Principle Applied AI Engineer

Job Overview

As the Principal Applied AI Engineer, you will be the lead architect of the "cognitive" layer of the AI platform. While the Backend Principal builds the deterministic infrastructure, you will engineer the probabilistic systems that power our "Unified Context Library" and "Agentic Orchestration" layer. You will design the autonomous workflows that turn a Product Manager’s idea into a technical specification, and a User Story into deployable code.

This role sits at the intersection of elite software engineering and applied artificial intelligence. You will not be training foundational models from scratch; rather, you will be mastering the art of Applied AI: orchestration, retrieval‑augmented generation (RAG), and the engineering of agentic systems using the AWS Bedrock Agent Core framework. You will work within the AI Platform Services division, a dedicated R&D unit tasked with delivering measurable velocity improvements to the entire organization.

Why Join Pennymac?

• Architect the Future of SDLC: You will build the "Agent Factory" that drives our "conveyor belt" of software delivery, moving us from a reactive to a proactive engineering culture.
• Greenfield Innovation: This is a rare chance to build an enterprise‑grade AI platform from the ground up, leveraging the latest in AWS Bedrock Agent Core and Agentic AI frameworks.
• High-Impact & Visibility: Your work will directly impact the daily lives of hundreds of engineers and product owners, reducing "Idea-to-MR" cycle times and eliminating manual toil.
• Cutting-Edge Stack: Work with a modern, cloud‑native stack (AWS, Node.js/Type Script) specifically tailored for high‑performance AI applications.

• Elite Engineering Core: Bachelor’s Degree in Computer Science or equivalent, with 8+ years of professional software engineering experience. You are a software engineer first, who has mastered AI tools.
• Type Script/Node.js Expert: Unlike most AI roles that focus on Python, our platform is built on Node.js and Type Script. You must have deep expertise in building backend services and AI chains in this ecosystem.
• Applied AI & Agent
  
  Experience:
  
  Hands‑on experience building applications powered by LLMs. You have shipped products using frameworks like Lang Chain, Strands, or AWS Bedrock.
• RAG Mastery: Proven track record of building production‑grade RAG systems. You understand the nuances of embeddings, vector stores (Pinecone, Milvus), and semantic search.
• Cloud Native (AWS): Extensive experience with AWS serverless architecture (Lambda, API Gateway, Dynamo
  
  DB). Familiarity with AWS Bedrock and Agent Core is a significant advantage.
• Systems Thinking: Ability to design complex, asynchronous systems where state is fluid and outcomes are probabilistic.
• Startup Mentality: High ownership, high energy, and the ability to thrive in a fast‑paced "internal startup" environment.

• Experience with Evaluation Frameworks (e.g., Lang Smith, Ragas) for automated testing of LLM outputs.
• Familiarity with the Model Context Protocol (MCP) for standardizing AI tool connections.
• Background in Developer Tools (building CLI tools, IDE plugins, or CI/CD automations).
• Understanding of Graph Databases (e.g., Neo4j) for knowledge graph implementation alongside vector search.

Some key benefits include:

• Comprehensive Medical, Dental, and Vision
• Paid Time Off Programs including vacation, holidays, illness, and parental leave
• Wellness Programs, Employee Recognition Programs, and onsite gyms and cafe style dining (select locations)
• Retirement benefits, life insurance, 401k match, and tuition reimbursement
• Philanthropy Programs including matching gifts, volunteer grants, charitable grants and corporate sponsor ships

Salary range: $90,000 – $150,000. Individual salary may vary based on location, market data, and experience. Some roles may be eligible for performance-based compensation and/or stock-based incentives awarded to employees based on company and individual performance.

Office