AI Engineer

Location: US-based hybrid position with a coworking space provided in the Boston, MA area. Limited travel of approximately 10% or less may be required, including occasional travel to Connecticut and less frequent travel to Tempe, Arizona. A valid driver’s license, automobile insurance, and a clean driving record for at least the preceding 39 months are required.

Base pay: $129,339–$200,000 per year, with potential incentive, commission, or annual bonus pay.

Company

hirify.global provides digital-first K–12 curriculum solutions and develops Curriculum-Informed AI technology to help educators personalize instruction.

What you will do

• Prototype AI applications and agentic workflows using model APIs, tool calling, retrieval, structured outputs, and state management.
• Compare models and architectures, applying fine-tuning or other model adaptation when evaluation supports it.
• Build evaluation datasets, automated checks, and human review workflows to measure quality, robustness, and regressions.
• Diagnose failures through traces and error analysis, improving grounding, tool reliability, context handling, and recovery from unexpected outputs.
• Design sandboxed execution with least-privilege access, network and filesystem restrictions, secrets protection, resource limits, output validation, and auditable execution.
• Measure latency, throughput, and inference costs; test emerging techniques and collaborate with application engineers, learning researchers, and security partners.

Requirements

• Bachelor’s degree in computer science, engineering, or a related field and at least 5 years of software or machine learning engineering experience, or an acceptable combination of education and experience.
• Hands-on experience building LLM applications with tool use, retrieval, structured outputs, and evaluation, including the ability to explain failures and improvements.
• Strong Python or TypeScript skills and experience with APIs, asynchronous code, data models, testing, cloud services, and debugging across system boundaries.
• Practical understanding of sandboxing, isolation, access controls, secrets management, and security risks in agentic systems.

Nice to have

• Experience with multimodal or voice AI, agent orchestration, model adaptation, or evaluation infrastructure.
• Active experimentation with emerging AI methods.
• Experience with agentic toolkits or frameworks such as Deep Agents, LangChain, LangGraph, OpenClaw, Hermes, or comparable tools.

Culture & Benefits

• Small, entrepreneurial, co-located R&D team focused on experimentation, rapid learning, and collaboration.
• Flexible work arrangements and work-from-home opportunities supporting work/life balance.
• Health, dental, and vision plans, including medical plans with zero employee premiums.
• 401(k) with company match, paid holidays, paid time off, winter shutdown, and paid bonding leave.
• Maternity, fertility, and family-building benefits; mental health resources; life and disability insurance; and pre-tax savings plans.
• Professional development programs, tuition reimbursement, and paid volunteer time off.