Manager, Software Engineering - AI Tools

DLB Associates

1d•Remote

About The Position

AI2IO is seeking a Manager, Software Engineering to lead the people, capability, and operating environment behind its 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. The manager develops people, builds workforce capability, improves team clarity, and translates strategy and architecture into context the team and broader organization can understand, without replacing technical lead, architecture, product, analysis, or delivery authority. The role begins with ownership of people leadership and the AI Tools delivery environment, then expands toward workforce strategy, specialized capability development, management-system improvement, and organizational leadership across a maturing AI engineering function. The manager supports sustainable delivery, responsible AI and data-governance practices, hiring and onboarding, leadership development, and clear, healthy team practices. The position is remote and may require travel of up to 5% to any or all U.S. states.

Requirements

Demonstrated professional experience leading, managing, architecting, or delivering production AI or LLM platforms or applications, with credible fluency across several relevant AI disciplines.
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 the authority of 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, dependencies, 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.
At least 8 years of professional software engineering, AI engineering, data engineering, data science, or closely related technical-delivery experience.
At least 2 years of formal people management within a software or technology organization.

Nice To Haves

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.
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.

Responsibilities

Manage and develop all engineers and Technical Leads assigned to the specialty team through one-on-ones, expectations, feedback, performance reviews, development planning, recognition, and appropriate handling of performance concerns.
Connect individual goals with assignments, coaching, learning, mentoring, and opportunities for increasing ownership.
Partner with Technical Leads on technical contribution and development needs while retaining accountability for career evaluation, formal performance decisions, employee relations, and team health.
Assess capacity, critical skills, experience distribution, key-person dependencies, succession risks, and staffing needs; coordinate learning, mentoring, hiring, and onboarding to address capability gaps.
Develop future Technical Leads and management candidates through scoped assignments, feedback, readiness criteria, and partnership with current leaders.
Ensure teams have sufficient staffing, capability, role clarity, decision pathways, tools, and organizational support for sustainable delivery.
Partner with Technical Leads and Project Managers on delivery health, risks, dependencies, capacity, and recovery without replacing their ownership; intervene on material delivery problems as appropriate.
Review delays, incidents, rework, quality concerns, support burdens, and workload imbalance to identify organizational or capability improvements, and protect teams from sustained overload.
Translate strategic and architectural direction into objectives, decision context, capability needs, dependencies, risks, and intake-ready work in partnership with relevant organizational stakeholders.
Participate in developer discussions and intake, help clarify requirements and stories without taking over product ownership or analysis, and help technical leaders explain architecture and implementation direction to non-AI engineers and leadership.
Improve tactical documentation, communication rhythms, and decision records while leaving architecture approval and technical decomposition to the appropriate leaders.
Own workforce capability, staffing, development, and training plans across AI application engineering, agents, semantic engineering, ontology and taxonomy, data science, knowledge graphs, retrieval, data pipelines, evaluation, responsible AI, governance, platform operations, and supporting software engineering.
Develop engineers across specialized AI concerns and the surrounding C#/.NET, Azure, API, identity, security, testing, CI/CD, observability, and production-support environment.
Reduce single-person dependencies in platform architecture, knowledge-graph pipelines, semantic models, agent workflows, data governance, and operations.
Champion responsible AI, data governance, access control, evaluation, observability, model-risk, knowledge-quality, and operational practices; ensure staffing, training, ownership, and escalation paths support these capabilities.
Partner with technical leaders and the Director, AI Strategy and Enablement to identify governance and platform risks requiring clearer ownership, specialist support, or investment.
Balance research and experimentation with documentation, production readiness, supportability, security, quality, cost awareness, and sustainable delivery.
Establish candid team practices for discussing risks, uncertainty, mistakes, disagreements, workload concerns, and alternative viewpoints; address conflict, overload, escalation failures, knowledge bottlenecks, and reluctance to surface delivery problems.
Lead workforce planning, role requirements, interview plans, evaluation criteria, hiring priorities, structured selection, interviewer calibration, candidate recommendations, and consistent onboarding.
Evaluate onboarding effectiveness, identify retention risks, and coordinate appropriate responses.
Maintain clear leadership boundaries with Technical Leads, Architects, Project Managers, Product Owners, and Business Analysts, providing management partnership without taking over their defined authority.
Improve performance management, career development, hiring, onboarding, workforce planning, team operating practices, and leadership continuity.
Identify cross-team patterns and contribute to department-level capability planning, organizational design, role definition, career frameworks, staffing, leadership development, and organizational change.
Evaluate whether adopted practices improve clarity, fairness, staffing effectiveness, internal growth, management consistency, and sustainability; represent capacity, capability, succession, and organizational risks in department planning.
Perform other related duties as assigned.

Benefits

Choice of comprehensive medical plans, including two PPO-style plans and a high-deductible health plan with HSA option.
Flexible spending accounts.
Dental and vision plans.
Medical, dental, and vision benefits extended to spouse or domestic partner and dependent children up to age 26.
401(k) with company match and self-directed brokerage account option.
Paid time off, including additional paid time off during the last week of the year.
Company-paid life insurance for employees and eligible dependents.
Short- and long-term disability and AD&D coverage.
Professional development opportunities, tuition reimbursement, and professional licensing assistance.
Paid parental leave after one year of employment.