Mercury

3 months ago

Senior Software Engineer - AI Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Senior software engineer to extend, harden, and scale Mercury's internal AI platform and enablement layer, building shared infrastructure, knowledge context, and self-service tooling to accelerate cross-team AI workflows. You’ll work on LLM gateway infrastructure, prompt libraries, guardrails, and knowledge artifacts, collaborating with domain teams to ships production-ready AI capabilities.

Location: San Francisco, New York

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Extend the AI platform foundation by building and evolving MCP servers, expanding the LLM gateway infrastructure, and turning early patterns into durable defaults.
•Strengthen the shared knowledge layer by shaping structured context artifacts and improving knowledge discovery and retrieval.
•Enable faster prototyping and iteration by building sandbox environments, self-service scaffolding, and evaluation harnesses for rapid AI experimentation.
•Partner with domain teams to standardize sources of truth and ensure data sources stay fresh and reliable.
•Collaborate across engineering and non-engineering stakeholders to communicate impact and align on highest-leverage work.

Key Requirements

•Has 5+ years of backend development experience in complex, production systems.
•Fluent across programming languages and can navigate platform engineering, infrastructure, and developer tooling.
•Hands-on experience building LLM-powered systems—RAG pipelines, agents, eval frameworks—andhas shipped at least one of these to production.
•Understands tradeoffs in AI deployments: cost modeling, observability, latency, and safety.
•High-agency and self-directed; can operate without tightly-defined scope and communicate clearly across technical and non-technical audiences.

Experience:5+ yearsAISaaSFintech

Skills:CommunicationProblem-solvingCollaborationLeadership

Languages:English

Tech Stack:LLMRAGGatewayGuardrailsPolicy-as-codeObservabilityScalabilityInfrastructure

Company Brief

Mercury

Provides banking and financial infrastructure for startups and small businesses, offering business checking accounts, payments, debit cards, venture debt integrations, and treasury services via a developer-friendly platform.

Industry: Fintech Infrastructure

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2017

Website LinkedIn

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Mercury

3 months ago

Senior Software Engineer - AI Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: San Francisco, New York

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Extend the AI platform foundation by building and evolving MCP servers, expanding the LLM gateway infrastructure, and turning early patterns into durable defaults.
•Strengthen the shared knowledge layer by shaping structured context artifacts and improving knowledge discovery and retrieval.
•Enable faster prototyping and iteration by building sandbox environments, self-service scaffolding, and evaluation harnesses for rapid AI experimentation.
•Partner with domain teams to standardize sources of truth and ensure data sources stay fresh and reliable.
•Collaborate across engineering and non-engineering stakeholders to communicate impact and align on highest-leverage work.

Key Requirements

•Has 5+ years of backend development experience in complex, production systems.
•Fluent across programming languages and can navigate platform engineering, infrastructure, and developer tooling.
•Hands-on experience building LLM-powered systems—RAG pipelines, agents, eval frameworks—andhas shipped at least one of these to production.
•Understands tradeoffs in AI deployments: cost modeling, observability, latency, and safety.
•High-agency and self-directed; can operate without tightly-defined scope and communicate clearly across technical and non-technical audiences.

Experience:5+ yearsAISaaSFintech

Skills:CommunicationProblem-solvingCollaborationLeadership

Languages:English

Tech Stack:LLMRAGGatewayGuardrailsPolicy-as-codeObservabilityScalabilityInfrastructure

Company Brief

Mercury

Industry: Fintech Infrastructure

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2017

Website LinkedIn