaboration with QA and platform teams. Partner closely with DevOps to ensure scalable, reliable, and cost-efficient cloud infrastructure.

Cross-Functional Collaboration

Collaborate closely with Product Management, Business, QA, Platform, and DevOps teams to define requirements and deliver impactful solutions. Act as a bridge between technical and non-technical stakeholders, ensuring alignment and transparency. Support roadmap planning by providing technical input, feasibility assessments, and delivery estimates.

Position Requirements:
10+ years of hands-on software engineering experience. 3+ years in an engineering leadership or people management role. Proven experience delivering LLM-powered and agentic AI systems into production at enterprise scale. Experience leading POCs and transitioning experimental solutions into production systems.

Technical Skills:

Strong expertise in Generative AI, agentic systems, and LLM workflows. Deep proficiency in Python for backend services, AI orchestration, and evaluation pipelines. Hands-on experience with agentic and LLM frameworks such as LangChain, LangGraph, , Open Agent Platform (OAP), and OpenAI Agentic SDK. Experience with LLM evaluation and quality frameworks such as RAGAS and DeepEval. Strong experience designing and scaling RAG and CAG architectures using vector databases like Pinecone. Extensive experience with Google Cloud Platform (GCP) including GKE, Cloud Run, Pub/Sub, Cloud Functions, IAM, and networking. Experience with Docker and Kubernetes. Experience with observability and monitoring tools (Cloud Monitoring, Cloud Logging, Prometheus, Grafana, ELK, SigNoz). Strong understanding of API and platform security using OAuth2, JWT, and JWE. Experience building AI-powered user interfaces using ReactJS. AWS experience is a plus.

Soft Skills & Competencies:

Strong people leadership and coaching skills. Excellent communication and presentation skills, including the ability to demo technical solutions to diverse audiences. Strong analytical thinking and decision-making ability. Comfortable operating in ambiguity and fast-paced environments. Proven ability to balance hands-on technical work with people and delivery management. Excellent cross-team collaboration and stakeholder management skills.

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