About the role
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