Senior AI Engineer

Mexico - Ciudad de Mexico - Plaza Carso

Mexico - Monterrey

Mexico - Altamira

Full time

JR14189

As we create a colorful, capable and cleaner world through chemistry, we invite you to join our team to harness the power of chemistry to shape markets, redefine industries and improve lives for billions of people around the world.

At Chemours, our people are redefining how the world thinks of chemistry by approaching everything we do with a commitment to delivering Trusted Chemistry that creates better lives and helps communities thrive. That begins with how we use our science, data, and unmatched technical expertise to develop market-leading products with the highest levels of performance, sustainability, and safety in the industry.

Powered by chemistry, our products are used in applications that make the products we rely on, processes, and new technologies possible. In key sectors such as clean energy, advanced electronics, high-performance computing and AI, climate friendly cooling, and high-quality paints and coatings for homes and industrial infrastructure---sustainable solutions and more modern living depend on Chemours chemistry.

Chemours is seeking a Senior AI Applications Engineer to join our growing AI & Data Science team. This position will report directly to the Head of Data Science & AI, and would be located at our Plaza Carso Offices in Mexico City. For the right candidate we may consider remote.

Experienced full stack software engineer who has a track record of designing & launching apps (for internal and 3rd party use) & GenAI solutions. Successful candidates will be able to thrive in a fast paced, ambiguous environment with a continuous learning mindset. Role will also require heavy stakeholder/end-user engagement throughout the build process. Accommodate eastern time zone working hours.

• Identify, design, and integrate Generative AI solutions into existing business workflows to deliver measurable value
• Design, architect, implement,and productionize traditionalsoftware applications and GenAI agents.
• Partner with users and stakeholders to scope the use case, gatherrequirements, establish successcriteria, and deliver an intuitive, high-quality UX.
• Lead high-impact initiatives across multiple business functions, including Manufacturing, Legal, Finance, R&D, Supply Chain, Procurement, and Sales.
• Mentor & help accelerate the work of junior developers; foster collaboration and teamwork and pair-programming culture.
• Collaborate with related teams (ie. Cybersecurity, Infrastructure, Data Engineering, Office 365) to go thru approvals, architecture, security & governance reviews.
• When assigned to an opportunity, you will lead end-to-enddelivery.
• You will serve as product owner to defineand maintain aphased roadmap, incorporating continuous user feedback, backlog prioritization, and release planning into yourrecommendations.
• Lead software development from design throughdeployment.
• Communicate progress to non-technical but key stakeholders on a proactive & regular basis.
• For existing codebases, address technical debt and build scalable, reusable architectures that are well documented and conform to security and compliancestandards.
• Manage the full lifecycle of deployed applications, including debugging, enhancements, upgrades, and continuous improvement driven by user feedback and evolving technology.

• Degree in Computer Science or Computer Engineering
• 8+ years advanced backend development with PythonAND Javascript
• 2+ years designing, coding (in Python), and deploying custom and complex GenAI solutions and multi-agent GenAI systems in production. We need to see evidence beyond building simple recommender systems orchatbots.
• Minimum 2 years UI & frontend development with React.js, Typescript, and HTML
• Strong hands-on experience designing and building GenAI architectures and multi-agent systems, including embeddings, advanced Retrieval-Augmented Generation (RAG) techniques, and a variety of search architectures. Candidates should be able to clearly articulate solutions they have built using hybrid search, agentic search, vector search, and full-text search architectures.
• Demonstrated experience developing, deploying, and evaluating GenAI solutions, with a strong understanding of evaluation frameworks (evals) and a proven ability to optimize the cost-to-performance ratio of production AI applications.
• Strong proficiency with Pydantic models, including knowing when and how to leverage them to design robust, scalable, and maintainable GenAI architectures and workflows.