Forward Deployed Engineer, Applied AI

Job not on LinkedIn

🔥 12 hours ago

🍂 Massachusetts – Remote

🍂 Massachusetts – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

👻 Ghost score 12%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Snowplow

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2012

☁️ SaaS

🏢 Enterprise

💰 Venture Round - Snowplow on 2023-06

SaaS • Enterprise

Snowplow is the Customer Context Infrastructure that transforms raw behavioral data into real-time customer context for AI agents and advanced analytics. Data teams rely on Snowplow to collect and process event-level data in real time, delivering it to their warehouse, lake, or stream, without the engineering overhead of building data infrastructure. Product and engineering teams rely on it to power agentic AI systems, personalization, and fraud detection. Snowplow provides products like Data Foundation, Event Tracking, Data Pipeline, Event Studio, Profiles, Real-Time Triggers, Modeling & Analytics, ML & Agentic AI features (Agentic Context, Intent Detection, Proactive Decisioning). It integrates with many data platforms (Databricks, Snowflake, BigQuery, S3, Kafka, Clickhouse) and ML/agent frameworks (LangChain, AWS Bedrock, Vertex AI, Vercel). It targets industries like Games, Media & Entertainment, Retail & Ecommerce, Software, Financial Services and teams including Data Engineering, Product Analytics, Data Science, Marketing. Snowplow emphasizes real-time, validated, governed event-level data, open and transparent approach, privacy and compliance, and deployment options including self-hosted pipelines. It positions itself as enabling real-time customer context for AI agents and advanced analytics, replacing legacy analytics tools and in-house pipelines.

📋 Description

• Map business workflows by documenting inputs, steps, approvals, and quality standards • Evaluate whether workflows should be moved onto agents, including cases where AI is unnecessary • Design and build agentic workflows on Snowplow's shared factory framework • Define approval gates, autonomous actions, human approvals, and audit records • Make domain knowledge, systems of record, and quality standards explicit for agent use • Improve prototypes for reliability, edge cases, evaluation, and adoption • Tune outputs with domain experts and encode their judgment into checks • Train functions to operate and evolve the workflows, then hand them off • Coordinate post-handoff improvements with embedded and platform engineers • Develop and document repeatable workflow transformation patterns and reference implementations

🎯 Requirements

• Shipped real software in someone else's stack; comfortable with unfamiliar codebases, datasets, or business systems • Fluent in at least one of Python, TypeScript, or Go; able to learn the others as needed • Built LLMs/agents or agentic workflows in production, including prompts, tools, evaluation, and failure modes • AI-native workflow, automation, or agent built and still used; willingness to demonstrate it during interviews • Experience understanding undocumented processes by working with non-engineers • Self-direction and comfort with ambiguity • Clear communication with senior stakeholders • Experience in a forward deployed, solutions engineering, internal tools, or consulting engineering role, or end-to-end process transformation experience • Willingness to use AI during the application process and demonstrate work with AI on a real task

🏖️ Benefits

• Meaningful equity stake • Competitive Base Salary • Flexible working • Generous PTO • Medical, Dental & Vision Insurance • 401k • MacBook and home office equipment allowance • Enhanced Family leave

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