Associate Director, AI Foundations Engineering (3 Openings)
Novartis
Summary
The Associate Director, AI Foundations Engineering will lead the engineering strategy, design, development, deployment, and ongoing optimization of our agentic AI platform and solutions. This role is responsible for building scalable, secure, and reliable AI-driven systems that transform existing products, processes, and workflows into intelligent, agentic AI experiences. As a key technical leader, the Associate Director will partner closely with product, data, architecture, security, and business teams to define platform capabilities, drive implementation excellence, and operationalize continuous improvement across the AI lifecycle. The ideal candidate brings deep expertise in AI engineering, platform architecture, and production operations, along with a strong track record of translating emerging AI capabilities into practical, high-impact business solutions.
Job description
Key Responsibilities
- Lead the architecture, design, and engineering delivery of the organization's agentic AI platform and related solutions.
- Drive the transformation of existing products, processes, and workflows into scalable agentic AI-enabled capabilities.
- Oversee end-to-end AI engineering operations, including development, deployment, monitoring, reliability, and continuous improvement.
- Partner with cross-functional stakeholders to define technical roadmaps, platform standards, and solution priorities aligned to business goals.
- Establish engineering best practices for AI system performance, scalability, security, governance, and maintainability.
- Guide the evaluation, integration, and optimization of AI models, orchestration frameworks, and supporting platform components.
- Build, mentor, and lead high-performing engineering teams while fostering innovation, accountability, and technical excellence.
- Identify opportunities to accelerate value delivery through reusable AI services, automation, and operational efficiencies.
Essential Requirements
- Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience. An advanced degree is a plus but not required.
- 5+ years of professional software engineering experience, including at least 1–2 years building applications on large language models, with at least one agentic system deployed beyond a demo.
- Hands-on experience building AI agents on AWS. This includes Amazon Bedrock (models, Agents, Knowledge Bases, Guardrails) and Bedrock AgentCore or comparable approaches for agent runtime, memory, tool access, and identity.
- Proficiency with at least one agent framework, such as Strands Agents, LangGraph, LlamaIndex, CrewAI, or a custom orchestration layer. You should be able to explain when a simple workflow beats a multi-agent design.
- Strong Python skills plus experience with AWS services commonly used in agent architectures: Lambda, Step Functions, ECS/EKS, API Gateway, DynamoDB, S3, and IAM.
- Experience with retrieval-augmented generation (RAG), including chunking strategies, embeddings, vector stores (OpenSearch, pgvector, or similar), and improving retrieval quality.
- Experience designing tool use and function calling so agents can connect to APIs, databases, and enterprise systems. Familiarity with Model Context Protocol (MCP) is preferred.
- A practical approach to evaluation and observability: test sets for agent behavior, LLM-as-judge or human review loops, tracing (CloudWatch, OpenTelemetry, LangSmith, or similar), and monitoring cost and latency.
- Ability to take an ambiguous business problem to a working prototype quickly, then harden it for real users with security, guardrails, error handling, and CI/CD using CDK or Terraform.
- Clear communication of technical tradeoffs to product and business partners, and comfort working in a small, fast-moving team.
Requirements
- Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience
- 5+ years of professional software engineering experience
- At least 1–2 years building applications on large language models
- At least one agentic system deployed beyond a demo
- Hands-on experience building AI agents on AWS
- Experience with Amazon Bedrock (models, Agents, Knowledge Bases, Guardrails)
- Experience with Bedrock AgentCore or comparable approaches for agent runtime, memory, tool access, and identity
- Proficiency with at least one agent framework (Strands Agents, LangGraph, LlamaIndex, CrewAI, or custom orchestration layer)
- Strong Python skills
- Experience with AWS services: Lambda, Step Functions, ECS/EKS, API Gateway, DynamoDB, S3, IAM
- Experience with retrieval-augmented generation (RAG), including chunking strategies, embeddings, vector stores (OpenSearch, pgvector, or similar), and improving retrieval quality
- Experience designing tool use and function calling for agents to connect to APIs, databases, and enterprise systems
- Familiarity with Model Context Protocol (MCP) is preferred
- Practical approach to evaluation and observability: test sets for agent behavior, LLM-as-judge or human review loops, tracing (CloudWatch, OpenTelemetry, LangSmith, or similar), and monitoring cost and latency
- Ability to take an ambiguous business problem to a working prototype quickly, then harden it for real users with security, guardrails, error handling, and CI/CD using CDK or Terraform
- Clear communication of technical tradeoffs to product and business partners
- Comfort working in a small, fast-moving team
Benefits
- Health Insurance
- Life Insurance
- Disability Benefits
- 401(k) with company contribution and match
- Vacation
- Personal days
- Holidays
- Performance-based cash incentive
- Annual equity awards
Company overview
Novartis is a global pharmaceutical company headquartered in Basel, Switzerland, dedicated to reimagining medicine to improve and extend people's lives. As an innovative medicines company, Novartis focuses on developing high-value treatments that address society's greatest disease burdens through technology leadership in research and development. The company operates across five core therapeutic areas: cardiovascular, renal and metabolic diseases; immunology; neuroscience; oncology; and hematology. With a workforce of approximately 75,883 employees worldwide, Novartis reaches nearly 300 million patients across 118 countries. The company leverages advanced technology platforms including targeted protein degradation, cell therapy, gene therapy, radioligand therapy, and xRNA to develop breakthrough treatments. Novartis maintains a strong portfolio of oncology drugs and generics while continuously expanding its pipeline through strategic acquisitions and internal research. The company's commitment extends beyond drug development to ensuring global access to medical innovations through novel access approaches and patient assistance programs.