Mercury
Mercury~20d ago
$166,600 – $218,700/yr

Senior Software Engineer - AI Engineering

United States - San FranciscoRemotesenior
Data ScienceOtherSoftware EngineerSoftware Engineer AiSoftware Engineering
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Quick Summary

Key Responsibilities

routing, rate limiting, cost attribution, and observability across teams. Turn early patterns into durable defaults: shared prompt libraries, guardrails,

Technical Tools
Data ScienceOtherSoftware EngineerSoftware Engineer AiSoftware Engineering

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.

Responsibilities

~1 min read

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.

  • 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.
  • Shape and maintain structured context artifacts—clean, reliable, agent-consumable—so LLMs working in Mercury's systems can reason accurately about our domain.
  • Improve internal knowledge discoverability and retrieval so both humans and agents can quickly find accurate answers.
  • Partner with domain teams to standardize key sources of truth, and keep them fresh.
  • Build and refine sandbox environments and tooling that let engineers experiment with AI safely and at speed.
  • Create self-service scaffolding so non-engineers—PMs, ops, finance—can prototype and deploy AI-powered workflows with minimal hand-holding.
  • Build playgrounds and evaluation harnesses so internal AI agents can be tested and iterated in controlled environments before hitting production.

This list is illustrative. Priorities will shift as we learn; the right person will help choose the next highest-leverage work.

  • Has 5+ years of backend development experience in complex, production systems—you've built things that other engineers depended on.
  • Is fluent across programming languages and can navigate platform engineering, infrastructure, and developer tooling without needing a map.
  • Has hands-on experience building LLM-powered systems—RAG pipelines, agents, eval frameworks—and has shipped at least one of these to production.
  • Understands the real tradeoffs in AI deployments: cost modeling, observability, latency, and safety—not just the exciting parts.
  • Is high-agency and self-directed. You can operate effectively without tightly-defined scope, find the highest-leverage work, and get it done.
  • Communicates clearly across technical and non-technical audiences—you can explain what you built and why it matters.

The total rewards package at Mercury includes base salary, equity, and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

  • US employees (any location): $166,600 - $218,700
  • Canadian employees (any location): CAD 157,400 - 206,650

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024. 

[Please see the independent bias audit report covering our use of Covey for more information.] 

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Location & Eligibility

Where is the job
Worldwide
Fully remote, anywhere in the world
Who can apply
Same as job location
Listed under
Worldwide

Listing Details

First seen
April 6, 2026
Last seen
April 27, 2026

Posting Health

Days active
20
Repost count
0
Trust Level
56%
Scored at
April 27, 2026

Signal breakdown

freshnesssource trustcontent trustemployer trust
Mercury
Mercury
greenhouse

We’re building banking for startups. We emphasize beauty and usability, and customers seem to love our product.

Employees
350
Founded
2016
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MercurySenior Software Engineer - AI Engineering$167k–$219k