Forward Deployed Engineer, Applied AI

Snowplow•,

About The Position

Snowplow is hiring its first Forward Deployed Engineer on the Applied AI team to help transform the company’s recurring work with AI-native workflows. Reporting to the Senior Director of Applied AI, you will embed with one business function at a time, work with its leader and team members to understand how work is performed, build agentic workflows, tune them with domain experts, and hand them over so the function can operate and evolve them independently. You will map workflows, assess whether they are appropriate for agent automation, and build on Snowplow’s shared factory framework. This includes defining approval gates and audit records, making the function’s knowledge and quality standards usable by agents, and improving prototypes for reliability and adoption. You will also document and refine the approach so future engagements and shared framework implementations can build on it. The role combines hands-on engineering with discovery, stakeholder communication, and change enablement. Engagement priorities may shift as the company’s transformation progresses.

Requirements

Fluency in at least one of Python, TypeScript, or Go, with the ability to pick up other languages as needed.
Experience shipping software in another organization’s or team’s codebase, dataset, or business system and becoming productive quickly.
Experience building and operating LLM-based agents or agentic workflows in production, including prompts, tools, evaluation, and failure handling.
An AI-native workflow, automation, or agent that you built and still use, which you can demonstrate during interviews.
Ability to work with non-engineers, listen actively, and uncover both documented and undocumented work processes.
Self-direction and ability to work through ambiguity, time-boxed engagements, and changing business priorities.
A preference for handing off durable capabilities rather than becoming an ongoing dependency for a team.
Low ego and willingness to replace or retire your own work when a better approach emerges.
Ability to explain changes clearly to senior stakeholders and advocate for an engineering pattern when appropriate.
Experience in a forward deployed, solutions engineering, internal tools, or consulting engineering role, or experience transforming a process end to end within a company.

Responsibilities

Map how a business function’s work operates, including inputs, steps, approvals, and quality criteria.
Use evidence from workflow discovery to recommend whether a workflow should be moved onto agents, including when AI is not needed.
Design and build agentic workflows on Snowplow’s shared factory framework.
Define where agents can act autonomously, where human approval is required, and what activity must be recorded.
Make the function’s knowledge, systems of record, and quality standards explicit and usable by agents.
Improve workflow reliability, handle edge cases, evaluate output, and work with domain experts to encode their judgment into checks.
Train the function to operate and evolve the workflows, then hand them off to the function or an embedded Applied AI engineer.
Remain available after handoff and coordinate workflow issues or improvements with embedded and platform engineers.
Document the workflow-to-handoff approach and contribute reference implementations to the shared framework.
Communicate with function leaders and other stakeholders about workflow changes and the engineering pattern.