Forward-deployed Engineer - LatAm (Remote)

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 AI 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.