[Hiring] Senior Engineering Manager, Data & AI @Alvys

Role Description

Lead the engineering team behind Foundry, Insights, Intel, and Voice: the agents, analytics, and data intelligence of the modern freight platform.

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

The Senior Engineering Manager, Data & AI leads the engineering group behind Foundry, Insights, Intel, and Voice. You'll own the group's technical strategy, delivery, and quality, hire and develop its engineers, and stay hands-on by prototyping, writing evals, reading traces, and reviewing architecture in depth.

• The team is about eight engineers today and growing.
• It owns the shared foundation those products run on: a context graph that connects loads, trips, carriers, drivers, customers, documents, and conversations; event-sourced platform data streaming into the warehouse; and the evals, tracing, guardrails, and model routing every agent depends on.
• Alvys facilitates more than $1 billion in funds every month across invoices, carrier payments, and driver settlements.
• This team turns it into agents that do real work and intelligence customers can't get anywhere else.
• Expect to spend about a third of your time building.
• You'll set the standard for how an AI-first team works: coding agents in the daily workflow, evals before scale, and production evidence over demos.
• The platform runs on .NET (C#, and increasingly F#), TypeScript, and Python on Azure and AKS, with Cosmos DB, Postgres, Elasticsearch, Snowflake, dbt, and Fivetran underneath.

Qualifications

• 8+ years building software, including 3+ years managing engineers.
• You've grown senior engineers and tech leads and remain a hands-on builder who can prototype, debug production, and review code credibly.
• Production LLM systems.
• You've shipped LLM-powered products to real users, not demos, and can explain what broke, what you measured, and what you changed.
• Agentic engineering in your own work.
• You've built with coding agents every day and can show the multi-agent workflows, contracts, hooks, and loops you put into production, and the checks that kept them honest.
• Depth in agent systems.
• You've built with tool use, function calling, MCP, orchestration, memory, and retrieval, and you understand where agents fail.
• Evaluation discipline.
• You've built eval systems that combine offline suites, online metrics, human review, and transcript analysis, and used them to gate releases.
• Strong data engineering judgment.
• You've worked with event streams, CDC, cloud warehouses, dbt, and data quality, and you know how the shape of the data limits what models can do.
• Distributed systems in production.
• You've designed and operated production services with real reliability requirements.
• Multi-tenant security.
• You've secured multi-tenant SaaS and isolated customer data, and you treat agent permissions as a security boundary.
• Language fluency.
• You write Python or TypeScript fluently and are comfortable reading C#, F#, and .NET. Experience with F# or another functional language is a plus.
• Startup-stage fit.
• You've operated at Series B/C velocity amid ambiguity, thin support, competing priorities, and a bias toward shipping and learning.
• Clear technical communication.
• You can explain a tradeoff to an engineer, a customer, and an executive.

Requirements

• Manage, coach, and develop a team of about eight engineers, including senior engineers and tech leads, and grow it as the portfolio expands.
• Hire senior and staff engineers, and keep the quality bar high as the team scales.
• Run the team AI-first, with coding agents in the daily workflow and clear standards for how AI-written code is reviewed, tested, and shipped.
• Set technical direction for agents, data, and the context graph, and make the build, buy, and model calls with cost, quality, and speed in view.
• Make tradeoffs across four products that share one platform, including what gets built, what gets cut, and where the team invests.
• Own the agent development lifecycle from prototype to production to continuous improvement.
• Build self-learning loops so agents improve from outcomes, user corrections, and transcripts, and make that improvement measurable.
• Make evals a release gate. No agent ships without tests for quality, safety, latency, and cost.
• Own the context graph that links loads, trips, carriers, drivers, customers, documents, and conversations, and the entity resolution that keeps it trustworthy.
• Partner on the data platform that feeds it, including event streams, CDC into Snowflake, data quality, and lineage, so agents and analytics share one source of truth.
• Capture decision traces so precedent becomes searchable for agents and people, while rules stay explicit.
• Design agents that change data with scoped permissions, human approvals, and audit trails, and defend against prompt injection and tool misuse.
• Enforce tenant isolation and least privilege across every agent, tool, and data path.
• Own reliability and unit economics. Track cost per task, per call, and per tenant, and keep margins healthy as usage grows.
• Spend about a third of your time building: prototype, write evals, read traces, and debug production.
• Work as a peer to product and design leadership on direction, architecture, sequencing, and delivery.
• Work directly with customers and our Forward Deployed Engineering team, and turn repeated patterns into platform features.

Benefits

• Competitive salary and equity options.
• Flexible work environment.
• Health, dental, and vision insurance.
• Generous PTO policy.
• Professional development opportunities.

Company Description

Alvys is building the operating system for modern freight. Our AI-powered, cloud-native platform brings dispatch, driver mobile, safety and compliance, billing and settlements, native EDI, reporting, integrations, and automation into one product.

• Founded in 2020 by freight industry insiders.
• More than 3,000 trucking and brokerage companies use Alvys today.
• Raised $77M to date, including a $40M Series B.
• Building a modern interface for a traditional TMS.