Jobs / United States / Novartis Pharmaceuticals Corporation
Associate Director, AI Foundations Engineering (3 Openings)
Novartis Pharmaceuticals Corporation · 🇺🇸 Remote Position (USA) · Remote
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 75 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Novartis Pharmaceuticals Corporation paid sponsored hires in similar roles3 certified filings for “Director, AI Use Case Lead” (Computer and Information Research Scientists) in NJ: $186k–$186k, median $186k. Most were filed at wage level III (100%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Novartis Pharmaceuticals Corporation
The US Department of Labor certified 75 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Novartis Pharmaceuticals Corporation →
About the role
Job Description Summary #LI-Remote 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. This position can be based remotely anywhere in the U.S. (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. The expectation of working hours and travel (domestic and/or international) will be defined by the Hiring Manager. There are 3 positions available. 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, t