Senior Engineering Manager, Data & AI

Location: Remote, United States. Some travel is required for team onsites, customer visits, and industry events. Relocation assistance is not provided.

Company

hirify.global is building an AI-powered, cloud-native operating system for modern freight, combining dispatch, driver mobile, compliance, billing, settlements, EDI, reporting, integrations, and automation in one product.

What you will do

• Lead, coach, and grow an engineering team of about eight engineers, including senior engineers and tech leads.
• Set technical strategy across Foundry, Insights, Intel, Voice, the context graph, and the shared data platform.
• Own the agent lifecycle from prototyping through production and continuous improvement, including self-learning loops and release-gating evaluations.
• Build trustworthy data foundations using event streams, CDC, Snowflake, data quality, lineage, entity resolution, and decision traces.
• Design secure, auditable, tenant-isolated agents with scoped permissions, human approvals, least privilege, and protection against prompt injection and tool misuse.
• Remain hands-on for about one-third of the time by prototyping, writing evaluations, reading traces, debugging production, and reviewing architecture and code.

Requirements

• 8+ years building software, including 3+ years managing engineers, with experience growing senior engineers and tech leads while remaining hands-on.
• Production experience shipping LLM-powered products to real users, including explaining failures, measurements, and corrective changes.
• Daily use of coding agents and demonstrated production experience with multi-agent workflows, contracts, hooks, loops, and verification checks.
• Experience with tool use, function calling, MCP, orchestration, memory, retrieval, and agent failure modes.
• Experience building evaluation systems combining offline suites, online metrics, human review, and transcript analysis to gate releases.
• Strong data engineering judgment involving event streams, CDC, cloud warehouses, dbt, and data quality.
• Experience designing and operating distributed production systems with real reliability requirements.
• Experience securing multi-tenant SaaS and isolating customer data, treating agent permissions as a security boundary.
• Fluency in Python or TypeScript and comfort reading C#, F#, and .NET; experience with F# or another functional language is a plus.
• Experience operating at Series B/C velocity amid ambiguity, limited support, competing priorities, and a bias toward shipping and learning.
• Ability to explain technical tradeoffs to engineers, customers, and executives.

Nice to have

• Production experience with knowledge graphs, context graphs, entity resolution, or GraphRAG.
• Experience with real-time voice agents, telephony, speech-to-text, text-to-speech, turn-taking, and latency budgets.
• Experience with fine-tuning, reinforcement learning from feedback, or prompt optimization against evaluation sets.
• Experience with embedded automation or workflow platforms such as Activepieces, n8n, or Temporal.
• SRE experience or a record of running systems other teams depend on.
• Logistics, freight, or another operations-intensive industry experience.
• Founder or early-stage engineering leadership experience and a history of hiring, growing, and retaining excellent engineers.

Culture & Benefits

• AI-first engineering practices emphasize independent verification, human accountability, measurable precision, and production evidence over demos.
• Security-first design uses approved infrastructure, managed identity, least privilege, tenant isolation, audit trails, and bounded costs.
• Engineers work directly with customers and Forward Deployed Engineering to turn repeated operational patterns into platform features.
• The role offers frontier AI work on a proprietary freight dataset and a portfolio spanning four products on one shared platform.
• Some travel is required for team onsites, customer visits, and industry events; the role is remote within the United States.