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Tech Stack
Tools & technologiesAzurePython.NET
About the role
Key responsibilities & impact- Lead the people, capability, and operating environment behind AI2IO's growing AI platform and agent ecosystem
- Serve as formal people manager for all engineers and AI Engineer Technical Leads on the AI Tools team
- Conduct one-on-ones, set expectations, provide feedback, complete performance reviews, and plan professional development
- Build team capability through learning, pairing, assignments, mentoring, hiring, and onboarding
- Maintain visibility into capacity, critical skills, dependencies, succession risks, and staffing needs
- Ensure staffing, role clarity, decision pathways, tools, and organizational support enable sustainable delivery
- Partner with Technical Leads and Project Managers on delivery health, risks, dependencies, capacity, and recovery
- Translate AI strategy and architectural direction into objectives, context, capability needs, dependencies, risks, and intake-ready work
- Participate in developer discussions and intake across AI specialists, software engineers, delivery partners, and leadership
- Develop workforce capability across AI application engineering, agents, semantic engineering, ontology and taxonomy, data science, knowledge graphs, retrieval, data pipelines, evaluation, responsible AI, governance, platform operations, and software engineering
- Support responsible AI, data governance, access control, evaluation, observability, model-risk, knowledge-quality, and operational practices
- Establish healthy team practices for candid discussion of risks, uncertainty, mistakes, disagreements, workload concerns, and alternative viewpoints
- Lead hiring, structured selection, interviewer calibration, candidate recommendations, onboarding, and retention-risk responses
- Maintain clear boundaries with Technical Leads, Architects, Project Managers, Product Owners, and Business Analysts
- Improve performance management, career development, hiring, onboarding, workforce planning, team operating practices, and leadership continuity
- Contribute to department-level capability planning, organizational design, role definition, career frameworks, cross-team staffing, leadership development, and organizational change
Requirements
What you’ll need- Demonstrated professional experience leading, managing, architecting, or delivering production AI or LLM platforms or applications
- Credible fluency across 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
- Experience supporting responsible AI, data-governance, access-control, evaluation, observability, or model-risk practices
- Ability to communicate complex AI and data concepts to AI specialists, 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
- 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
- Bachelor's degree in a related field, or equivalent experience preferred
- Up to 5% travel, potentially to any or all 50 US states
Benefits
Comp & perks- Choice of comprehensive medical plans (including two PPO-style plans and a HDHP w/ HSA option)
- Flex spending accounts (FSA)
- Dental and vision plans
- Comprehensive medical, dental and vision benefits extended to spouse / domestic partner and dependent children up to age 26
- 401k with company match and self-directed brokerage account option
- PTO including additional paid time off during the last week of the year
- Company paid life insurance coverage for employees and their eligible dependents
- Short and long-term disability, AD&D coverage
- Professional development opportunities
- Tuition reimbursement and professional licensing assistance
- Paid parental leave after one year of employment