Sr. Director, AI Engineering & Platform

Salary: $68,000 - 108,000 per year Requirements: We require current experience delivering production AI systems, including agentic architectures, multi-agent orchestration, tool use and protocols such as MCP, large-scale retrieval-augmented generation, model serving, and evaluation methods for reliable probabilistic systems. The leader must be able to review complex implementation work and understand where low-code platforms and emerging agentic systems add value. We require a strong software engineering foundation, including distributed and event-driven systems, API design, cloud-native infrastructure, containers, orchestration, infrastructure-as-code, and CI/CD. The leader must have expert command of at least one production programming language, commonly Python, and understand the trade-offs affecting scale, latency, and cost. We require experience taking AI or ML platforms from architecture through enterprise-scale production and operating systems relied on daily by engineers and users, with appropriate reliability, observability, and security. We require deep AI/MLOps and lifecycle expertise, including model and prompt versioning, automated evaluation and regression testing, monitoring and drift detection, and release practices such as canaries, rollback, and governance gates. We require experience with AI-specific security and risk, including threat modeling for prompt injection, data leakage, and agent action control, and embedding controls into platforms. We require Director-level or higher engineering leadership experience, including prior Senior Director or equivalent scope, software engineering experience, and expertise developing AI and ML engineering talent. The leader must have led engineers, architects, and engineering leaders, and owned build-versus-buy and vendor decisions evaluated against measured value in a fast-moving market. We require permanent authorization to work in the United States for any employer without requiring a visa transfer or visa sponsorship now or in the future. We prefer experience establishing an AI platform or Agent Factory-style delivery engine from a low-maturity starting point, primarily using internal talent. We prefer hands-on experience with technologies such as AWS Bedrock and AgentCore, Snowflake Cortex and Streamlit, Anthropic Claude, Microsoft 365 PowerApps or Copilot Studio, and Git-based engineering workflows. We prefer experience across multiple providers, including practical knowledge of portability, routing, and resilience against vendor lock-in. We prefer advanced agent evaluation and reuse practices, such as evaluation-set design, judge models, red-teaming, statistical rigor, and reusable components including shared tools and skills. We prefer a record of productizing internal AI for high-value outcomes in enterprise employee and operations use, including leadership in digital transformation. We prefer a record of increasing organizational fluency and adoption of a platform, not merely its spending. Responsibilities: We expect this leader to build, mentor, and develop Agent Factory engineering leaders and developers, allocate work according to comparative advantage, and establish clear timelines and accountabilities. We expect this leader to own our AI platform end to end, including architecture, engineering, AI/MLOps, agent tooling, and operations, and to promote reusable reference architecture across use cases. Our named technologies include Snowflake, M365 PowerApps and Copilot Studio, Claude, and AWS AgentCore. We expect this leader to set technology direction and make build-versus-buy and runtime decisions across the approved stack, assess switching costs and lock-in, experiment before committing, and develop knowledge through engagement with providers and partners. We expect this leader to establish architecture and standards that move prototypes into production and maintain reliable, monitored, evaluated systems with dependable and accurate AI output. We expect this leader to manage platform economics with Finance, including FinOps for consumption-priced services, cost centers, per-user and tier thresholds, and anomaly alerts that connect spending to value. We expect this leader to own AI risk with Legal, Security, Infrastructure, and Compliance, covering tool approval, vendor security, and regulatory readiness while aligning AI controls with our enterprise security posture. We expect this leader to advocate for the platform across our organization, publish its roadmap, build organizational fluency, and report adoption and business value. Technologies: AI API AWS CI/CD Cloud Copilot Git MCP Microsoft 365 MLOps Model Serving Python Security Snowflake Office 365 More: We are Infor, and hackajob is collaborating with us to connect us with candidates for this Senior Director, AI Engineering & Platform role. The position leads the platform and engineering practice that bring our internal AI into production; its scope is AI for Infor employees and operations, not customer-facing product AI. The leader runs our Agent Factory and is accountable for developing talent, setting technical standards, and delivering production outcomes. Our Data & AI capability within Infor IT brings together Trusted Data Products, AI Engineering & Platform, and Analysis & Engagement. We emphasize economic thinking, strategic investment, allocating talent effectively, and shipping outcomes rather than presentations. We are investing in and scaling this capability through 2026 and beyond. The platform team is responsible for enabling agents and solutions to reach production responsibly, with reusable architecture and practical operating frameworks. last updated 41 week of 2026