ZS is a management consulting and technology firm that partners with companies to improve life and how we live it. We transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Founded in 1983, ZS has more than 15,000 employees in over 40 offices worldwide.
AI Engineering Managers in ZAIDYN Content will own the end-to-end architecture, design, and delivery of large-scale AI and platform systems supporting the Agentic Foundation workstream. In this role, you will lead teams building multi-tier, distributed applications across API, service, data, and AI layers while staying deeply engaged in system design and technical reviews. You will drive engineering excellence across performance, scalability, reliability, maintainability, and production readiness. You will serve as a technical authority for complex architectural and production challenges, making pragmatic trade-offs that balance near-term delivery with long-term platform evolution. You will partner closely with Product, AI/ML, DevOps, Data Engineering, and Consulting teams to integrate GenAI capabilities into robust enterprise platforms. You will also mentor engineers and help build a culture of technical depth, ownership, accountability, and reuse across AI components and platform capabilities.
- Lead architecture and system design for large-scale, distributed, multi-tier systems spanning frontend, APIs, services, data, and AI layers.
- Define engineering standards, design patterns, service boundaries, API approaches, data models, and platform architecture decisions.
- Architect and build production-grade GenAI-enabled systems using LLMs, prompt pipelines, model APIs, and agentic or workflow-based approaches.
- Guide engineers through design reviews, code reviews, technical debt resolution, and scalable implementation practices.
- Own delivery across high-impact, parallel workstreams by driving planning, prioritization, risk identification, and execution discipline.
- Ensure systems are observable, reliable, debuggable, production-ready, and aligned with cloud-native and CI/CD practices.
- Partner with Product, AI/ML, Data Engineering, DevOps, and Consulting teams to translate complex business needs into scalable technical solutions.
- Deep software engineering experience with strong foundations in core computer science, data structures, algorithms, and system design.
- Engineering management or technical leadership experience with proven ability to lead teams while remaining technically credible and hands-on.
- Experience building and scaling large-scale, distributed, multi-tier applications across backend, services, data, and AI layers.
- Strong backend engineering skills, with Python preferred, and familiarity with frameworks such as FastAPI, Flask, or similar technologies.
- Strong understanding of distributed systems, microservices, API design, service-oriented architecture, data modeling, and storage systems.
- Hands-on experience building production-grade GenAI or LLM systems, including prompt pipelines, model integrations, and agentic or workflow-based AI systems.
- Ability to balance short-term delivery with long-term platform evolution, reuse, standardization, and maintainability.
- Fluency in English, a client-first mentality, collaborative spirit, strong problem-solving approach, and ability to communicate technical trade-offs clearly to stakeholders.
- Ability to build engineering culture through coaching, hiring, structured development, and clear expectations for technical excellence.
- Experience supporting complex platform or AI solution discussions with internal stakeholders and/or clients is preferred.
- 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