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