Principal Engineer - Gen AI

Job Summary Responsibilities

• Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups
• Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking
• Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions
• Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions
• Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization
• Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership

Required Qualifications

• 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications

• Proven experience designing and scaling enterprise GenAI platforms and AI-driven products.
• Strong expertise in Agentic AI, multi-agent systems, RAG architectures, Knowledge Graphs, and long-term memory frameworks.
• Experience architecting model orchestration solutions, including model routing, selection, fallback, and optimization strategies.
• Deep understanding of LLMOps, AI platform engineering, CI/CD automation, and production-grade AI deployments.
• Hands-on experience with cloud AI platforms such as Azure OpenAI, AWS Bedrock, and Google Vertex AI.
• Proficiency with GenAI frameworks including LangGraph, LangChain, AutoGen, MCP, or equivalent orchestration technologies.
• Expertise in vector databases, graph databases, embeddings, semantic search, and retrieval technologies.
• Strong cloud-native engineering background with Kubernetes, microservices, containers, and distributed systems.
• Experience establishing AI observability, monitoring, evaluation, resiliency, and reliability practices.
• Knowledge of AI security, responsible AI, governance, privacy, and regulatory requirements.
• Understanding of token economics, AI cost optimization, usage forecasting, and platform efficiency strategies.
• Experience designing reusable APIs, SDKs, and developer frameworks that accelerate enterprise adoption.