Senior Software Engineer - AI Engineering

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

CAD 157K-207K From the posting source checked Jun 20, 2026

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

U.S. benchmark only; posted salary is not compared across countries or currencies.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Company

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Software Engineer - AI Engineering San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States In 1600, William Gilbert published De Magnete -the first systematic study of magnetism. He didn't just theorize; he built instruments, ran experiments, and shared what he learned so that others could go further. Three centuries later, those foundations helped power the modern world. At Mercury, we're making a deliberate, company-wide bet on AI. Frontier users are already pushing boundaries-building agents, automating workflows, moving fast. But they're doing it in silos. This role exists to change that: to take those scattered experiments and turn them into shared infrastructure, shared context, and shared capability. The goal is a multiplier effect-where the most ambitious AI work inside Mercury lifts the velocity of everyone else. What you'll do You'll join a team that has already started building Mercury's internal AI platform and enablement layer. Your work will be to extend, harden, and scale what's in motion , and to help partner teams adopt it. Extend the AI platform foundation - Build and evolve MCP servers that connect internal systems and data sources into a coherent interface for agents and engineers. - Expand and operate our LLM gateway infrastructure: routing, rate limiting, cost attribution, and observability across teams. - Turn early patterns into durable defaults: shared prompt libraries, guardrails, and policy-as-code so teams can move fast safely. Strengthen the shared company knowledge layer - Shape and maintain structured context artifacts-clean, reliable, agent-consumable-so LLMs working

Read the full description at job-boards.greenhouse.io. FewerJobs shows a preview and links to the original posting.