Lead AI Engineer

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.

What you'll do: Lead AI Engineer in the Platforms and Products will…

We are seeking a highly motivated Applied AI Engineer with a strong foundation in Machine Learning and a deep interest in Large Language Models (LLMs) and Generative AI . This role focuses on building, optimizing, and evaluating production-grade LLM systems , including Retrieval-Augmented Generation (RAG) , fine-tuning workflows, and scalable inference pipelines.

Design and implement LLM-powered applications using state-of-the-art transformer models.

Build and optimize RAG pipelines using embeddings, chunking strategies, and vector search.

Experiment with prompt engineering , structured outputs (JSON schemas/function calling), and tool-augmented LLMs (agents/workflows).

Fine-tune models using techniques such as LoRA , PEFT , and instruction tuning .

Develop and evaluate embedding models for similarity search and semantic retrieval.

Conduct LLM evaluation using automated and human-in-the-loop techniques (offline + online).

Optimize inference workflows for latency , GPU utilization , and cost efficiency (quantization, batching, caching).

Build and maintain REST API Services (FastAPI etc.) to deploy LLM/RAG endpoints, integrate with product systems, and support scalable inference.

Contribute to integration of AI systems into production software environments (CI/CD, monitoring, reliability).

Research and prototype cutting-edge approaches in Generative AI and share learnings with the team.

What you’ll bring:

A master's or bachelor's degree in Computer Science or related field from a top university

4+ years' hands-on experience in Machine Learning (ML) with production LLM systems

Good fundamentals of machine learning, deep learning and fine tuning models (LLM) including: Understanding of transformer architectures

Prompt engineering expertise

Embeddings and vector search

Experienced in backend API design with FastAPI, async patterns, rate limiting

Experience with vector DB including: Pinecone, Weaviate, or Chroma

Embedding storage and similarity search

Hybrid search implementations

Strong programming expertise in Python is must including: Async programming (asyncio, async/await)

Type hints and Pydantic

SOLID principles and design patterns

Experience in ML Ops to measure and track model performance including: MLFlow for model tracking

Langfuse for LLM observability (strongly preferred)

Model versioning and A/B testing

Experience in working with NLP & computer vision

Fluency in English

Client-first mentality

Intense work ethic

Collaborative spirit and problem-solving approach

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.

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

What you'll do: Lead AI Engineer in the Platforms and Products will…

We are seeking a highly motivated Applied AI Engineer with a strong foundation in Machine Learning and a deep interest in Large Language Models (LLMs) and Generative AI . This role focuses on building, optimizing, and evaluating production-grade LLM systems , including Retrieval-Augmented Generation (RAG) , fine-tuning workflows, and scalable inference pipelines.

Design and implement LLM-powered applications using state-of-the-art transformer models.

Build and optimize RAG pipelines using embeddings, chunking strategies, and vector search.

Experiment with prompt engineering , structured outputs (JSON schemas/function calling), and tool-augmented LLMs (agents/workflows).

Fine-tune models using techniques such as LoRA , PEFT , and instruction tuning .

Develop and evaluate embedding models for similarity search and semantic retrieval.

Conduct LLM evaluation using automated and human-in-the-loop techniques (offline + online).

Optimize inference workflows for latency , GPU utilization , and cost efficiency (quantization, batching, caching).

Build and maintain REST API Services (FastAPI etc.) to deploy LLM/RAG endpoints, integrate with product systems, and support scalable inference.

Contribute to integration of AI systems into production software environments (CI/CD, monitoring, reliability).

Research and prototype cutting-edge approaches in Generative AI and share learnings with the team.

What you’ll bring:

A master's or bachelor's degree in Computer Science or related field from a top university

4+ years' hands-on experience in Machine Learning (ML) with production LLM systems

Good fundamentals of machine learning, deep learning and fine tuning models (LLM) including: Understanding of transformer architectures

Prompt engineering expertise

Embeddings and vector search

Experienced in backend API design with FastAPI, async patterns, rate limiting

Experience with vector DB including: Pinecone, Weaviate, or Chroma

Embedding storage and similarity search

Hybrid search implementations

Strong programming expertise in Python is must including: Async programming (asyncio, async/await)

Type hints and Pydantic

SOLID principles and design patterns

Experience in ML Ops to measure and track model performance including: MLFlow for model tracking

Langfuse for LLM observability (strongly preferred)

Model versioning and A/B testing

Experience in working with NLP & computer vision

Fluency in English

Client-first mentality

Intense work ethic

Collaborative spirit and problem-solving approach

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.

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