MongoDB
Software Engineer 3
United States
Sponsorship not specified$109k-$215kDetected 8 hours ago
JavaScriptTypeScriptPythonJavaGoC#GitMongoDBAWSGCPCI/CDGitHub ActionsAPI DevelopmentLLMsAgentic AIDesign SystemsResearchLeadershipCommunication
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odds of building a lasting career here
61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
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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 the US or can be based out of any of our US 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 U.S.-based candidates.
- MongoDB's base salary range for this role in the U.S. is:
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.