Manager Software Engineering (AI/ML)

About the Role:

The Manager of Software Engineer provides leadership, management, direction, and vision to software engineers and/or development employees including offshore contractors/consultants and interns needed to support, run, and change activities in the software development life cycle. The position works closely with development peers, product and project leaders/managers, and other in-house software developers.

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

(Hybrid - 3 days in office)

Requirements:

• 10 years of Software Development experience

• 2 years of management experience

• BS Engineering/Computer Science or equivalent experience required; advanced degree preferred

• Experience leading teams delivering AI/ML-driven products or data-intensive platforms is strongly preferred.

Technical Skills:

• Expertise and proven experience in various staffing and resource models.

• Strong proficiency in database technology, design and manipulation, optimization, and best practices.

• Knowledge in normalized/dimensional data modeling principles and their application to complex business needs.

• Experience with modern data architectures supporting AI systems (e.g., data pipelines, feature/embedding pipelines).

• Proven knowledge and experience in project planning and management tools to manage project progress, budget, and scope.

• Experience in code reviews and development approaches.

• Expertise in industry best practices in offshore partnership development.

• Proven ability to lead test-driven development and maintenance.

• Industrywide or broad companywide technical knowledge.

• Specialized coding skills.

• Knowledge of large complex systems.

• Software development process expert in applicable methodologies (e.g., Agile, Waterfall).

• Expertise in data modeling, design and manipulation, optimization, best practices, tuning, and leading industry trend knowledge.

• Experience building or managing AI-enabled systems, including LLM integrations, RAG pipelines, or search/recommendation systems.

• Familiarity with vector databases, semantic search, and information retrieval systems (e.g., Pinecone, OpenSearch, Elasticsearch).

• Understanding of prompt engineering, model evaluation, and AI system reliability (e.g., hallucination mitigation, evaluation frameworks).

Responsibilities:

• Successfully partner and lead large offshore resources in solving complex business needs.

• Lead engineering teams in delivering AI-powered features and platforms, including LLM-based applications, RAG systems, and intelligent workflows.

• Perform reviews to ensure enterprise and architectural standards and processes are followed.

• Complete management responsibilities to include performance management, hiring and coaching of staff, and resource planning.

• Provide technical guidance and architectural oversight, particularly in the design of scalable AI-enabled systems.

• Manage system and user acceptance testing cycles to ensure accurate and quality business solutions.

• Lead the development of technical standards, and perform reviews to ensure enterprise and architectural standards and processes are followed.

• Establish best practices for AI system development, including prompt design, evaluation, monitoring, and responsible AI usage.

• Serve as a primary technical point of contact for external technology resources.

• Recommend technical strategy and direction across functional area.

• Drive AI strategy adoption within the team, identifying opportunities to leverage generative AI to improve products and internal productivity.

• Participate in development and evolution of architecture.

• Consult with stakeholders to find alternative work-arounds during system outages.

• Provide design input across a product.

• Work directly with customers and end users.

• Serve as acknowledged “go to” person on coding and technical issues.

• Interface with other technical personnel or team members to finalize requirements.

• Write and review portions of detailed specifications for the development of system components of moderate complexity.

• Complete complex bug fixes.

• Translate business problems into scalable AI/automation solutions.

• Design and work with complex data models.

• Seek diverse ideas and perspectives from a variety of sources to create better solutions, products, and services.

• 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.

• Foster a culture of experimentation and rapid prototyping in AI and emerging technologies.

• Manage and encourage new ideas from staff to foster improvements through innovations.

• Build and grow team capabilities in AI/LLM development through hiring, mentoring, and upskilling.