Associate Director, AI Engineer

Salary Range:

Kč1,354,220.00 - Kč2,514,980.00

Job Description Summary

#LI-Hybrid
Location: Prague, Czech Republic / Basel, Switzerland
About the Role
We are hiring four Associate Directors, AI Engineering to join Biomedical Research Data & Digital, Software & Workflows and help shape the next generation of agentic AI capabilities across Novartis Biomedical Research.
As an Associate Director, AI Engineer, you will be a senior individual contributor and technical authority for production-grade agentic AI. This is a hands-on technical leadership role, not a people-management position. Leadership is exercised through technical direction, architecture, engineering excellence and influence rather than direct reports.
You will own complex architecture and design decisions, establish engineering standards and reference architectures for others to build upon, and remain actively involved in the code.
The Software & Workflows organization partners with scientists, data experts and AI specialists across Novartis Biomedical Research to transform scientific workflows and laboratory processes. Our ambition is to make advanced digital and AI capabilities usable, scalable and impactful, helping teams generate better insights, improve decisions and accelerate the discovery of innovative medicines.
You will set the technical direction for agentic AI across a broad portfolio of software delivery initiatives. You will bring together engineering, science, architecture, operations, security and enterprise technology, challenge established approaches, make thoughtful technical trade-offs and help engineers learn and grow, while ensuring solutions meet demanding standards for quality, performance, security, compliance and reliability.
What You'll Work On
You will work on agentic AI for drug discovery, scientific workflow automation and lab-in-the-loop systems.
You will own the architecture behind some of the team's most complex technical challenges, including multi-agent platforms designed to accelerate target identification and the broader drug discovery pipeline, agentic automation of complex cross-functional scientific research workflows, and lab-in-the-loop systems integrating AI reasoning with wet-lab experimentation.
You will establish the engineering patterns and reference architectures that enable these systems to be scalable, trustworthy and reusable across the organization.

Job Description

Key Responsibilities

• Own the architecture and design of agentic AI platforms and solutions end to end, remaining hands-on through development, deployment, monitoring, reliability and continuous improvement.
• Take complex technical problems from ambiguous business or scientific needs through to robust, production-grade solutions.
• Drive the transformation of existing products, processes and scientific workflows into scalable agentic AI-enabled capabilities, including drug discovery, scientific workflow automation and lab-in-the-loop systems.
• Own architecture decisions for agentic systems and large language model inference at scale on AWS, including Amazon Bedrock and AgentCore, balancing reliability, latency, cost, security and governance.
• Establish engineering best practices and reference architectures for AI system performance, scalability, security, governance and maintainability.
• Define and advance DevOps, MLOps and AgentOps standards, including CI/CD, infrastructure as code, containerization, reproducible pipelines, model/data/prompt versioning and experiment tracking.
• Guide the evaluation, integration and optimization of AI models, agent orchestration frameworks and supporting platform components.
• Define evaluation and observability standards, including agent test sets, human or LLM-based evaluation, tracing, and cost and latency monitoring.
• Partner with product, data, architecture, security and scientific stakeholders to define technical roadmaps, platform standards and solution priorities aligned with business and scientific goals.
• Raise the technical bar across the engineering community through design reviews, coding standards and technical mentorship, providing leadership through technical expertise and influence rather than direct people management.

Essential Requirements

• 8+ years of professional software and/or AI engineering experience, including experience delivering production-grade AI solutions and a strong track record as a hands-on technical lead.
• Deep hands-on expertise building AI agents on AWS, including Amazon Bedrock, such as models, Agents, Knowledge Bases and Guardrails, and Bedrock AgentCore.
• Proficiency with at least one agent framework, such as Strands, LangGraph, LlamaIndex, CrewAI or custom orchestration, and the judgement to determine when a simpler workflow is preferable to a multi-agent architecture.
• Strong Python expertise together with experience using AWS services commonly used in agent architectures, such as Lambda, Step Functions, ECS/EKS, API Gateway, DynamoDB, S3 and IAM.
• Experience with retrieval-augmented generation, including chunking, embeddings and vector stores such as OpenSearch or pgvector, as well as tool use/function calling to connect agents with APIs, databases and enterprise systems. Model Context Protocol experience is preferred.
• Deep DevOps/MLOps expertise, including CI/CD, infrastructure as code using CDK or Terraform, containers and orchestration, reproducible pipelines, rigorous AI evaluation and observability.
• Demonstrated ability to translate ambiguous business or scientific problems into secure, resilient production solutions incorporating appropriate guardrails, error handling and governance.
• Demonstrated ability to set technical direction, drive design decisions across engineers and clearly communicate complex technical trade-offs to product, scientific and business stakeholders.

Desirable Requirements

• Experience operationalizing AI coding tools and modern AgentOps practices across an engineering team.
• Experience with AI governance and compliance within a regulated or life-sciences environment, including awareness of the EU AI Act.

Benefits & Rewards

At Novartis, we're committed to reimagining medicine together and rewarding the people who make it happen.

Expected Annual Base Salary Range for role: 1,354,220 CZK to 2,514,980 CZK Annual

The base salary offered is determined based on gender-neutral objectives, such as relevant skills, competencies and experience in accordance with the Novartis pay setting policy and upon joining Novartis will be reviewed periodically.

In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters.

The rewards of being part of our team go far beyond base pay and incentives. We also offer a variety of competitive benefits in kind to help you thrive personally and professionally, such as insurance plans, retirement plans, wellbeing resources and global recognition programs. In addition, we provide flexible and hybrid working options, where possible, and a minimum of 14 weeks paid parental leave.

Pay equity is a fundamental principle of our employment policy and reflects our commitment to create a diverse, equitable and inclusive environment that treats all employees with dignity and respect, as outlined in our Code of Ethics.

Benefits and compensation may vary by country and are subject to local legal requirements, including provisions of collective bargaining agreements where applicable. A full overview of your compensation package, including any relevant collective bargaining agreement details applicable to your role based on your employment location and Novartis employer entity, will be communicated separately to you during the application process.

Commitment to Diversity and Inclusion

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Skills Desired

AngularJS, Back-End Development, C++ Programming Language, Graphics Tools, Hardware Architectures, Model-View-ViewModel (MVVM), Object-Oriented Design (OOD), Software Architectures, Software Design, Software Development, Software Engineering, Spring Boot, Systems Architecture, Unit Testing, Verification and Validation (V&V), Windows Presentation Foundation