ZS - Engineering Manager - Artificial Intelligence

Description :

ZS is seeking an experienced Engineering Manager AI Engineering to lead the design, delivery, and evolution of AI-powered platforms and services. This role combines technical leadership, people management, and execution ownership, and is critical to building scalable, reliable, and high-impact

GenAI systems across products and client solutions.

This is a hands-on leadership role for someone who brings strong engineering judgment, deep GenAI experience, and the ability to grow high-performing teams while owning complex delivery outcomes.

Role Overview :

As an Engineering Manager AI Engineering, you will :

- Own end-to-end technical and delivery responsibility for multiple AI platforms and services

- Lead and mentor senior engineers, technical leads, and service owners

- Drive architecture, engineering standards, and execution discipline

- Act as the primary technical and delivery escalation point

- Partner closely with Product, AI/ML, DevOps, Data Engineering, and Consulting teams

You will balance delivery commitments with long-term platform health, scalability, and reuse.

Key Responsibilities :

Technical Leadership & Architecture :

- Own system-level architecture and technical decision-making across AI platforms and services

- Guide design and implementation of backend services, APIs, and AI integrations

- Ensure systems are scalable, secure, and production-ready

- Provide technical direction on GenAI workflows, agentic systems, and service orchestration

Engineering Management & Team Leadership :

- Manage and mentor senior engineers, technical leads, and service owners

- Set clear expectations around ownership, quality, and delivery

- Support team growth through coaching, feedback, and development planning

- Build a culture of strong engineering fundamentals, accountability, and collaboration

Delivery Ownership & Execution :

-

Own delivery outcomes across multiple parallel workstreams

- Partner with product and delivery teams to plan, prioritize, and sequence work

- Identify risks early and make pragmatic trade-offs

- Act as escalation point for technical and delivery challenges

AI Platform & Service Enablement :

- Oversee development of AI-powered backend services using Python (FastAPI / Flask)

- Enable GenAI use cases by integrating LLMs, prompt pipelines, agentic workflows, and enterprise data systems

- Drive standardization and reuse across AI components where appropriate

- Ensure clear service ownership and operational readiness

Engineering Quality & Governance :

- Define and enforce engineering standards, patterns, and best practices

- Review designs and code at a system level to ensure quality and maintainability

- Identify technical debt and guide remediation plans

- Partner with DevOps to ensure observability, reliability, and operational clarity

Cross-Functional Collaboration :

- Work closely with Product, AI/ML, DevOps, Data Engineering, and Consulting teams

- Translate business and client needs into sound technical approaches

- Communicate technical trade-offs clearly to non-technical stakeholders

- Support client-facing discussions when required for complex AI systems

Required Qualifications :

- 10+ years of software engineering experience, including 3+ years in a technical leadership or engineering management role

- Strong backend engineering experience in Python (FastAPI, Flask, or similar frameworks)

- Hands-on experience building, integrating, and scaling GenAI / LLM-based systems, including prompt pipelines, model APIs, and agentic or workflow-based AI solutions

- Experience building and operating AI-enabled or data-intensive systems in production

- Proven ability to lead engineers while remaining technically credible

- Experience owning architecture and delivery across multiple services

- Comfortable operating in ambiguity and making pragmatic technical and delivery decisions

Nice to Have :

- Experience with cloud platforms (AWS, Azure, or GCP)

- Exposure to consulting or client-facing environments

- Background in platform, shared services, or accelerator-based engineering

What Success Looks Like in This Role :

- Engineering teams operate independently with clear ownership

- GenAI systems are scalable, reliable, and reusable

- Delivery is predictable and high quality

- Technical decisions balance speed with long-term sustainability

- Engineers grow in capability, confidence, and impact