Manager, Software Engineering - AI Tools

Manager, Software Engineering 

Remote - work virtually from anywhere in the United States 

Director, Software Engineering 

AI2IO is seeking a Manager, Software Engineering to lead the people, capability, and operating environment behind a growing AI platform and agent ecosystem serving architecture, engineering, construction, commissioning, design, proposal, and related business workflows. The team is building governed AI agents, semantic and knowledge-graph capabilities, retrieval and data pipelines, and shared platform services informed by data available within the QCS Ecosystem. 

This is a formal people-management role for all engineers and AI Engineer Technical Leads on the AI Tools team. Candidates must bring demonstrated professional experience leading, managing, architecting, or delivering production AI or LLM platforms or applications, with broad credibility and demonstrated depth across several relevant AI disciplines. The role develops people, builds workforce capability, improves team clarity, and helps translate strategy and architecture into context the team and broader organization can understand without replacing Technical Lead, architecture, product, analysis, or delivery authority. 

This role grows from complete ownership of people leadership and the AI Tools delivery environment toward broader workforce strategy, specialized capability development, management-system improvement, and organizational leadership across a maturing AI engineering function. As the organization grows, expand impact through multi-team capability planning, development of technical and people leaders, management-system improvement, workforce strategy, and resolution of organizational challenges beyond the assigned specialty. 

• Direct reports understand expectations, receive timely feedback, and have credible development plans aligned with software-engineering and specialized AI capability needs. 

• The team has sufficient staffing, role clarity, technical leadership, training, and organizational support to deliver and operate the AI platform sustainably. 

• Strategic and architectural direction becomes understandable objectives, context, risks, dependencies, and intake-ready work without displacing Product Owner, Business Analyst, AI Engineer Technical Lead, architecture, or Project Manager authority. 

• AI Engineer Technical Leads retain technical authority and receive effective management partnership rather than tactical micromanagement. 

• Responsible AI, data governance, evaluation, access, observability, knowledge quality, and production-readiness initiatives have visible ownership, staffing, training, and progress. 

• Key-person risks in agent architecture, semantic engineering, knowledge graphs, data science, governance, and platform operations are reduced. 

• Engineers outside the specialty and leaders receive clear explanations of AI Tools work, tradeoffs, risks, and outcomes. 

• Management practices remain consistent with the broader Software Engineering organization while adapting to experimentation, research uncertainty, and production AI operations. 

• Demonstrated professional experience leading, managing, architecting, or delivering production AI or LLM platforms or applications, with credible fluency across several of the following: agent systems, semantic engineering, retrieval, data science, data engineering, data governance, knowledge graphs, evaluation, responsible AI, and production AI operations. 

• Demonstrated ability to translate complex technical or architectural direction into organizational context, capability needs, risks, dependencies, and actionable team understanding. 

• Experience managing performance, difficult feedback, recognition, development, reviews, promotions, and sustained performance concerns. 

• Experience managing engineers and technical leaders while preserving clear authority for AI Engineer Technical Leads, Architects, Product Owners, Business Analysts, and Project Managers. 

• Experience with workforce planning, hiring, skill-gap assessment, onboarding, retention, succession, and staffing recommendations for specialized teams. 

• Sufficient software-engineering foundation to assess application architecture, APIs, data, identity, security, testing, CI/CD, observability, dependency, delivery, support, and operational risk without directing implementation. 

• Experience supporting responsible AI, data-governance, access-control, evaluation, observability, or model-risk practices in a growing organization. 

• Ability to communicate complex AI and data concepts to AI specialists, mainstream software teams, product and delivery partners, and leadership. 

• Experience managing distributed or remote teams and improving team practices, documentation, and leadership continuity. 

• Excellent interpersonal, written, verbal, coaching, facilitation, conflict-resolution, and organizational judgment. 

• Experience managing teams that build production AI platforms, agent frameworks, knowledge graphs, semantic layers, retrieval systems, or AI-enabled enterprise applications. 

• Hands-on background in AI architecture, LLM application development, data science, data engineering, ontology or taxonomy design, graph technologies, or semantic engineering. 

• Experience with Azure AI Foundry, Azure OpenAI, Semantic Kernel, Azure AI Search, Python agent frameworks, Microsoft Azure, C#/.NET, or adjacent enterprise AI platforms. 

• Experience applying AI to AEC, commissioning, engineering design, proposal development, document-intensive workflows, or domain-specific business processes. 

• Experience developing Technical Leads, AI specialists, data professionals, or emerging technical leaders. 

• Relevant management, coaching, Azure AI, data, architecture, Agile, or project-management certifications. 

• Up to 5%, this may include travel to any or all 50 US states 

• Travel is defined as physically leaving home on behalf of business activities including but not limited to client sites, meetings with other employees, meeting for business development purposes, running errands on behalf of the business, attending industry conferences, etc. 

• 8+ years of professional software engineering, AI engineering, data engineering, data science, or closely related technical-delivery experience, including at least 2 years of formal people management within a software or technology organization. 

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Systems, Electrical Engineering, Mathematics, or a materially related field, or equivalent experience preferred. 

• Lead a specialized engineering team building a governed AI platform and agents for real AEC, commissioning, design, proposal, and business workflows. 

• Work at the intersection of software engineering, AI applications, semantic systems, data science, knowledge graphs, and organizational enablement. 

• Help convert ambitious AI strategy into a capable, supported team with clear context, sustainable practices, and strong technical leadership. 

• Shape hiring, development, governance adoption, leadership continuity, and operating systems during an important growth stage. 

AI2IO does not accept unsolicited resumes from recruiters, employment agencies, or other staffing services. Unsolicited resumes include any resume or hiring document sent to AI2IO in the absence of a signed Service Agreement where AI2IO has expressly requested recruitment/staffing services specific to the position at hand. Any unsolicited resumes, including those submitted to hiring managers or other business leaders, will become the property of AI2IO and AI2IO will have the right to hire that candidate without reservation – no fee or other compensation will be owed or paid to the recruiter, employment agency, or other staffing service.