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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 deploying production-grade AI/ML applications, particularly focused on LLMs and generative AI. Proficient in Python, with a strong understanding of software development best practices and experience in integrating AI solutions into operational workflows.
Highest-signal resume keywords
Python ProgrammingLLM API ExpertiseProduction AI Agent DevelopmentCI/CD DeploymentAsynchronous Programming
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringAI/ML Application DevelopmentState ManagementError HandlingTestable Hypotheses TranslationAutomated EvaluationsPredictive TriggersDecision AutomationObservabilityCaching Optimization
Soft Skills
MentoringCollaborationProblem-Solving
Tools & Technologies
OpenAI SDKGoogle AI SDKCrewAILangChainGitGitHub
Industry Keywords
AI WorkflowsOperational FrictionCustomer Experience (CX)ComplianceTransaction Systems
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Partner with Ops leadership to transform operational friction into AI-assisted workflows
- Design end-to-end solutions involving predictive triggers, LLM-powered categorization, decision automation, and alert systems
- Architect, ship, and maintain stateful AI agents that call tools, move cases between queues, and retain state throughout case lifecycles
- Establish production monitoring, tracing, and observability for agentic workflows
- Integrate AI agents into CX, compliance, hold-queue, and transaction systems using least-privilege access
- Own containerization, CI/CD deployment, and post-launch stability
- Design automated evals-as-code, trajectory evaluations, adversarial benchmarks, and business-outcome measurements
- Optimize RAG pipelines and agent loops through caching, prompt compression, and model routing
- Mentor junior engineers and drive practices for asynchronous programming, error handling, and structured data validation
- Define autonomy boundaries, confidence thresholds, escalation paths, approval gates, and audit trails
- Collaborate with the Head of Ops Labs, AI leads, engineering teams, and product managers to develop and execute the AI roadmap
Requirements
What you’ll need- 5+ years of hands-on experience in software engineering, with at least 2 years dedicated to building and deploying production-grade AI/ML applications focused on LLMs or generative AI
- Mandatory expertise in Python and deep familiarity with at least one core LLM API or framework, such as OpenAI SDK, Google AI SDK, CrewAI, or LangChain
- Proven experience shipping production AI agents that take actions, including tool calling, multi-step orchestration, state management, human-in-the-loop escalation, guardrails, and failure handling
- Strong understanding of software development best practices, Git/GitHub, and CI/CD pipelines
- Ability to translate ambiguous operational briefs into testable hypotheses and validate assumptions through experiments
- Ability to translate high-level business needs into concrete, maintainable, and well-tested code
- Experience building AI for CX, support, compliance, or other operations teams
- Equivalent competencies in the listed areas will also be considered
Benefits
Comp & perks- Initial stock options grant
- Annual performance bonus
- Unlimited PTO
- Paid parental leave
- Work model: currently fully remote, with a future transition to a hybrid setup
- Health, dental, and vision plans
- Continuous learning opportunities
- Empowering opportunities for growth in a dynamic entrepreneurial environment