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AI Solutions Engineer (Forward Deployed Engineer)

AI Engineer Full-time Permanent US

Job details

$136K – $209K • Offers Equity • Offers Bonus Salary
US Eligibility
Not specified Experience
Full-time Employment

About this role

Role overview An AI Solutions Engineer, also described as a Forward Deployed Engineer, sits inside the engineering organization and acts as the technical bridge between AI capability and the rest of the business. The role partners directly with non-technical departments to discover workflows, ship automations, and mature them into durable AI-powered agents that deliver measurable value.

Responsibilities

- Shadow domain experts across departments to surface pain points, then design and ship minimum viable automations, scripts, and API integrations that mature into managed agents. - Define success metrics with stakeholders, track adoption and return on investment, and prioritize work based on feasibility, risk, and business value. - Build, evaluate, and operate AI workflows with evaluation frameworks, guardrails, observability tooling, and feedback loops. - Serve as an in-house authority on AI, helping non-technical teams get more out of the AI features already available inside their existing SaaS tools. - Mentor peers, build reusable documentation and training, and demo emerging AI capabilities to broaden internal adoption. - Contribute to hosted and local AI harness development by feeding back distilled problems and prototypes. - Benchmark model performance, tune prompts and token usage, manage API latency, and monitor operational costs. - Ensure that AI work across departments adheres to company policy on data privacy, security, and ethical use.

Requirements

- At least three years of professional software development experience with strong proficiency in Go or JavaScript, ideally both, and standard practices such as version control and testing. - Hands-on experience building applications with Large Language Models or managing AI-driven workflows, including agent design, skills, context, and memory. - Comfort working with APIs and Model Context Protocol interfaces for platforms such as Jira, GitHub, or Salesforce. - Ability to translate complex machine learning and engineering concepts into clear, business-friendly language. - Demonstrated record of analyzing business operations, shaping technical requirements from loosely defined problems, and prioritizing by return on investment. - High emotional intelligence, comfort working autonomously inside non-technical departments, and a collaborative rather than gatekeeping style.

Benefits and work setup

- Health, vision, and dental coverage. - Opportunity for equity ownership. - Life and AD&D insurance, short- and long-term disability coverage. - Employee Assistance Program and Employee Resource Groups. - Company outings and events. - Unlimited paid time off. - 401(k) plan with company match.

Skills detected in the listing

JavaScriptGoStakeholder ManagementMachine LearningLLM
Detected Sep 17, 2026
Last verified Sep 17, 2026

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