🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
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. 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. 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. #LI-ES1 Total Rewards The total rewards package at Mercury includes base salary, equity (stock options/RSUs), 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 USD Canadian employees (any location): $157,400 — $206,650 CAD
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.