Principal Analyst, AI Solutions

Red Hat•Raleigh, NC

About The Position

The Data and Innovation team is seeking a Retrieval Strategist to serve as product manager and technical strategist for our search and content retrieval capabilities. In this role, you will lead the evolution of search infrastructure to support both traditional keyword-based search and modern AI-powered retrieval patterns including RAG (Retrieval-Augmented Generation), MCP servers, and conversational search agents. You will be responsible for defining how search capabilities must adapt to effectively serve AI applications while maintaining excellence in traditional search use cases. This role requires deep software engineering expertise, particularly in search engineering, combined with product management skills to drive the team's roadmap and prioritize initiatives. You will focus heavily on retrieval quality, establishing processes and metrics to monitor performance and rapidly address issues, while also researching emerging technologies like vector search and hybrid search approaches to inform the team's strategic direction. At Red Hat, our commitment to open source innovation extends beyond our products - it’s embedded in how we work and grow. Red Hatters embrace change – especially in our fast-moving technological landscape – and have a strong growth mindset. That's why we encourage our teams to proactively, thoughtfully, and ethically use AI to simplify their workflows, cut complexity, and boost efficiency. This empowers our associates to focus on higher-impact work, creating smart, more innovative solutions that solve our customers' most pressing challenges.

Requirements

8+ years of software engineering experience with significant focus on search engineering and information retrieval
Deep expertise in search technologies such as Elasticsearch, Solr, or similar platforms
Strong understanding of search algorithms, relevance ranking, and query processing techniques
Experience with vector databases and embedding-based search approaches (e.g., FAISS, Pinecone, Weaviate)
Knowledge of RAG (Retrieval-Augmented Generation) architectures and their application to AI systems
Familiarity with natural language processing and semantic search concepts
Product management experience or demonstrated ability to manage roadmaps and drive technical initiatives
Strong programming skills in languages such as Python, Java, or similar
Experience implementing search quality metrics and monitoring systems
Understanding of distributed systems and scalability challenges in search infrastructure
Excellent analytical and problem-solving skills with data-driven decision-making approach
Strong communication skills with ability to explain technical concepts to varied audiences
Bachelor's degree in computer science or related technical discipline; advanced degree preferred

Nice To Haves

Experience with machine learning and LLM-based applications
Knowledge of content management systems and document processing pipelines
Experience with A/B testing and experimentation frameworks for search optimization

Responsibilities

Serve as product manager for the search and content retrieval team, defining roadmap, priorities, and success metrics
Develop and implement retrieval quality frameworks, including monitoring, testing, and rapid issue resolution processes
Define technical strategy for supporting AI applications, including RAG pipelines, MCP server integrations, and conversational search interfaces
Research and experiment with emerging retrieval technologies including vector search, hybrid search, semantic search, and embedding-based approaches
Collaborate with AI/ML teams to understand retrieval requirements for AI agents and ensure search infrastructure meets their needs
Work with content management teams to optimize content indexing, metadata, and structure for improved retrieval quality
Establish performance benchmarks and quality metrics for both traditional and AI-powered retrieval use cases
Lead proof-of-concept projects to validate new retrieval approaches and technologies
Provide technical guidance to the search engineering team on architecture and implementation decisions
Partner with application teams to integrate search capabilities and gather feedback on retrieval quality
Stay current with industry trends in information retrieval, search technologies, and AI-powered content discovery
Create documentation and best practices for search integration patterns and optimization techniques
Analyze search usage patterns and quality metrics to identify opportunities for improvement

Benefits

Comprehensive medical, dental, and vision coverage
Flexible Spending Account - healthcare and dependent care
Health Savings Account - high deductible medical plan
Retirement 401(k) with employer match
Paid time off and holidays
Paid parental leave plans for all new parents
Leave benefits including disability, paid family medical leave, and paid military leave
Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

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