Senior Software Engineer - AI Engineering
Mercury · United States
- Hybrid
- Full-time
- $166,600 / year
- United States
Tailored resume — keyword-matched to this role.
Hiring manager — we find who's hiring.
Intro email — drafted to reach them directly.
Job highlights
- Build and scale Mercury's internal AI platform.
- Develop LLM gateway and knowledge layers.
- Enable faster AI prototyping across teams.
- Requires 5+ years backend development experience.
- Must have shipped LLM-powered systems to production.
About the role
About Mercury
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 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.
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.
Total Rewards
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 - 206,650Equal Opportunity
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.Key skills/competency
- Senior Software Engineer
- AI Engineering
- Backend Development
- LLM Systems
- RAG Pipelines
- Agent Development
- Platform Engineering
- Infrastructure
- Developer Tooling
- Production Systems
Skills & topics
- Senior Software Engineer
- AI Engineering
- Backend Development
- LLM
- RAG
- Agents
- Platform Engineering
- Infrastructure
- Developer Tooling
- SaaS
- Fintech
- Machine Learning
- Python
- Go
- Cloud Computing
- AWS
- GCP
- Azure
- Software Development
- Engineering Manager
- Team Lead
How to get hired
- Tailor your resume: Highlight your 5+ years of backend experience and any hands-on LLM project successes.
- Showcase AI expertise: Emphasize experience with RAG pipelines, agent frameworks, and production deployments.
- Demonstrate high agency: In your application and interviews, provide examples of self-directed work and problem-solving.
- Prepare for technical and behavioral questions: Be ready to discuss complex systems, AI tradeoffs, and communication skills.
- Research Mercury's AI focus: Understand their bet on AI and how this role contributes to their strategy.
Technical preparation
Master backend development and production systems.,Build and deploy RAG pipelines or agents.,Understand LLM cost, latency, and safety.,Familiarize with cloud infrastructure and tooling.
Behavioral questions
Describe a complex production system you built.,How do you identify high-leverage work?,Explain a technical concept to non-technical people.,How do you handle ambiguity in projects?
Frequently asked questions
- What is the primary focus of the Senior Software Engineer - AI Engineering role at Mercury?
- The Senior Software Engineer - AI Engineering role at Mercury focuses on building, extending, and scaling the company's internal AI platform and enablement layer. This involves developing core infrastructure like LLM gateways and shared knowledge layers to support AI initiatives across the company and enable faster prototyping for engineers and non-engineers alike.
- What specific technical experience is required for the Senior Software Engineer - AI Engineering position?
- The ideal candidate for the Senior Software Engineer - AI Engineering role has 5+ years of backend development experience in complex production systems. Crucially, they must have hands-on experience building LLM-powered systems, such as RAG pipelines or agents, and have successfully shipped at least one to production. Familiarity with platform engineering, infrastructure, and developer tooling is also essential.
- How does Mercury approach compensation for the Senior Software Engineer - AI Engineering role?
- Mercury offers a competitive total rewards package including base salary, equity, and benefits. Salary ranges are updated regularly based on industry data. For US employees, the target base salary range is $166,600 - $218,700. For Canadian employees, it's CAD 157,400 - 206,650. Offers are determined by experience, expertise, location, and internal pay equity.
- What kind of AI projects have engineers worked on at Mercury prior to this role?
- Prior to this role, engineers at Mercury have been engaged in 'scattered experiments' with AI, pushing boundaries by building agents and automating workflows. This role is designed to consolidate these individual efforts into shared infrastructure and capabilities, leveraging these early patterns to create durable defaults for broader company use.
- What does 'high-agency' mean in the context of the Senior Software Engineer - AI Engineering role at Mercury?
- 'High-agency' at Mercury means being self-directed and proactive. For the Senior Software Engineer - AI Engineering, this involves operating effectively without tightly defined scope, identifying the highest-leverage work, and independently driving it to completion. It's about taking initiative and making a significant impact.
- How does Mercury support diversity and inclusion in its hiring process for the AI Engineering role?
- Mercury is an Equal Employment Opportunity employer committed to diversity and belonging. All applicants are considered without regard to protected characteristics. They also offer reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If assistance is required, candidates are encouraged to inform their recruiter.