Senior AI Engineer (AI)

Location: Remote across the United States and Canada. Candidates in Toronto or New York City may use the office on a hybrid schedule. Travel for off-sites and team gatherings may be required up to once per quarter.

Base salary: USD $150,000–$185,000 for candidates in the United States; CAD $130,000–$165,000 for candidates in Canada.

Company

hirify.global is a SaaS and AI technology company building workforce-development products that help people find better jobs and support agencies, governments, and employers.

What you will do

• Design, build, and ship production LLM experiences, including conversational coaching, agentic workflows, tool use, function calling, retrieval, and orchestration.
• Develop evidence-based coaching and career-pathway products that recommend the next best step for job seekers.
• Analyze labor-market transitions and workforce interventions, including causal effects on wages and lifetime earnings.
• Build evaluation harnesses, quality metrics, regression tracking, and human-in-the-loop review processes for AI systems.
• Develop predictive, classification, ranking, and recommendation models when they are appropriate for the product.
• Build trusted data pipelines and integrate AI systems with internal tools, databases, SaaS platforms, case-management systems, and enterprise workflows.

Requirements

• Approximately 5+ years of applied ML or AI engineering experience shipping systems used by real people.
• Production experience with LLM products, prompt engineering, agentic workflows, tool use, retrieval, and orchestration.
• Strong evaluation discipline, including open-ended quality metrics, regression detection, and human review.
• Hands-on experience with classical machine learning, predictive models, or classification models.
• Production fluency in Python and SQL, plus experience with data pipelines, labeling, knowledge sources, governance, APIs, databases, and external integrations.
• Sound judgment around safety and guardrails in benefits, eligibility, and career-decision products, with the ability to explain technical tradeoffs to non-technical audiences.

Nice to have

• Experience with AWS, SageMaker, RAG at production scale, recommender systems, ranking, or search.
• Experience with jobs-and-skills, HR, labor-market, government, public-sector, O*NET, or ESCO data.
• Knowledge of labor economics, program evaluation, or workforce-intervention measurement.
• Publications, talks, blog posts, or open-source work demonstrating AI or ML engineering depth.

Culture & Benefits

• High-velocity, high-trust, high-impact environment with significant ownership and technical influence.
• Close collaboration with Engineering, Product, and the VP of Data & AI.
• Remote work across the United States and Canada, with optional office access in Toronto and New York City.
• Opportunity to shape AI platform practices, evaluation standards, prompting patterns, and agent safety policies.
• Values include curiosity, outcome focus, continuous improvement, speed, ownership, and teamwork.

Hiring process

• Online application and recruiter screen.
• Hiring-manager interview, performance challenge, and final one-to-one interviews.
• The process generally takes around six weeks.