Senior Software Engineer - AI Engineering

Mercury; United States; On-site; USD 166,600 - 218,700; Full time

Job summary

Mercury is seeking an experienced backend developer to extend its internal AI platform. You will build and maintain systems that integrate internal data and enhance knowledge discoverability across teams. The ideal candidate has over 5 years in backend development, is fluent in multiple programming languages, and has experience with LLM-powered systems. This role offers a base salary range of $166,600 to $218,700 for US employees. Mercury values diversity and is an equal opportunity employer.

Qualifications

• 5+ years of backend development experience in complex, production systems.
• Fluent across programming languages and can navigate platform engineering and infrastructure.
• Hands-on experience building LLM-powered systems and has shipped to production.

Responsibilities

• Build and evolve MCP servers connecting internal systems and data sources.
• Expand and operate LLM gateway infrastructure for routing and observability.
• Create self-service scaffolding for non-engineers to prototype AI workflows.

Skills

Backend development

Programming languages fluency

LLM-powered systems experience

AI deployment tradeoffs understanding

Job description

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.

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 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.

Enable Faster Prototyping And Iteration Across The Company

• 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.

The ideal candidate

• 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.

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.