Clara - Forward-deployed Engineer - LatAm (Remote)
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT
Requirements
• Strong proficiency in Python; working knowledge of Node.js or Java • Strong proficiency in Python • 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 • Hands-on experience integrating LLMs into production applications • Database expertise: PostgreSQL, vector databases (Pinecone, Weaviate, Chroma, pgvector), or data modeling • Database expertise • Cloud infrastructure: AWS services (ECS, S3, Lambda, RDS, API Gateway, SQS, etc.) • Cloud infrastructure • API development: RESTful services, authentication, rate limiting, error handling • API development • Built and deployed at least 2 AI/ML features or products to production that real users interact with • Built and deployed at least 2 AI/ML features or products to production • Experience with containerization (Docker) and orchestration (ECS, EKS, or similar) • Experience with containerization (Docker) and orchestration • Comfortable with git workflows and CI/CD practices (GitHub Actions, GitLab CI, automated deployments) • Comfortable with git workflows and CI/CD practices • 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 • Problem-solver first, technology evangelist second • Comfortable with ambiguity and rapid iteration—you thrive when requirements are fuzzy and priorities shift • Comfortable with ambiguity and rapid iteration • Self-directed with ability to scope and execute projects independently—you can take a problem and run with it • Self-directed with ability to scope and execute projects independently • Bias toward action—you ship working solutions and iterate based on feedback rather than pursuing perfection • Bias toward action • Experience with LangChain, LlamaIndex, or similar LLM frameworks for building RAG applications • Experience with LangChain, LlamaIndex, or similar LLM frameworks • Familiarity with embedding models and semantic search implementations • Familiarity with embedding models • 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) • Knowledge of ML model deployment • Experience in fintech or highly regulated industries understanding compliance and security requirements • Experience in fintech or highly regulated industries • Background in data engineering or analytics to understand data pipelines and infrastructure • Background in data engineering • Experience with prompt engineering best practices and LLM evaluation frameworks • Experience with prompt engineering best practices • Contributions to open-source AI/ML projects or technical writing/blogging • Contributions to open-source • 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
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. • rapidly build and ship AI features • 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 • 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
Benefits
• 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. • 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. • Competitive salary and stock options (ESOP) from day one • Multicultural team with daily exposure to Portuguese, Spanish, and English (our corporate language) • Portuguese, Spanish, and English • 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 • hybrid work model • 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.
No credit card. Takes 10 seconds.