Data and AI Platform Engineer

Overview

We’re looking for a driven AI/ML Engineer to join our Data & AI Platform Engineering team and help build enterprise-grade AI and machine learning capabilities at scale.

In this role, you’ll partner with senior engineers, data scientists, and cross-functional teams to design, build, and support production-ready, well-governed AI/ML solutions
. You’ll work hands-on with unstructured data, embeddings, metadata, and semantic models
, while applying modern engineering practices in a secure, enterprise environment.

If you’re excited about LLMs, foundation models, and responsible AI
, and want to apply them in real-world, governed platforms—this role is for you.

• Design, implement, and support AI/ML components aligned with enterprise engineering standards
• Build secure, scalable, and maintainable AI/ML solutions using proven frameworks and patterns
• Develop pipelines for unstructured and semi-structured data (documents, text, metadata)
• Apply embeddings and semantic modeling to improve search, discovery, and AI use cases
• Write production-quality code with strong testing, CI/CD, and code review practices
• Collaborate with engineers, data scientists, and business partners to deliver impact
• Support MLOps/FMOps practices including deployment, versioning, monitoring, and reliability
• Apply LLMs and prompt engineering within established architectural and governance guidelines
• Contribute to AI governance, documentation, lineage, validation, and transparency

• 3+ years of experience in AI/ML engineering or applied machine learning
• Proven experience delivering AI/ML solutions in production
• Hands-on experience with unstructured data, embeddings, or semantic techniques
• Strong Python skills (Java or similar languages a plus)
• Experience with ML frameworks (Tensor Flow, PyTorch, Scikit-learn)
• Cloud experience—
  AWS preferred (AWS Bedrock a strong plus)
• Exposure to MLOps/FMOps and governed AI environments
• Familiarity with Spark, SQL, No
  
  SQL;
  Palantir Foundry/AIP a plus