Engineering Lead AI Engineering

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.

What you ll do:

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.

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

What you ll bring:

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

How you ll grow:

- Cross-functional skills development & custom learning pathways
- Milestone training programs aligned to career progression opportunities
- Internal mobility paths that empower growth via s-curves, individual contribution and role expansions

📌 Manager - AI Engineering (Bengaluru)
🏢 ZS
📍 Bengaluru