The Senior Developer, AI is responsible for designing, developing, deploying, and supporting enterprise AI solutions including scalable AI applications, AI agents, and RAG solutions using Databricks.
Responsibilities
Design, build, test, deploy, and support scalable enterprise AI applications, AI agents, and intelligent workflows using Databricks and cloud-native technologies.
Develop AI agents, multi-agent workflows, and RAG solutions by integrating enterprise data, APIs, tools, and business processes to enable automation and decision support.
Create APIs, backend services, integrations, and reusable frameworks while applying software engineering best practices such as CI/CD, automated testing, monitoring, and secure deployment.
Drive solution reliability, performance, Responsible AI compliance, data governance, operational readiness, and continuous improvement through testing, evaluation, and technical reviews.
Partner with business stakeholders, Product Owners, Architects, Data Scientists, Data Engineers, platform teams, and vendors while providing technical guidance, knowledge sharing, and mentoring across AI Delivery PODs.
Lead the commercial and technical strategy for CoreWeave’s inference offerings across the AMER region, driving new customer wins, shaping product roadmap, and translating customer needs into product feedback.
Locations (6)
Bellevue, Washington, United States
Dallas, Texas, United States
Livingston, New Jersey, United States
Manhattan, New York, United States
San Francisco, California, United States
Senior Principal Chief Architect -Enterprise Platform/Distributed AI Infrastructure & Kubernetes/PyTorch
Lead the Forward Deployed Engineering function for APAC AI Center of Excellence, architecting hybrid cloud AI platforms and driving open‑source community engagement.
Responsibilities
Orchestrate the Forward Deployed Engineering squad and set technical strategy
Drive end‑to‑end technical strategy for large‑scale hybrid cloud AI deployments
Design complex integration layers for client platforms
Act as primary technical bridge to global product and ecosystem engineering hubs
Maintain community‑first mindset and contribute to open‑source foundations
Lead the Data & AI Platforms tower, owning strategy, roadmap, and operations for enterprise data and AI platforms on AWS and Databricks, while managing cross-functional teams and ensuring platform stability during the company separation.
Compensation
The anticipated base pay range for this position is : $168,000.00 - $290,950.00
Responsibilities
Own strategy, roadmap, budget and run of enterprise Data & AI platforms on AWS and Databricks
Turn target-state architecture and standards into platform services
Stand up and stabilize cloned and transitional platforms during separation
Plan and deliver TSA exits from Johnson & Johnson platforms
Consolidate regional and functional data lakes, ingestion frameworks and BI tools onto one governed lakehouse
Requirements
Bachelor’s degree in Computer Science, Engineering or a related technical field
Nice to have: Master’s degree in Computer Science, Engineering or a related field
Nice to have: medical device
Nice to have: life sciences
Nice to have: regulated industry (GxP, CSV/CSA, 21 CFR Part 11, data privacy)
Build and maintain foundational cloud infrastructure for AI and ML data science teams at Penguin Random House.
Compensation
The salary range for this position is $185,000-$210,000. All positions are currently eligible for an annual profit award or bonus, subject to Company results.
Responsibilities
Design and own core components of our AWS environment used across data science products
Set standards for how people and AI agents change infrastructure, including reviews, tests and guardrails
Build self‑service CI/CD pipelines and promotion gates for scientists to ship models
Help maintain security, compliance and reliability of cloud environments
Shape platform roadmap and communicate progress to stakeholders
Requirements
Nice to have: Evaluation or error analysis of ML or LLM systems
Senior MLOps & Cloud Infrastructure Engineer responsible for building, operating, and evolving the cloud infrastructure and engineering platforms behind production AI systems.
Responsibilities
Design, provision, and operate scalable infrastructure on GCP
Manage containerised applications and ML workloads with Kubernetes
Build reproducible infrastructure using Terraform
Design and improve CI/CD pipelines for backend services and data pipelines
Improve service availability, resilience, and incident response
Support the Compliance and Client Lifecycle Integrity (CLI) departments by simplifying access to data, automating processes and contributing to the development of AI into the tasks of the Compliance and Client Lifecycle Integrity departments.
Responsibilities
Process streamlining and automation
Data Stewardship
Reporting & Regulatory Support
Compliance Analysis
Ad-hoc Projects
Requirements
Master's degree in a Quantitative field, Engineering, Computer Science or Data Science
Lead and grow an engineering team dedicated to bringing production‑grade machine learning models to the core of global trade intelligence.
Responsibilities
Lead, coach, and support a high‑performing squad of Machine Learning Engineers
Drive the end‑to‑end technical direction and operational excellence for ML infrastructure, automated training, model evaluation, and low‑latency inference pipelines
Partner with Product Managers, Data Scientists, and Data Engineering leads to align roadmaps, scope technical initiatives, and deliver high‑impact features predictably
Define and champion engineering best practices across MLOps, system observability, data quality monitoring, and automated testing to ensure high reliability
Provide architectural guidance and participate in technical design reviews, helping the team evaluate trade‑offs between speed, scalability, and long‑term maintainability
The base salary range for this role is $177,000 to $237,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).
Responsibilities
Serve as the AMER field's primary intelligence source on AI inference
Drive commercial and technical strategy in AMER for net new customer wins
Identify new business opportunities in AMER
Develop deep expertise across the AI runtime landscape
Translate customer requirements into product feedback
Requirements
Advanced degree in Computer Science, Machine Learning, or Engineering
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