Manager, Analytics Software Engineering (AI)

Location: Morrisville, North Carolina, United States; hybrid work with in-office and in-person expectations

Salary: $170,000–$220,000 per year, with comprehensive benefits and performance-based incentives.

Company

hirify.global provides intelligent data infrastructure, unified storage, integrated data services, and enterprise solutions across major cloud platforms.

What you will do

• Lead globally distributed software engineering, data science, and technical leadership teams.
• Guide architecture, resolve critical technical issues, and unblock teams as a hands-on player-coach.
• Promote responsible use of machine learning, Generative AI, agents, recommendation systems, and predictive models.
• Own execution and operational health for strategic products, shared platforms, and technical workstreams.
• Translate priorities into outcome-based roadmaps with milestones, dependencies, risks, and success measures.
• Partner with product, architecture, data, program, analytics, and business leaders on strategy and measurable outcomes.

Requirements

• Bachelor’s or master’s degree in computer science, engineering, data science, or a related field, or equivalent practical experience.
• 8+ years of experience in software engineering, data platforms, data science, or related disciplines, including 4+ years managing cross-functional technical teams.
• Experience leading globally distributed teams across time zones with clear ownership and reliable delivery.
• Experience delivering enterprise-scale, data-intensive, or AI-enabled products from concept through production.
• Strong understanding of software architecture, APIs, data pipelines, cloud platforms, and production operations.
• Working knowledge of machine learning, predictive modeling, Generative AI, and the deployment, monitoring, and governance of AI-enabled solutions.

Nice to have

• Experience with Python, C#, .NET, SQL Server, Azure Data Factory, Azure Databricks, Spark, or Power BI.
• Experience with modern data architectures, microservices, cloud-native applications, and large-scale structured and unstructured data.
• Familiarity with Azure OpenAI, LLMs, RAG, AI agents, vector databases, MLOps, model monitoring, and responsible AI.
• Knowledge of DevOps, CI/CD, automated testing, observability, and production operations.

Culture & Benefits

• Hybrid working environment focused on connection, collaboration, and culture.
• Health insurance, life insurance, retirement or pension plans, paid time off, and leave options may be included.
• Performance-based incentives, employee stock purchase plans, and restricted stock units may be available.
• Flexible environment supporting work-life balance, initiative, impact, and ownership.
• Benefits vary by country and region and are subject to local laws and company policies.

Hiring process

• Applications are reviewed only when submitted through the company website.
• Some stages of the hiring process may use AI tools to support application evaluation and candidate selection.