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