Associate Director, Scientific Computing and AI Engineer
Denali Therapeutics
August 31, 2026
Remote friendly (South San Francisco, CA)
United States
IT
Key Accountabilities/Core Job Responsibilities
Scientific Computing & HPC Platform Engineering
- Lead architecture, build-out, and ongoing optimization of on-prem GPU clusters, hybrid cloud HPC environments, and supporting storage and networking infrastructure
- Partner with research scientists to profile workloads, size infrastructure, and improve job performance and researcher self-service
- Design, operate, and support compute environments for intensive workloads (e.g., molecular dynamics, CryoEM, genomics, structural biology, AI model training)
- Implement job scheduler configurations (Slurm/LSF), parallel file systems, and interconnect optimization to maximize throughput/utilization
- Architect cloud-burst strategies for elastic scaling of peak HPC and ML training workloads
Applied AI Engineering & Generative AI Solutions
- Design/engineer production AI/ML and generative AI solutions across cloud infrastructure, data pipelines, vector databases, RAG architectures, and LLM app layers
- Build and deploy agentic AI workflows to automate or augment scientific processes
- Develop and maintain AI evaluation frameworks, prompt engineering standards, and MLOps for reliable, auditable outputs in a GxP-adjacent environment
- Prototype/pilot AI capabilities (agents, digital twins, foundation model fine-tuning) and transition to scalable production
- Collaborate to scope AI use cases, define success criteria, and deliver proof-of-concept and production deployments
- Implement Infrastructure as Code and CI/CD with integrated security and compliance controls
Technical Leadership & Architecture Guidance
- Act as senior technical partner; set engineering standards, reference architectures, and guardrails
- Mentor engineers; translate complex concepts for non-technical stakeholders
- Evaluate technologies; lead proof-of-concepts and build-vs-buy recommendations
- Participate in architecture reviews
Requirements
- Bachelor’s or Master’s in CS, Engineering, or related field
- Typically 10–12+ years platform/scientific computing/infrastructure experience; 3+ years as senior/principal individual contributor
- Deep hands-on expertise in 2+ areas: HPC (Slurm/LSF, parallel FS, GPU/CUDA), production cloud engineering, AI/ML platform engineering, generative/agentic systems (LangChain, LangGraph, AutoGen) and foundation models
- Proficiency in Infrastructure as Code and CI/CD; strong Python/scripting
- Experience in regulated biotech/pharma/life sciences with GxP or 21 CFR Part 11/data integrity frameworks
- Ability to lead initiatives end-to-end from architecture to production
- Hands-on experience with vector databases, knowledge graphs, and RAG architectures
Compensation/Benefits
- Salary range: $159,000.00–$207,000.00; total rewards include 401k, healthcare coverage, ESPP, and other benefits
Application Instructions
- Learn more/careers: https://www.denalitherapeutics.com/careers
Scientific Computing & HPC Platform Engineering
- Lead architecture, build-out, and ongoing optimization of on-prem GPU clusters, hybrid cloud HPC environments, and supporting storage and networking infrastructure
- Partner with research scientists to profile workloads, size infrastructure, and improve job performance and researcher self-service
- Design, operate, and support compute environments for intensive workloads (e.g., molecular dynamics, CryoEM, genomics, structural biology, AI model training)
- Implement job scheduler configurations (Slurm/LSF), parallel file systems, and interconnect optimization to maximize throughput/utilization
- Architect cloud-burst strategies for elastic scaling of peak HPC and ML training workloads
Applied AI Engineering & Generative AI Solutions
- Design/engineer production AI/ML and generative AI solutions across cloud infrastructure, data pipelines, vector databases, RAG architectures, and LLM app layers
- Build and deploy agentic AI workflows to automate or augment scientific processes
- Develop and maintain AI evaluation frameworks, prompt engineering standards, and MLOps for reliable, auditable outputs in a GxP-adjacent environment
- Prototype/pilot AI capabilities (agents, digital twins, foundation model fine-tuning) and transition to scalable production
- Collaborate to scope AI use cases, define success criteria, and deliver proof-of-concept and production deployments
- Implement Infrastructure as Code and CI/CD with integrated security and compliance controls
Technical Leadership & Architecture Guidance
- Act as senior technical partner; set engineering standards, reference architectures, and guardrails
- Mentor engineers; translate complex concepts for non-technical stakeholders
- Evaluate technologies; lead proof-of-concepts and build-vs-buy recommendations
- Participate in architecture reviews
Requirements
- Bachelor’s or Master’s in CS, Engineering, or related field
- Typically 10–12+ years platform/scientific computing/infrastructure experience; 3+ years as senior/principal individual contributor
- Deep hands-on expertise in 2+ areas: HPC (Slurm/LSF, parallel FS, GPU/CUDA), production cloud engineering, AI/ML platform engineering, generative/agentic systems (LangChain, LangGraph, AutoGen) and foundation models
- Proficiency in Infrastructure as Code and CI/CD; strong Python/scripting
- Experience in regulated biotech/pharma/life sciences with GxP or 21 CFR Part 11/data integrity frameworks
- Ability to lead initiatives end-to-end from architecture to production
- Hands-on experience with vector databases, knowledge graphs, and RAG architectures
Compensation/Benefits
- Salary range: $159,000.00–$207,000.00; total rewards include 401k, healthcare coverage, ESPP, and other benefits
Application Instructions
- Learn more/careers: https://www.denalitherapeutics.com/careers