Research Engineer developing conditional generative adversarial networks for synthetic microstructures in PMC and CMC. Collaborating with AFRL and advancing materials performance through data - driven insights.
About the role
- AI Innovation Engineer at Clara, focused on rapidly shipping AI features for the leading fintech in Latin America. Join a pragmatic team for impactful work in an innovative environment.
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
- 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
- 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
- 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
Benefits
- 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
Job title
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