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 & Quality • 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