Applied AI Engineer (AI)

TL;DR

Applied AI Engineer (AI): Building and deploying enterprise-grade AI solutions and agents with an accent on LLM integration and production-grade system design. Focus on creating evaluation frameworks, optimizing agent quality, and scaling AI workflows for strategic customers.

Location: Menlo Park, CA, US. Must be able to travel at least 25% of the time.

Salary: $126K – $181.7K

Company

hirify.global is a cloud data platform empowering enterprises to unlock the power of AI and achieve their full potential through innovation and collaboration.

What you will do

• Architect, build, and deploy enterprise-grade AI solutions, including sophisticated AI agents.
• Define quality metrics, evaluation frameworks, and golden datasets to systematically improve agent accuracy and safety.
• Develop scalable and performant code and pipelines using Python and SQL.
• Manage the full implementation lifecycle from prototype to production, including monitoring and observability.
• Act as a hands-on technical advisor for strategic customer data science and engineering teams.
• Collaborate with Product and Engineering teams to influence the future of the hirify.global AI platform.

Requirements

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 3+ years of professional software engineering experience.
• Willingness to travel at least 25% of the time onsite with customers.
• Proven experience building applications using LLMs, specifically with RAG and agentic workflows.
• Hands-on experience defining quality metrics and running evaluations for LLM or agent systems.
• Excellent problem-solving and communication skills to articulate technical concepts to stakeholders.

Nice to have

• Experience with eval and observability tooling (e.g., Braintrust, LangSmith, Arize, Weave, Promptfoo).
• Expertise in failure-mode analysis for agent or RAG systems.
• Experience with the MLOps lifecycle in cloud environments (AWS, Azure, or GCP).
• Familiarity with core data science libraries such as pandas, numpy, or Snowpark.
• Prior experience in a customer-facing technical role (e.g., Solutions Architect, Sales Engineer).
• Startup experience.

Culture & Benefits

• Opportunity to work at the forefront of the enterprise AI revolution.
• Culture centered on impact, innovation, and low-ego collaboration.
• Exposure to strategic customers and cutting-edge AI technology.
• Dynamic, fast-moving environment with an experimental mindset.