AI Engineer (LLM)

TL;DR

AI Engineer (LLM): Developing and owning the prompts, agents, and evaluation pipelines for user-facing AI features within a productivity analysis platform with an accent on production-grade reliability and output quality. Focus on designing rigorous evaluation systems, optimizing LLM orchestration, and translating complex product requirements into scalable AI agents.

Location: On-site in San Francisco, CA (5 days a week). E-3 sponsorship available for Australians to relocate.

Salary: $180,000 – $250,000

Company

hirify.global builds a platform that captures how work happens inside large organizations to measure productivity, check process conformance, and analyze where AI can automate work.

What you will do

• Build and own end-to-end AI features, from initial prototype to production.
• Optimize AI output quality via prompt engineering, model selection, and retrieval strategies.
• Design and implement rigorous evaluation systems to measure real-world output and catch regressions.
• Iterate on agent designs and orchestration patterns to ensure reliability and stability.
• Collaborate with Product and AI Platform teams to integrate features into solid infrastructure.
• Evaluate and integrate new models and tools to improve latency, cost, and quality.

Requirements

• Hands-on experience shipping LLM-powered features to production users.
• Strong production engineering skills in TypeScript/Node (AWS Lambda) and/or Python.
• Practical expertise in prompt engineering, retrieval, and agent design.
• Proven track record of building effective AI evaluation systems.
• Solid software engineering fundamentals and ability to write production-ready code.
• Experience with LLM providers such as Anthropic, OpenAI, Google Vertex, or AWS Bedrock.

Nice to have

• Background in ML, NLP, or applied research.
• Experience with pgvector or other vector retrieval systems.
• Experience with post-training or fine-tuning of models.
• Proficiency with Anyscale Ray or distributed compute frameworks for batch inference.
• Open source contributions to LLM or agent tooling.

Culture & Benefits

• Early-stage, fast-paced environment with a focus on rapid iteration.
• Equity (ESOP) and competitive base salary.
• $1,000 monthly food and commuting allowance.
• Laptop of choice.
• Support for diverse backgrounds and inclusive team culture.

Hiring process

• Resume screening.
• 1:1 interview with the founder.
• Technical deep-dive into past AI engineering work.
• Collaborative problem-solving session with the team.