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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and improving LLM applications and integrations using Python and various SDKs, while effectively mentoring and guiding colleagues through technical challenges and live builds.
Highest-signal resume keywords
Python ProgrammingLLM Application DevelopmentAPI IntegrationMentoring and TrainingDebugging and Troubleshooting
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonAPIsGitTestingDebuggingLLM SDKTool CallingMulti-Step WorkflowsData SafeguardsQuality Evaluation
Soft Skills
CollaborationCommunicationProblem-SolvingMentoringAdaptability
Tools & Technologies
OpenAI SDKGoogle SDKMaestroVersion Control Systems
Industry Keywords
Technical Office HoursIntegration PatternsTroubleshooting GuidesLive BuildsUser-Centric Automation
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Build and improve reference agents, tool integrations and workflows with Python, LLM SDKs and APIs
- Pair with colleagues to scope practical builds, review code, and debug prompts, retrieval, tool calls, state, permissions and failures
- Run regular technical office hours, triage requests and track issues to closure
- Escalate complex integration, data, security or production problems with reproducible examples, logs and attempted fixes
- Turn recurring issues into reusable resources
- Create starter kits, tested agents, integration patterns and troubleshooting guides
- Maintain documentation, versioning, permissions and ownership on approved platforms including Maestro
- Own technical content and exercises for hands-on bootcamps and learning tracks
- Teach through live builds and debugging and mentor colleagues through guided builds and code reviews
- Test new platform capabilities, share practical guidance, bring recurring gaps to platform owners, and track adoption metrics
- Collaborate with team leads, Internal Talent, AI Solutions, FDE, AI Enterprise, Data, Security and platform specialists
Requirements
What you’ll need- Hands-on experience building LLM applications, agents or automations for real users, including what failed and how you improved it
- Strong Python, APIs, authentication, Git, testing and debugging
- Practical use of at least one LLM SDK such as OpenAI or Google
- Ability to read logs and traces, isolate failures and create reproducible examples
- Experience with tool calling, multi-step workflows, state, structured outputs, human review and failure handling
- Ability to build useful evaluations and explain quality, latency, cost and data safeguards
- Experience mentoring builders and mixed technical and business audiences through live builds and debugging, with follow-through after training
- Live pairing or debugging exercise during the interview
- Ability to turn ambiguous requests into testable hypotheses, know when to escalate, and close the loop
Benefits
Comp & perks- Competitive salary
- Initial stock options grant
- Annual performance bonus
- Unlimited PTO
- Paid parental leave
- Hybrid work setup
- 401(k) with employer matching, for US-based employees
- Health, dental, and vision plans
- Continuous learning opportunities
- Empowering opportunities for growth in a dynamic entrepreneurial environment
