R107731 Software Engineering Lead; AI​/ML - Raleigh, NC

The Software Engineering Lead serves as a subject matter expert for a specific team of Software Engineers. In addition to writing code on complex systems and applications, this position provides direction on project plans, schedules, and methodologies. The position has direct reports.

This is a full-time position based in Raleigh, NC.

(Hybrid - 3 days in office)

• 7+ years of Software Engineering experience
• 2+ years of experience building or integrating AI/ML-driven applications (e.g., LLM-based systems, search/recommendation systems, or intelligent automation tools).
• BS Engineering/Computer Science or equivalent experience required

• Experience developing AI-enabled applications, including LLM integrations, prompt engineering, and orchestration frameworks (e.g., Google ADK, OpenAI SDK, Anthropic SDK, Lang Chain, or similar)
• Strong proficiency with data manipulation language including optimization techniques.
• Strong understanding of normalized/dimensional data modeling principles.
• Ability to design and work with complex data models.
• Experience with vector databases and semantic search technologies (e.g., Solr, Qdrant, Elasticsearch, or similar).
• Strong knowledge of multiple data storage subsystems.
• Familiarity with RAG architectures, including document ingestion, embedding pipelines, and retrieval optimization
• Experience working with Python for AI/ML workflows is strongly preferred.
• Ability to partner and lead internal and external technology resources in solving complex business needs.
• Ability to write and review portions of detailed specifications for the development of complex system components.
• Experience designing and implementing agent-based systems, including tool usage, multi-step reasoning workflows, and API orchestration.
• Ability to evaluate AI system performance, including hallucination mitigation, evaluation frameworks, and monitoring of model outputs.

• Serve as the initial point of escalation for software development issues within specific area of responsibility.
• Interface with other technical personnel or team members to finalize requirements.
• Lead the design and implementation of AI-powered features, including LLM-based workflows, RAG pipelines, and intelligent agents.
• Write and review portions of detailed specifications for the development of system components of moderate complexity.
• Translate business problems into AI-driven solutions, selecting appropriate models, tools, and architectures.
• Establish best practices for prompt engineering, model evaluation, and safe/secure use of AI systems.
• Mentor engineers on AI/LLM development patterns, including prompt design, evaluation, and system integration.
• Stay current with advancements in generative AI, foundation models, and applied AI tooling, and drive adoption where appropriate.
• Oversee data pipelines supporting AI systems, including ingestion, embedding, indexing, and retrieval.
• Carry out management responsibilities in accordance with the organization’s policies, procedures, and applicable laws. Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance; rewarding and disciplining employees; and addressing complaints and resolving problems.
• Drive innovation through experimentation with emerging AI capabilities and rapid prototyping.