Staff Software Engineer, Agentic Tools

New

CriblAI infrastructure

Remote - United StatesFull-TimeStaff

Salary210,000 - 245,000 USD per year

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Job Details

Experience: Staff-level (or equivalent) professional software engineering experience
Required Skills: Node.jsJavascriptTypeScriptCI/CDDistributed Systems

Bring staff-level (or equivalent) professional software engineering experience building and operating production distributed systems.
Have strong TypeScript, modern JavaScript, and Node.js experience shipping production services.
Demonstrate strong software engineering fundamentals in design, testing, debugging, APIs and services, and code quality.
Have experience with automated pipelines, progressive delivery or safe rollout, monitoring, and rollback in a continuous deployment culture.
Have hands-on fluency with modern LLM and agentic coding workflows in production or serious internal platforms.
Bring experience building backend services, integrations, automation, and internal tools.
Have professional experience with agent orchestration, tool-calling systems, evaluation or guardrail techniques, and reliable backend integrations.
Be familiar with agent frameworks, orchestration layers, and integrating external tools and data sources into LLM-based systems; MCP or equivalent is a plus.
Have production experience with event-driven systems such as queues, streams, pub/sub, or webhooks.
Be fluent in observability metrics, logs, and traces, and use them to operate and improve production systems.
Communicate, document, and teach clearly, and be comfortable driving adoption.
Use good judgment around security, permissions, data access, and safe tool rollout.

Design, build, and operate production agentic workflows and platform harnesses, including orchestration, tool integrations, shared context, and extension points.
Turn goals into specifications, rules, constraints, and acceptance criteria that AI systems can execute reliably.
Build observability and guardrails, including tracing, regression detection, human-in-the-loop controls, safe rollout, and operability.
Own agent runtime components such as job isolation, scheduling, execution environments, secrets and access, and cloud operations.
Design and operate event-driven architectures using queues, streams, webhooks, or asynchronous job fan-out where appropriate.
Keep agentic systems on automated CI/CD paths with progressive delivery and clear rollback.
Improve how AI helps engineers write, test, review, debug, and validate changes in real repositories and pipelines.
Partner across Engineering to understand workflows, ship tools, and drive adoption through playbooks, examples, demos, and enablement.
Evaluate models, agent frameworks, MCP-style tool protocols, and the broader AI tooling ecosystem.
Take projects from agreed design through implementation, rollout, and day-two operability.

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