Senior Principal Al Engineer

About Cornerstone:
Cornerstone powers the future-ready workforce with modern, AI-driven employment solutions. Our platform enables companies to develop, manage, and engage their talent-unlocking growth and innovation across organizations of all sizes.

In this role you will..

• Design, develop, and deploy production-grade AI agents and multi-agent systems using modern LLM frameworks.
• Build and optimize Retrieval-Augmented Generation (RAG) solutions for enterprise-scale applications.
• Develop intelligent workflows involving planning, reasoning, memory management, tool calling, and function calling.
• Design and implement scalable backend services and REST APIs using Python frameworks such as FastAPI.
• Integrate LLMs with enterprise systems, vector databases, APIs, and external tools.
• Deploy AI applications using Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.
• Optimize AI systems for latency, scalability, reliability, and cost efficiency.
• Build evaluation pipelines to measure retrieval quality, response relevance, hallucination rates, and overall LLM performance.
• Implement semantic search, hybrid search, reranking, embedding pipelines, and vector database integrations.
• Establish observability, monitoring, logging, and tracing for AI applications using industry-standard tools.
• Collaborate with product managers, software engineers, data scientists, and platform teams to deliver end-to-end AI solutions.
• Mentor junior engineers and promote AI engineering best practices, coding standards, and architectural excellence.
• Stay up to date with emerging advancements in LLMs, Agentic AI, RAG, and AI infrastructure.

• Bachelor's or master's degree in computer science, Artificial Intelligence, Machine Learning, or a related technical field.
• 8+ years of overall software engineering experience.
• Minimum 3 years of hands-on experience building AI/Generative AI applications using Large Language Models (LLMs).
• Minimum 3 years of experience developing scalable backend software and distributed systems.
• Strong proficiency in Java and Python and modern software engineering principles.
• Hands-on experience with AI orchestration frameworks such as LangGraph, LangChain, LlamaIndex, etc.
• Experience designing and implementing production-grade RAG systems, including embedding models, semantic search, hybrid search, reranking, and vector databases.
• Experience with vector databases such as Milvus, Pinecone, Weaviate, OpenSearch, Elasticsearch, FAISS, or ChromaDB.
• Experience integrating and deploying applications using LLMs such as OpenAI GPT, Claude, Gemini, Llama, Mistral, Amazon Nova, or Azure OpenAI.
• Strong experience building REST APIs using FastAPI or similar Python frameworks.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Experience deploying AI solutions on cloud platforms such as AWS, Azure, or GCP.
• Familiarity with CI/CD pipelines, Git, and modern DevOps practices.
• Experience with AI evaluation, prompt engineering, observability, and monitoring tools such as LangSmith, Langfuse, MLflow, OpenTelemetry, Prometheus, or Grafana.
• Strong understanding of software architecture, microservices, asynchronous programming, and distributed systems.
• Excellent problem-solving, communication, and collaboration skills, with the ability to work effectively in a cross-functional team environment.