THE ROLE

This is ZAIDYN's key AI Engineering leadership position. You will expand and strengthen the team responsible for our agentic platform. This is a hands-on, deeply technical role that requires someone who can hold an architecture conversation with Architects and engineers, then pivot to delivering a pitch of our architecture to a CIO.

You will report directly to the Head of Engineering/CTO, partner with the Sr. Director of Product Management and work alongside our application product and platform teams to define what it means for ZAIDYN to ship trusted, production-grade AI. The word 'trusted' is critical here, and not just another marketing adjective. Our clients are enterprises making real decisions with real consequences and looking for us to enable Agentic operations. Thus, the AI applications we build must be a) Accurate, comprehensive and relevant and b) auditable, governed, and compliant.

RESPONSIBILITIES

Build and lead the ZAIDYN AI Engineering function

• Lead the dedicated AI Engineering team by hiring, structuring, and setting the technical culture.

• Define the team model that scales with engineering pods organized around platform capabilities and rationalized across geographies.

• Own the full talent lifecycle from sourcing, hiring, onboarding, performance, and retention.

• Partner with Product and QA to establish AI-native development practices including eval frameworks, LLM Ops discipline, and agent observability standards.

Own the Agentic Platform Architecture

• Drive architecture decisions for ZAIDYN's agentic platform from orchestration and retrieval to validation-gate agent patterns, cost management and multi-agent coordination.

• Own the technical integration between AWS Bedrock AgentCore and our orchestration and observability stack, and ZAIDYN Applications

• Set standards for when to use RAG vs. fine-tuning vs. long-context approaches; enforce those standards through code review and design review.

• Ensure the platform meets enterprise-grade requirements: latency, cost-per-inference, audit trails, hallucination management, and PII handling.

• Lead the push from agentic alpha to beta to GA holding the team accountable to shipping and adoption timelines, not research timelines.

Define and Enforce Engineering Quality

• Establish evaluation frameworks for every AI feature before it goes to clients.

• Distinguish clearly between demo-quality and production-quality AI and hold that line. Lead the organization on building high quality, accurate, reliable and consistent AI applications.

• Create PR review standards for LLM-powered features that your team and future teams inherit.

Represent AI Engineering Externally

• Engage with technical leadership on clients on technical credibility; able to explain architectural decisions in language executives and enterprise architects both understand.

• Contribute to ZAIDYN's thought leadership on trusted agentic AI for enterprise contexts.

• Stay ahead of the field: evaluate new frameworks, models, and infrastructure options and make build vs. buy vs. integrate decisions with speed and rigor.

WHAT WE'RE LOOKING FOR

• 15+ years in software engineering with 5+ years in AI/ML/Data engineering in a production context, and at least 5 years leading 3 - 5 scrum teams across multiple locations (US, Eastern Europe, India etc.)

• Direct experience shipping multi-agent or RAG-based systems into enterprise B2B environments.

• Hands-on fluency with technologies like LangGraph and LangChain, or equivalent agent orchestration frameworks. You should be able to read and critique a graph implementation.

• Experience managing engineering teams of 15+ individuals, including hiring and growing senior engineers.

• Strong opinions on eval frameworks, LLMOps, and what 'production-ready' actually means for AI systems.

• AWS experience, ideally with Bedrock, SageMaker, or adjacent enterprise AI services.

• Clear written and verbal communication; able to write a design doc and a stakeholder brief with equal facility.

• Have built multi-tenant, enterprise SaaS products, especially business applications or platforms that power multiple applications.

Highly Preferred

• Experience building Analytical applications such as those used for planning, optimization, scenario analysis, dashboards/Business Intelligence and predictions.

• Experience building AI functions from scratch or early stages.

• Familiarity with LangSmith or similar observability/tracing tools for agent pipelines.

• Exposure to regulated or high-trust enterprise environments (healthcare, financial services, pharma) where AI governance and auditability are table stakes.

• Understanding of data architecture patterns (data mesh, vector stores, hybrid retrieval) that underpin enterprise RAG systems.

• B.S in Computer Science, Math or any branch of Engineering. Graduate degree in these fields is preferred.

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

Perks & Benefits:

At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well-being, financial future, time away, and professional development. With robust skills-building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you'll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community. For details on total rewards in United States, visit ZS US office locations | Where we work | ZS.

Hybrid working model:

We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.

Travel:

Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.