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Félix

Senior AI Engineer, Ops Labs

Félix

. Design, build, and scale autonomous AI agents for product and internal operations .

Posted 11/6/2026full-timeRemote • ArgentinaSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying production-grade AI applications, particularly with LLMs, while effectively translating operational challenges into scalable AI solutions. Proficient in Python and familiar with software development best practices, CI/CD pipelines, and AI performance metrics.

Highest-signal resume keywords
Python ProgrammingLLM API ExpertiseProduction AI Agent DevelopmentCI/CD DeploymentAI for Customer Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Software EngineeringAI/ML Application DevelopmentState ManagementError HandlingPredictive TriggersAutomated EvaluationsRAG Pipelines OptimizationAsynchronous ProgrammingTechnical Feasibility MappingOperational Workflow Design
Soft Skills
MentoringProblem-SolvingCollaborationCommunicationTranslating Ambiguity
Tools & Technologies
OpenAI SDKGoogle AI SDKCrewAILangChainGitGitHubContainerizationMonitoring ToolsObservability ToolsVector Databases
Industry Keywords
Customer ExperienceComplianceOperational MetricsAHTFCRCSATSLAAI StrategyAutomationDecision Automation

Tech Stack

Tools & technologies
Python

About the role

Key responsibilities & impact
  • Design, build, and scale autonomous AI agents for product and internal operations
  • Develop end-to-end AI strategies and use cases to automate and scale CX operations
  • Partner with the Head of Ops Labs and Ops leadership to identify operational problems and AI opportunities
  • Design AI-powered solutions that provide automation while preserving CX agent visibility and authority
  • Validate impact before scaling and map operational workflows to technical feasibility
  • Design evaluation frameworks measuring business outcomes and technical quality
  • Partner with AI leads, engineering teams, and product managers to turn AI strategy into a roadmap
  • Transform operational friction into AI-assisted workflows using predictive triggers, LLM-powered categorization, decision automation, and alert systems
  • Architect, ship, and maintain stateful production AI agents that call tools, move cases between queues, and maintain state throughout case lifecycles
  • Establish LLMOps 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
  • Build automated evals-as-code, trajectory evaluations, adversarial benchmarks, and safety and groundedness checks
  • 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

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
  • 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
  • RAG and vector databases are a plus
  • Strong understanding of software development best practices, Git/GitHub, and CI/CD pipelines
  • Personal projects or demonstrable GitHub contributions are a strong plus
  • Ability to translate ambiguous operational briefs into testable hypotheses
  • Ability to clarify success metrics and understand trade-offs between technical sophistication and operational constraints
  • Experience validating assumptions via 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
  • Familiarity with AHT, FCR, CSAT, and SLA metrics is a strong plus
  • Equivalent competencies in the listed areas will also be considered

Benefits

Comp & perks
  • Competitive salary
  • 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