My job alerts

AI Innovation Engineer (Ingeniero de Innovación) - Mexico City (Hybrid)

Clara

Software Engineering, Data Science

Latin America

Posted on Feb 5, 2026

Apply now

Ready to accelerate your career?

Clara is the fastest-growing company in Latin America. We've built the leading solution for companies to make and manage all their payments. We already help over 20,000 large and growing businesses operate with agility and financial clarity through locally issued corporate cards, bill pay, financing, and a powerful B2B platform built for scale.

Clara is backed by some of the most successful investors in the world, including top regional VCs like monashees, Kaszek, and Canary, and leading global funds like Notable Capital, Coatue, DST Global Partners, ICONIQ Growth, General Catalyst, Citi Ventures, SV Angel, Citius, Endeavor Catalyst, and Goldman Sachs - in addition to dozens of angel investors and local family offices.

We’re building the financial infrastructure that powers high-performing organizations across the region. We invite you to join us if you want to be part of a fast-paced environment that will accelerate your career and support you to do some of the best work of your life alongside a passionate and committed team distributed across the Americas.

CLARA's Innovation Team is looking for a pragmatic, fast-moving Innovation Engineer who thrives on shipping AI-powered features quickly. This team operates in ultra-fast mode, identifying opportunities, building prototypes, and delivering production-ready AI solutions that create immediate business value. You'll work at the intersection of product, engineering, and AI—turning ideas into deployed features in weeks, not months.

Responsibilities

Your main focus will be to rapidly build and ship AI features that solve real customer and internal problems. You'll own projects end-to-end: from scoping and architecture to implementation and production deployment. Speed and pragmatism are core to this role—you'll make smart tradeoffs to deliver quick wins while maintaining production quality standards.

Core Responsibilities:

Rapid AI Product Development

Design, build, and deploy AI-powered features and applications from 0 to 1 in production
Integrate LLMs and AI models into existing products and workflows, handling the full stack from API integration to user-facing features
Build intelligent automation tools that improve internal operations, customer experience, or business processes
Create MVPs and prototypes quickly to validate ideas, then iterate based on real usage and feedback
Own the entire lifecycle: scoping, technical design, implementation, deployment, and monitoring

Production Engineering & Infrastructure

Build robust APIs and backend services that power AI features with proper authentication, rate limiting, and error handling
Design and implement data pipelines that support AI applications: document processing, embedding generation, vector search
Deploy and maintain containerized applications on AWS infrastructure (ECS, Lambda, S3, RDS)
Implement monitoring, logging, and observability for AI features in production
Ensure AI applications meet security, privacy, and compliance requirements for financial services

Cross-Functional Collaboration & Innovation

Work closely with product teams, data scientists, and business stakeholders to identify high-impact AI opportunities
Translate business problems into technical solutions, making pragmatic decisions about build vs. buy vs. API
Share knowledge and evangelize successful patterns across engineering teams
Balance speed with sustainability—ship fast without creating technical debt that blocks future iteration
Contribute to the broader engineering organization by bringing innovation team learnings back to core teams

Continuous Learning & Experimentation

Stay current with rapidly evolving AI tools, frameworks, and best practices
Experiment with new AI capabilities and evaluate their potential for Clara's use cases
Share findings, demos, and insights with the broader team to inspire innovation

Requirements

Technical Skills:

Strong proficiency in Python; working knowledge of Node.js or Java
Hands-on experience integrating LLMs into production applications (not just prompt engineering)—you've built real features with OpenAI, Anthropic, or similar APIs
Database expertise: PostgreSQL, vector databases (Pinecone, Weaviate, Chroma, pgvector), or data modeling
Cloud infrastructure: AWS services (ECS, S3, Lambda, RDS, API Gateway, SQS, etc.)
API development: RESTful services, authentication, rate limiting, error handling

Experience:

Built and deployed at least 2 AI/ML features or products to production that real users interact with
Experience with containerization (Docker) and orchestration (ECS, EKS, or similar)
Comfortable with git workflows and CI/CD practices (GitHub Actions, GitLab CI, automated deployments)
Experience working across the full stack: backend APIs, data processing, and basic frontend integration

Mindset:

Problem-solver first, technology evangelist second—you choose the right tool for the job, not the newest one
Comfortable with ambiguity and rapid iteration—you thrive when requirements are fuzzy and priorities shift
Self-directed with ability to scope and execute projects independently—you can take a problem and run with it
Bias toward action—you ship working solutions and iterate based on feedback rather than pursuing perfection

Nice to Have

Experience with LangChain, LlamaIndex, or similar LLM frameworks for building RAG applications
Familiarity with embedding models and semantic search implementations
Experience with streaming APIs and real-time AI applications (WebSockets, Server-Sent Events)
Frontend experience (React, Next.js) to build full-stack AI features
Knowledge of ML model deployment (model serving, inference optimization, A/B testing)
Experience in fintech or highly regulated industries understanding compliance and security requirements
Background in data engineering or analytics to understand data pipelines and infrastructure
Experience with prompt engineering best practices and LLM evaluation frameworks
Contributions to open-source AI/ML projects or technical writing/blogging

What Makes You Stand Out

Execution & Velocity

You have a track record of shipping fast—your GitHub/portfolio shows completed projects, not abandoned experiments
You're comfortable making technical tradeoffs to hit timelines without sacrificing quality
You know when to build custom solutions vs. when to use managed services or third-party APIs
You can scope projects realistically and communicate progress transparently

Technical Depth & Pragmatism

You understand the full lifecycle of AI features: prompt engineering, API integration, error handling, cost optimization, monitoring
You've debugged production issues with LLM-powered applications and know the common pitfalls
You're proficient with modern development tools and AI assistants (GitHub Copilot, Cursor, Claude, ChatGPT) to accelerate your work
You write clean, maintainable code that others can understand and extend

Innovation & Business Sense

You think about business impact, not just cool technology—you ask "will this move the needle?" before building
You're curious and stay current with AI developments, but you're skeptical about hype
You enjoy working directly with stakeholders to understand problems and validate solutions
You're energized by ambiguity and the challenge of building something new

Collaboration & Communication

Excellent at working in distributed teams with strong communication skills
You can explain technical concepts to non-technical stakeholders clearly
You take ownership of outcomes, not just code—you care about whether users get value from what you build
You're humble, eager to learn, and willing to help others succeed

Why Join Clara's Innovation Team?

You'll have the autonomy to identify opportunities, build solutions, and ship AI features that create real business value. This isn't a research role—you'll be building production systems that customers and internal teams use daily. You'll work with cutting-edge AI technologies while maintaining the pragmatism and velocity of a high-performing startup. If you love moving fast, shipping frequently, and seeing your work create immediate impact, this is the team for you.

Why join Clara

At Clara, you’ll have the autonomy, speed, and support to make meaningful impact — not just on your team, but on how organizations are run across Latin America.

Who we are

We’re the leading B2B fintech for spend management in Latin America.
Certified as one of the world's fastest-growing companies, a Great Place to Work, and a LinkedIn Top Startup.
Passionate about making Latin America more prosperous and competitive.
Constantly innovating to build financial infrastructure that enables each of our customers to thrive.
Product-led, high-talent-density culture — designed for builders who raise the bar.
Proud of our open, inclusive, and values-driven environment.

What we believe in

#Clarity. We say things clearly, directly, and proactively.
#Simplicity. We reduce noise to focus on what really matters.
#Ownership. We take responsibility and never wait to be told.
#Pride. We build products and experiences we’re proud of.
#Always Be Changing (ABC). We grow through feedback, risk-taking, and action.
#Inclusivity. Every voice counts. Everyone contributes to our mission.

What we offer

Competitive salary and stock options (ESOP) from day one
Multicultural team with daily exposure to Portuguese, Spanish, and English (our corporate language)
Annual learning budget and internal accelerated development paths
High-ownership environment: we move fast, learn fast, and raise the bar — together
Smart, ambitious teammates — low ego, high impact
Flexible vacation and hybrid work model focused on results

If you’re ready for growth, ownership, and impact — apply now and help us redefine B2B finance in Latin America.

Clara’s Hybrid Policy

Claridians in a hybrid mode split their time between working from the office, talking to or visiting customers, or working from home. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for each individual and team.

We don't enforce a minimum number of days for most roles, but you're expected to spend time at the office organically, and be at the office most days during your ramp-up or when required by your leader.