MongoDB

MongoDB

Software Engineer 3

Alberta; British Columbia; Manitoba; Nova Scotia; Ontario; Quebec · Mid

Sponsorship not specified$108k-$149kDetected 4 days ago
JavaScriptTypeScriptPythonJavaGoC#GitMongoDBAWSGCPCI/CDGitHub ActionsAPI DevelopmentLLMsAgentic AIDesign SystemsResearchLeadershipCommunication

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odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 18 green-card filings in this occupation, 100% were for a worker who already held the job.

Green-card intent detected

MONGODB, INC. obtained a prevailing wage determination for Software Developers in San Francisco, CALIFORNIA on 2026-06-29. No matching green-card filing appears in our data yet. The determination expires in 21 days (2026-09-26), and a green-card filing must follow before then or the employer starts over.

Green-card follow-through: 59%

Of 17 labor certifications old enough to have been used, 7 expired without the employer filing the next step. Median time from filing to decision: 495 days.97% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

16 transfer filings in the last year, covering 16 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • This is a software engineering role at the intersection of developer tooling, applied AI, and software quality.
  • You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows.
  • This role is open to remote work in Canada or can be based out of any of our Canada offices.

Responsibilities

  • Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them
  • Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals
  • Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage
  • Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression
  • Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI
  • Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code
  • Collaborate with engineers, security partners, and product teams
  • Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams

Requirements

  • 2+ years of experience building production software, developer tools, internal platforms, or automation systems
  • Experience reasoning about correctness and safety with ambiguous input, nondeterministic output, false positives, or untrusted content
  • Comfort in an evolving R&D environment where the right abstraction emerges through prototypes and feedback
  • How can tests verify an agent tool's structured result when item order may vary, but counts, required fields, and values must remain correct

Nice to have

  • Experience with agentic systems, LLM applications, prompt or rubric-based evaluation, or AI-assisted development
  • Experience with Go, Python, JavaScript/TypeScript, Java, or C#
  • Experience with GitHub Actions security, secret handling, static rule engines, or policy enforcement
  • Experience moving prototypes into production
  • Ship tooling that makes agent skills or developer workflows easier to test, review, and adopt
  • Improve the quality and interpretability of evaluations, not just their count
  • Convert recurring manual work and fragile scripts into documented, reusable automation
  • What success looks like

Skills

  • how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior.

Compensation

  • Salary is one part of MongoDB's total compensation and benefits package.
  • Please note, the base salary range listed below and the benefits in this paragraph are only applicable to candidates based in Canada.
  • $108,000 - $149,000 CAD

Benefits

  • Other benefits for eligible employees may include:

Company info

  • With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we're powering the next era of software.
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This listing is sourced directly from MongoDB's careers page and normalized into a canonical job model.