AI / GenAI Engineering Lead

Posted Yesterday
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Warsaw, Warszawa, Mazowieckie, POL
Hybrid
Expert/Leader
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
Where passion changes lives
The Role
Lead the design, development, deployment, and operation of production-grade generative and agentic AI solutions. Build multi-agent workflows, RAG systems, enterprise integrations, evaluation frameworks, and secure cloud deployments on AWS. Establish reusable architecture patterns, testing, observability, and governance practices while collaborating with technical teams, stakeholders, and European clients.
Summary Generated by Built In
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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.
Role Description
What You'll Do
As an AI / GenAI Engineering Lead within ZS EDGE Technology in Poland, you will design, build and take to production enterprise-grade generative AI and agentic AI solutions.
This is a senior, hands-on engineering role at the intersection of agentic AI and software engineering. You will develop systems that combine large language models, enterprise data, tools, APIs and business workflows, taking solutions from initial design and proof of concept through production deployment, testing, monitoring and ongoing support.
You will work with engineering, architecture, advisory and account teams across Europe to translate emerging client needs into reliable, secure and scalable AI solutions. Although the initial demand is aligned to a major life-sciences client, the engineering patterns and capabilities developed through this role should be reusable across wider ZS AI delivery.
Your responsibilities will include:
  • Design, build and deploy production-grade GenAI and agentic AI applications
  • Develop multi-agent systems covering orchestration, routing, delegation, tool calling, state management, memory and human-in-the-loop patterns
  • Build agentic workflows using frameworks such as LangGraph, LangChain or equivalent orchestration technologies
  • Develop and deploy AI workloads on AWS using relevant generative AI and cloud-native services
  • Integrate AI agents with enterprise APIs, applications, structured and unstructured data and business workflows
  • Build retrieval-augmented generation and enterprise knowledge-retrieval capabilities
  • Design robust agent workflows with retries, fallback logic, checkpointing, error handling and recovery
  • Build evaluation and automated-testing approaches covering task completion, tool-use accuracy, groundedness, quality and regression
  • Apply sound software-engineering practices, including modular design, code review, version control and automated testing
  • Establish deployment practices using containerisation, CI/CD, infrastructure as code, monitoring and observability
  • Implement security, access, traceability and audit controls appropriate for enterprise and regulated environments
  • Monitor agent behaviour, workflow execution, latency, reliability, quality and operating cost
  • Contribute to high-level and low-level solution design and technical architecture reviews
  • Define reusable agentic architecture patterns, reference implementations and engineering standards
  • Collaborate with technical and non-technical stakeholders to turn ambiguous requirements into deliverable solutions
  • Participate, where required, in short European client engagements

What You'll Bring
  • Significant hands-on experience in software engineering, AI engineering, machine learning engineering or generative AI delivery
  • Strong Python development skills and sound software-engineering fundamentals
  • Demonstrable experience building GenAI or agentic AI applications beyond isolated prototypes
  • Experience designing complex agentic workflows or multi-agent systems
  • Practical understanding of tool and function calling, stateful workflows, agent routing, delegation, memory and context management
  • Experience using agent orchestration frameworks such as LangGraph, LangChain or comparable technologies
  • Experience integrating AI applications with enterprise APIs, databases, systems and external tools
  • Experience building RAG or enterprise knowledge-retrieval solutions
  • Understanding of embeddings, vector search, document processing and grounding
  • Experience defining test cases and evaluating agentic or LLM-based applications
  • Understanding of production-quality engineering, including Docker, CI/CD, automated testing, logs, monitoring and observability
  • Experience deploying and operating cloud-based applications
  • Solid SQL, API, data-pipeline and structured/unstructured data-processing foundations
  • Understanding of security, governance and responsible-AI requirements for enterprise applications
  • Ability to drive implementation independently while working effectively with architects, engineers, data scientists and business stakeholders
  • Strong professional English for collaboration across European teams and client environments

Preferred qualifications
  • Experience with AWS AI services, including Amazon Bedrock or related generative AI services
  • Experience with Amazon Bedrock AgentCore, AWS Strands Agents or equivalent technologies
  • Experience with other agent frameworks such as Semantic Kernel, AutoGen or CrewAI
  • Experience designing reusable multi-agent architecture patterns
  • Experience delivering AI solutions within life sciences, pharmaceuticals, financial services or another regulated industry
  • Experience with Kubernetes, Helm or other cloud-native deployment technologies
  • Experience with ML or LLM lifecycle tooling such as MLflow
  • Experience with monitoring platforms such as Prometheus, Grafana or cloud-native tracing services
  • Familiarity with classical machine learning or large-scale data processing tools such as Spark
  • Fluency in English
  • Client-first mentality
  • Intense work ethic
  • Collaborative spirit and problem-solving approach

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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 Poland , visit ZS Poland 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:
Candidates must possess or be able to obtain work authorization for their intended country of employment. 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

  • Significant hands-on experience in software engineering, AI engineering, machine learning engineering, or generative AI delivery
  • Strong Python development skills and software-engineering fundamentals
  • Experience building production-grade GenAI or agentic AI applications beyond isolated prototypes
  • Experience designing complex agentic workflows or multi-agent systems
  • Understanding of tool and function calling, stateful workflows, agent routing, delegation, memory, and context management
  • Experience with agent orchestration frameworks such as LangGraph, LangChain, or comparable technologies
  • Experience integrating AI applications with enterprise APIs, databases, systems, and external tools
  • Experience building retrieval-augmented generation or enterprise knowledge-retrieval solutions
  • Understanding of embeddings, vector search, document processing, and grounding
  • Experience defining test cases and evaluating agentic or LLM-based applications
  • Understanding of production engineering, including Docker, CI/CD, automated testing, logging, monitoring, and observability
  • Experience deploying and operating cloud-based applications
  • Solid SQL, API, data-pipeline, and structured/unstructured data-processing foundations
  • Understanding of security, governance, and responsible-AI requirements for enterprise applications
  • Ability to drive implementation independently and collaborate with architects, engineers, data scientists, and business stakeholders
  • Strong professional English for European team and client collaboration
  • Experience with AWS AI services, including Amazon Bedrock or related generative AI services
  • Experience with Amazon Bedrock AgentCore, AWS Strands Agents, or equivalent technologies
  • Experience with Semantic Kernel, AutoGen, CrewAI, or other agent frameworks
  • Experience designing reusable multi-agent architecture patterns
  • Experience delivering AI solutions in life sciences, pharmaceuticals, financial services, or another regulated industry
  • Experience with Kubernetes, Helm, or other cloud-native deployment technologies
  • Experience with ML or LLM lifecycle tooling such as MLflow
  • Experience with Prometheus, Grafana, or cloud-native tracing services
  • Familiarity with classical machine learning or large-scale data processing tools such as Spark
  • Fluency in English

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

ZS Compensation & Benefits Highlights

  • Healthcare Strength — Healthcare is described as a standout, with low‑cost medical through UMR/UnitedHealthcare, fully covered vision with an eyewear allowance, and mental‑health resources such as Talkspace, Bend Health, and a 24/7 EAP. Dental coverage is detailed as strong as well, including 100% for preventive/basic services and additional support for major and orthodontic care.
  • Parental & Family Support — The package includes 10 weeks of paid family leave and extensive family‑forming support (e.g., Carrot), plus backup childcare/eldercare/pet care and travel support like Milk Stork. These offerings indicate robust support for a wide range of family needs.
  • Leave & Time Off Breadth — Paid time off starts at 15 days from hire and increases to 20 days after 36 months, alongside 11 paid holidays, a floating holiday, and sick time with rollover. This structure signals broad time‑off provisions on paper.

ZS Insights

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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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About our Teams

ZS Offices

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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HQEvanston (Global HQ)
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