Senior Software Engineer II (AI Enablement)

New

JobgetherSoftware Engineering / AI

Remote work arrangement within the United States.Full-TimeSenior

Salary not disclosed

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Job Details

Bachelor's degree or higher in Computer Science, Engineering, or a related technical field.
5+ years of professional software engineering experience.
Demonstrated production ownership of a backend service or developer platform, such as an API gateway, service proxy, SDK/CLI, or internal developer platform.
Strong production experience with at least one modern application stack such as Python, TypeScript/Node, Go, or a comparable technology.
Strong experience with modern CI/CD practices and production software delivery.
Hands-on experience implementing authentication and authorization for machine-to-machine traffic, including OAuth2, OIDC, M2M credentials, token scoping, and secret management.
Demonstrated ability to instrument owned systems using metrics, structured logging, tracing, usage analytics, or similar observability practices.
Direct hands-on experience with agentic coding tools such as Claude Code, Cursor, Cody, Copilot agents, Aider, or equivalent tools in production.
Strong written communication skills for creating technical documentation and educational resources.
Experience authoring or maintaining MCP servers, Claude Code plugins, or comparable LLM-tooling integrations is preferred.
Experience operating an LLM gateway or inference proxy in production is preferred.
Background in healthcare technology, HIPAA-regulated environments, or systems handling protected health information is preferred.

Own and extend the MCP Gateway and connector platform, building and hardening integrations with enterprise systems such as Glean, Slack, Jira, Snowflake, Salesforce, Monday, Tableau, and Databricks.
Design and maintain authentication, authorization scopes, tenancy, rate limiting, and read/write policy enforcement for connected tools.
Own the plugin distribution layer and marketplace publishing pipeline, including versioning, CI/CD, plugin pull request reviews, release hygiene, and developer tooling synchronization.
Build and maintain shared plugins, skills, hooks, and Spec-Driven Development tooling used across engineering teams.
Create and maintain authoring documentation and guides that enable other teams to contribute to the platform independently.
Own platform observability, model gateway configuration, and AI cost attribution.
Define model-routing strategies and develop benchmarks and evaluation harnesses.
Extend infrastructure that transforms agent outputs into browsable, searchable, and collaborative experiences.
Run technical enablement activities such as office hours and educational sessions.
Mentor engineers on AI platform development patterns and plugin creation.

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