Principal AI Software Engineer

Insight Global is looking for a Principal AI Software Engineer to support a global client. As a Principal AI Software Engineer, you will drive technical vision and architect enterprise AI applications for multiple initiatives across the company. You’ll integrate LLMs, agent workflows, NLP, computer vision, and predictive analytics to build secure, high-availability and cost-efficient AI based solutions. You’ll partner with product, data science, and engineering leaders, mentor teams, and raise standards in Agile, testing, security, and documentation. We support growth, autonomy, and collaboration across research and product., Set AI architecture and technical vision across products. Lead cross-team initiatives with product and data science. Design RAG and agent workflows; optimize LLM integrations. Build multi-tenant, high-availability systems with observability. Establish AI cost management, monitoring, and security standards.

Bachelor’s degree in Computer Science, Computer Engineering, or related technical field. 10+ years of programming experience in a relevant language using modern front-end frameworks (React, Vue, or Angular) and multiple backend languages (Python preferred, Java, Node.js or Go). Proven track record designing and shipping production applications that incorporate LLMs or AI services at scale. Experience with vector databases (e.g. Milvus, Pinecone, Weaviate, pgvector) and advanced embedding model optimization in production applications. Expertise with multiple LLM providers and advanced AI orchestration frameworks (LangChain, LlamaIndex, custom frameworks). Extensive experience leading technical teams, driving cross-team initiatives, and providing technical mentorship. Expert-level experience with cloud platforms (AWS, GCP, or Azure) and advanced containerization (EKS). 13+ years of full software development lifecycle experience, including architecture design, technical leadership, and large-scale system optimization. Advanced understanding of enterprise RAG architectures, semantic search optimization, and conversation memory management at massive scale. Experience with multi-modal AI integration, model fine-tuning, and deployment of custom AI models. Experience with AI observability tools, cost optimization strategies, and performance monitoring at enterprise scale. Experience with cross-organizational collaboration and influencing other teams’ directions and road maps. Experience with technical strategy development and technology roadmap planning.