AI Engineer – Python LLM Architect, RAG & LangSmith Maestro
Engineering Role Details
Posted Dec 10, 2025At TeamStation AI, we are on a mission to bring together the brightest minds to solve tomorrow’s toughest technology challenges. Our work is about more than just AI—it’s about building the future through collaboration and innovation. We believe that the key to solving the world’s most complex problems lies in aligning diverse talents and perspectives. Our AI-powered platform enables cutting-edge scientific and technical teams to work smarter, faster, and together. By joining us, you’ll help unlock new technological breakthroughs and drive innovation where it matters most.
Join the Mission at TeamStation AI!
Where do we come from? We are seeking visionaries, innovators, and problem solvers who thrive in fast-paced, collaborative environments. If you’re passionate about AI, technology, and solving critical challenges, we want to hear from you. Come be part of a team where your ideas can drive the future.
AI Engineer – Master of Synthetic Intelligence (Senior Level)
Location: Mexico | Remote
Let’s talk about the AI hype. If you think being a "Senior AI Engineer" means just calling an API and stitching together a boilerplate prompt, we will waste your time, and you will hate our jobs. We aren't doing demo projects. We are building the core intelligence that dictates real-world, multi-million dollar advertising decisions in the Out-of-Home (OOH) media industry.
Are you tired of working on an "AI initiative" that is just marketing fluff? Do you want to move beyond simple LLM wrappers and actually architect the systems that make AI usable, reliable, and scalable?
Here is the reality of our TeamStation AI Partner: We are integrating large language models and other forms of generative AI directly into the brain of a global media platform. This means building RAG (Retrieval-Augmented Generation) pipelines, fine-tuning models for specific Ad Tech contexts, managing high-volume inference, and—most importantly—ensuring the output is not just plausible, but actionable. This role is about the engineering rigor required to make AI work in production, at scale, and in a high-stakes environment. You are the architect of the system, not just the user of the model.
What You’ll Do
- Architect and Implement AI Services: Design and deploy robust, low-latency microservices that leverage LLMs and other generative AI models usingPython.
- Be the Prompt Whisperer: Engineer, test, and optimize complex prompts for internal and external models, reducing "hallucinations" and ensuring contextual relevance within our proprietary Ad Tech data.
- Master the AI Plumbing: Build and maintain RAG systems, working with vector databases likePineconeorPostgreSQL(with pgvector) to provide models with the accurate, real-time context they need.
- Scale and Operationalize: Collaborate with Data Scientists and Data Engineers to take cutting-edge research and turn it into stable, high-availability features usingAWSservices (e.g., Lambda, EC2, ECS, Bedrock).
- Maintain Quality: Implement testing frameworks (Pytest, Playwright) specific to AI output to ensure consistency and reliability, because "close enough" is not good enough when millions are on the line.
Tech Stack & Tools
- Languages:Python(FastAPI, Flask)
- AI/LLM Frameworks:LangChain,OpenAI API,Hugging Face
- Data & Vector Stores:Pinecone,PostgreSQL(pgvector),Databricks
- Cloud:AWS
- DevOps:Git, Docker, Kubernetes (optional)
Requirements (Mid-Senior/Senior Level)
- 5+ years of experience in software engineering, with 3+ years dedicated to building and deploying AI/ML systems in a production environment.
- Expert proficiency inPythonand deep experience building scalable, asynchronous backend services.
- Proven track record of working hands-on with LLMs and Generative AI, including advanced prompt engineering and managing high-volume inference.
- Strong knowledge of data structures, algorithms, and microservice design patterns.
- Experience with CI/CD practices and source control (Git).
- Fluent in English.
Nice-to-Have (Bonus Points!)
- Full-stack capabilities with React or Next.js.
- Experience managing GPU resources for custom model deployment.
- Experience with the geospatial data stack.
What’s in It for You?
- Competitive Compensation: We pay top-tier rates for engineers who can deliver reliable AI.
- Fully Remote Work: Global team, LATAM focus.
- Career Growth: Work on problems that require true innovation, not just maintenance.
- Real Impact: Your code is the intelligence layer for a multi-billion dollar industry.