Senior Director, AI Engineering

Posted 3 Hours Ago
Be an Early Applicant
5 Locations
Hybrid
Senior level
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
Where passion changes lives
The Role
Lead ZAIDYN's AI Engineering function to design, build, and ship an enterprise-grade agentic AI platform. Own architecture, integrations (AWS Bedrock/AgentCore), LLMOps/eval frameworks, observability, governance, and team hiring/operations. Ensure production readiness, cost/latency controls, auditability, and cross-functional delivery with product and QA while representing the platform externally.
Summary Generated by Built In
ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving 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. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS.
ABOUT ZAIDYN
ZAIDYN is ZS's product business that is already making 9 figure ARR that is growing rapidly at 35%. Our products are used by 8 out of 10 large pharma and over 150 clients worldwide across 100 countries . We are in the middle of building our next generation Agentic AI platform that forms the underpinning of all our AI applications . These Agentic Applications will span Commercial Operations, Personalization/Marketing, Clinical operations, Medical Affairs and Patient Engagement.
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. O ur 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 l ead 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 ; e nforce 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 /D ata 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 framework s. 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.
Considering applying?
At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systems-the ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are integral to your success here. We are committed to building a team that reflects a broad variety of backgrounds, perspectives, and experiences. Learn more about our inclusion and belonging efforts and the networks ZS supports to assist our ZSers in cultivating community spaces and obtaining the resources they need to thrive.
If you're eager to grow, contribute, and bring your unique self to our work, we encourage you to apply.
ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law.
Work Authorization:
This position is not eligible for visa sponsorship. Candidates must have authorization to work in the United States that does not now or in the future require employer sponsorship.
To complete your application:
An on-line application, including a full set of transcripts (official or unofficial), is required to be considered.
NO AGENCY CALLS, PLEASE.
Find Out More At:
www.zs.com

Skills Required

  • 15+ years in software engineering with 5+ years in AI/ML/Data engineering in production
  • 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 LangGraph and LangChain or equivalent agent orchestration frameworks
  • Experience managing engineering teams of 15+ individuals, including hiring and growing senior engineers
  • Strong experience with evaluation frameworks, LLMOps, and production-ready AI standards
  • AWS experience, ideally with Bedrock, SageMaker, or adjacent enterprise AI services
  • Clear written and verbal communication; able to write design docs and stakeholder briefs
  • Experience building multi-tenant enterprise SaaS products or platforms
  • Authorization to work in the United States without employer sponsorship
  • B.S. in Computer Science, Math or Engineering (Graduate degree preferred)
  • Experience building analytical applications (planning, optimization, BI, predictions)
  • Experience building AI functions from scratch or in 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)
  • Understanding of data architecture patterns (data mesh, vector stores, hybrid retrieval)

What the Team is Saying

Ash Easwar
Suzanne Boyan
Kristina Sambucci
Callum Brazier
Michelle Lu
Mike Vula
Mina Labib
Judith Kulich
Anna Simon
Rachana Late
Bazgha Qutab
Ayush Kataria
Carolina Blanco
Kumar Ritwik
Emily Reynolds
Mahmood Majeed
Mahmood Majeed
Bazgha Qutab
Mahmood Majeed
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The Company
HQ: Evanston, IL
15,000 Employees
Year Founded: 1983

What We Do

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.

Why Work With Us

ZS is home to passionate people who embrace innovative thinking, collaboration and a client-first mindset. Welcome to a company where new ideas are celebrated, curiosity is welcomed, learning opportunities are abundant and colleagues become lifelong connections.

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Hybrid Workspace

Employees engage in a combination of remote and on-site work.

The Flexible & Connected model is our ZS standard. ZSers decide where it makes the most sense for them to work each day given client or teamwork.

Typical time on-site: 3 days a week
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