Senior Software Engineer, Applied AI
New
J
JobgetherApplied AI
Fully remote work across the United States and CanadaFull-TimeSenior
SalaryTarget total cash compensation of $298,000–$358,000 per year. Base salary: Annual base salary ranging from $240,000 to $300,000, depending on experience and the level demonstrated during the interview process. Annual performance bonus: A cash bonus of $58,000 when the company achieves its annual revenue goal, with potential upside of up to $116,000 if the goal is exceeded.
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Job Details
- Experience
- At least five years of professional experience in software engineering or a closely related technical role; at least two years of experience building products or systems powered by large language models (LLMs).
- Required Skills
- Software Engineering
Requirements
- At least five years of professional experience in software engineering or a closely related technical role.
- At least two years of experience building products or systems powered by large language models (LLMs).
- Demonstrated experience taking at least one AI agent into production and continuing to own and improve it.
- Strong coding proficiency with AI development tools such as Claude Code or Codex.
- Experience designing and incorporating evaluations throughout the development lifecycle, including defining success criteria and measurement methods.
- Track record of taking projects from concept through implementation and deployment, resolving ambiguity independently.
- Ability to assess business needs, make technical trade-offs, prioritize, and explain why features or solutions should not be pursued.
- Ability to work directly with non-engineering teams to understand workflows and translate business needs into practical AI solutions.
- Comfort adapting approaches in a rapidly evolving technical landscape where established best practices may not yet exist.
- Ability to design scalable, reusable solutions that support continuous workflow improvement.
Responsibilities
- Design, develop, and deploy AI agents, reusable skills, and foundational AI capabilities across business functions.
- Own implementation from identifying use cases and designing solutions through coding, evaluation, deployment, and internal adoption.
- Write technical specifications, evaluation criteria, and test cases that define measurable success for AI-powered workflows.
- Integrate evaluations into development, measure agent performance, identify weaknesses, and refine systems based on evidence.
- Work with sales, revenue operations, editorial, and people operations stakeholders to identify workflow automation opportunities.
- Partner with the Applied AI Product Manager to prioritize initiatives and make product and implementation decisions.
- Build systems that take advantage of improving model capabilities and reduce repeated manual redesign.
- Help teams shift from manual task execution to defining specifications, quality benchmarks, and supervision of AI-driven workflows.
- Measure practical improvements in productivity, quality, and operational efficiency.
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