Principal Machine Learning Engineer, SecureAI

📋 Description

• Implement intent-based enforcement to verify agent runtime requests match their intended purpose
• Apply LLM reasoning and prompt parsing to interpret prompts, tool payloads, and intent in real time
• Integrate low-latency inference or semantic evaluation engines directly into the API gateway
• Use embeddings, vector search, or zero-shot classification to score alignment between agent intent
• Design confidence-scored decision engines that feed semantic verification results into policy
• Establish evaluation benchmarks, prompt injection defenses, and guardrails to prevent bypasses or

🎯 Requirements

• 10+ years of software development experience, with strong programming expertise in Python (and
• Hands-on experience with applied machine learning, from feature engineering to training and
• Hands-on experience with modern Generative AI platforms (AWS Bedrock, OpenAI, Anthropic, etc.)
• Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base workflows
• Hands-on experience with LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or other related AI agent
• Familiarity with ML frameworks (FastAPI, PyTorch, TensorFlow, Spark ML) and workflow orchestration

🎁 Benefits

• Equity (where applicable)
• Bonus
• Health, dental, and vision insurance
• 401(k)
• Flexible spending account
• Paid leave (including PTO and parental leave)