Tech Lead

The Tech Lead is responsible for translating product ideas and data science capabilities into production-ready AI solutions. This role partners closely with Product Management and the Data Science Leader to rapidly design, prototype, and ship AI-driven features that deliver measurable business value. This is a highly hands-on technical leadership role focused on  speed, pragmatism, and production quality , balancing experimentation with scalable engineering practices.  

 This is a remote opportunity. We are seeking contractors located in LATAM who are comfortable working in an English-speaking professional environment.

Key Responsibilities  

AI Solution Delivery & Architecture  

• Lead the technical design and implementation of AI-powered product features from concept through production.  

• Own end-to-end architecture for AI solutions, including data flows, model integration, APIs, and application integration.  

• Make pragmatic decisions to accelerate delivery while maintaining system integrity.  

• Ensure AI solutions are secure, observable, scalable, and aligned with platform standards.  

Pod Leadership & Execution  

• Act as the technical lead for a cross-functional AI Pod.  

• Break down product requirements into executable technical workstreams and prototypes.  

• Guide rapid iteration cycles, proofs-of-concept, and MVPs, balancing experimentation with production readiness.  

• Review code, architecture, and technical decisions to maintain quality and velocity.  

Product & Data Collaboration  

• Partner closely with Product Management to shape problem definitions, success metrics, and delivery plans.  

• Collaborate with the Data Science Leader to integrate models, analytics, and data assets into product workflows.  

• Translate data science outputs into consumable APIs, services, and product features.  

• Provide technical feedback on feasibility, scope, and tradeoffs during product discovery.  

Operationalization & Qualit y  

• Ensure features are production-grade, including monitoring, logging, and performance tracking.  

• Implement guardrails around AI usage, including reliability, latency, cost controls, and failure modes.  

• Support experimentation frameworks, A/B testing, and post-launch learning loops.  

• Drive responsible AI practices, including explainability, bias awareness, and data privacy considerations.  

Technical Standards & Enablement  

• Define and enforce lightweight engineering standards for AI-enabled systems.  

• Promote reuse of components, prompts, pipelines, and services across AI initiatives.  

• Mentor pod engineers on AI-adjacent system design and best practices.  

• Contribute to internal documentation and shared AI patterns/playbooks.  

Required Qualifications  

• BS or MS in Computer Science, Engineering, or related technical field.  

• 5+ years of software engineering experience, including leading complex systems.  
• Strong experience designing and building production APIs and backend services.  
• Proficiency in Python and at least one backend language (e.g., Java, Node.js, Go).  

• Experience with cloud-native architectures (AWS, GCP, or Azure).  

• Solid understanding of data pipelines, model serving, and system observability.  

• Ability to work closely with product teams in fast-moving, iterative environments.  

Preferred Qualifications  

• Experience working in AI-first or data-driven product teams.  

• Familiarity with modern LLM platforms, prompt engineering, and agent frameworks.  

• Experience operationalizing ML models (model serving, monitoring, versioning).  

• Exposure to experimentation platforms, feature flags, and A/B testing.  
• Experience in Agile or product-led development environments.  

Total monthly compensation: $3,500 — $4,500 USD