We need a Lead Full-Stack Product Engineer with a heavy emphasis on Backend Architecture, Data Engineering, and Applied AI.

Offering a $5000 USD wage.

We need a really strong spoken English.

Fulltime long termo contract.

Here are the details.

Description

We are looking for an experienced software engineer to own and evolve the technical core of our live product. You will work where strong product engineering, data management, personalization and recommendation systems, and applied AI meet. The right person has built dependable software used by real customers and wants unusually direct influence over what gets built, how it works, and what improves next.

This is first and foremost a building role. Most of your time will be spent designing, coding, testing, shipping, and learning from what customers do next. You will also be a technical anchor for two engineers, helping the team make good decisions, work through hard problems, and raise the quality of what we ship.

The Client

Is an AI-native intelligence platform that helps organizations uncover, develop, and activate the influential voices within their networks. Starting in sports, the platform builds a living understanding of each athlete's voice, identity, ambitions, audience, and untold stories. This helps athletes strengthen their personal brands while giving organizations proprietary intelligence for storytelling, sponsorship, and activation.

Unlike generic content tools or social listening, Opine surfaces story data that does not exist anywhere else. Already working with two influential sports organizations, Opine plans to expand beyond sports to creators, brand ambassadors, executives, and employees whose experience and expertise carries value when voiced.

The Role

You will own the technical foundation beneath a working product already used by athletes, coaches, and organizations. That includes backend services, APIs, data models, integrations, application infrastructure, recommendation systems, platform architecture, and the AI capabilities behind personalization, content generation, and proactive coaching. Your job is to understand what is here, move it forward quickly, and help the product become more useful, reliable, and personal over time.

We want the ownership mentality often associated with a founding engineer, without asking someone to step into a co-founder role. You will notice important problems before they become polished tickets, make decisions with incomplete information, and stay close to the outcome after launch. Leadership in this role comes through judgment, initiative, and the quality of what you build.

Applied AI is central to Opine, but this is a product engineering role rather than a model research role. We need someone who knows when a problem calls for deterministic software, structured data, a personalization system, retrieval,



an agent, or a model, and can build the dependable production system around that choice.

The Product Today The product supports personal brand strategy, content planning and generation, organizational campaigns, social publishing, and performance insights. We are making the experience more proactive and personal while beginning to build a data intelligence layer that helps organizations better understand and activate the unique stories within their communities. Our current stack includes TypeScript, Next.js , Convex, WorkOS, PostHog, OpenAI and Anthropic models, social media data tools, and we expect you to improve the stack when product evidence supports the change.

Responsibilities

•⁠ ⁠Own and evolve the architecture behind Opine's product, backend, data, recommendation, and applied AI systems.

•⁠ ⁠Build and ship critical systems yourself, from APIs and data pipelines to recommendation services, agent workflows, and customer-facing product capabilities.

•⁠ ⁠Design reliable, secure, observable, and maintainable production software that can evolve as the product and customer base grow.

•⁠ ⁠Help build a scalable data intelligence layer that turns complex, evolving information into reliable, searchable, and privacy-conscious product experiences.

•⁠ ⁠Build recommendation and personalization systems that use behavioral signals, identity data, content performance, and feedback to surface the right idea, story, or action for each person.

•⁠ ⁠Build production AI systems that use agents, tools, memory, retrieval, evaluation, and feedback loops to improve the product.

•⁠ ⁠Strengthen practical engineering habits around system design, testing, code review, deployment, documentation, and incident response.

•⁠ ⁠Work closely with two engineers, offering technical feedback, unblocking difficult work, and helping the team ship with confidence.

•⁠ ⁠Work closely with product, design, the CEO, and the fractional CTO on the technical roadmap, and contribute to future engineering hires as the company grows.

Qualifications

•⁠ ⁠Eight or more years of professional software engineering experience, including substantial experience building and operating production systems.

•⁠ ⁠Experience operating as a senior, staff, or lead engineer with meaningful ownership of architecture and execution. Formal people management experience is welcome but not required.





•⁠ ⁠Strong backend engineering and system design skills, including API design, data modeling, service architecture, databases, integrations, and cloud infrastructure.

•⁠ ⁠Strong proficiency in TypeScript and comfort working across a modern product stack.

•⁠ ⁠A track record of owning systems through design, implementation, launch, monitoring, incident response, and ongoing improvement.

•⁠ ⁠Experience working in an early-stage or high-growth environment where priorities change, and engineers must make decisions with incomplete information.

•⁠ ⁠Strong product judgment and clear communication with technical and non-technical teammates. You can explain a tradeoff without turning it into a lecture.

•⁠ ⁠Strong knowledge of automated testing, continuous integration and deployment, security, performance, and reliability.

•⁠ ⁠Experience building data-intensive applications and production data pipelines with clear approaches to data quality, lineage, failure handling, and observability.

•⁠ ⁠Experience shipping LLM-powered, agentic, and/or highly personalized product experiences used by real customers.

•⁠ ⁠Working knowledge of agent orchestration, retrieval-augmented generation, memory, prompt and context engineering, tool use, embeddings, and model integration.

•⁠ ⁠Experience building evaluation, tracing, monitoring, and regression testing for systems with nondeterministic model behavior.

•⁠ ⁠Sound judgment about model selection, latency, cost, privacy, failure modes, and the boundary between model-driven and deterministic software.

•⁠ ⁠Daily fluency with AI-assisted engineering tools and a clear view of where they improve speed and where human review remains essential.

Preferred Experience

•⁠ ⁠Highly personalized consumer, creator, or professional software products.

•⁠ ⁠Experience in social publishing, media, sports, or the creator economy, especially while taking an early product from customer traction to a stable and scalable platform.

How We Work

•⁠ ⁠We expect engineers to use AI fluently in their daily work and to stay clear-eyed about where human judgment still matters.

•⁠ ⁠We move quickly, stay close to users, document important decisions, and hold a high bar for the systems customers rely on.

•⁠ ⁠We value direct communication, independent judgment, and people who raise problems early. We are remote and protect focus time.

•⁠ ⁠We see athletes as people with something real to say, not as content inventory. The product should reflect that in every interaction.

Language requirements

•⁠ ⁠This position is with a U.S.-based company. Advanced English proficiency is required, including strong written and verbal communication skills.

📌 Founding Engineer (AI/Data Product)/Staff Product Engineer wage. (Argentina)
🏢 Ultrix Labs
📍 Argentina