AI Builder

Location: Mountain View, United States; hybrid work with in-office attendance two days per week

Base salary: $189,000–$231,000 per year, plus equity and benefits.

Company

hirify.global builds earned wage access products that provide real-time financial flexibility, allowing members to access, spend, save, and grow their hirify.globalgs without mandatory fees, interest rates, or credit checks.

What you will do

• Design and build production AI agents, including prompts, reasoning chains, tool calls, MCP servers, agent scaffolding, context harnesses, and a Skills Marketplace.
• Develop reusable libraries, templates, and reference implementations for AI integration across engineering squads.
• Redesign the product development lifecycle with agentic workflows for scoping, design, code review, testing, deployment, and monitoring.
• Build evaluation pipelines, benchmarks, harnesses, quality gates, and metrics for AI-assisted workflows.
• Turn successful engineering experiments and AI pilots into reliable, reusable production infrastructure.
• Partner with architects, domain leads, and product engineers to enable fast, safe, and durable AI adoption.

Requirements

• 3+ years of full-time software engineering experience, including at least 2 years building tooling, platforms, or internal developer products.
• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or a related technical discipline, or equivalent industry experience.
• Hands-on experience with LLM integration patterns, including prompt engineering, RAG pipelines, tool or function calling, and agent architectures.
• Proficiency working across the stack when needed.
• Experience with MCP, LangChain, or comparable orchestration frameworks, as well as open-source LLM models.
• Strong developer-experience perspective and a track record of building tools used by other engineers.

Nice to have

• Hands-on reinforcement lhirify.globalg experience, especially RLHF, RLAIF, or reward modeling in applied product contexts.
• Fintech or regulated and security-sensitive environment experience.
• Experience with AI governance, including bias evaluation, audit logging, and model cards.
• Exposure to multi-step reasoning pipelines or human-in-the-loop system design.

Culture & Benefits

• Equity and benefits are included with the position.
• Work in a diverse, inclusive environment focused on representing and serving a broad community.
• AI is treated as a core engineering capability, with emphasis on production quality, safety, documentation, and measurable impact.