AI Engineer
Simetrik
Role: Business Value Associate
Location: LatAm
Investors:
Goldman Sachs Asset Management
Company Overview
Created in 2019, Simetrik is a robust B2B platform powered by no code and generative AI. It empowers financial and operational teams by allowing them to automate all reconciliations from start to finish, and anticipate and manage risks all on a single, intuitive, and robust interface inspired by spreadsheets.
Simetrik has established itself as a market leader in Latin America, handling two-thirds of the region’s transactions. Its clientele includes prominent institutions such as PayU, Mercado Libre, Rappi, PagSeguro, Falabella, Oxxo, Itaú, and Nubank, and partnerships with leading firms like Deloitte. Expanding its international reach, Simetrik has also successfully penetrated key Asian markets, serving clients in India and Singapore. The company's global footprint spans over 35 countries, monitoring over 200 million records daily.
Executive Team
Co-Founder & CEO
Co-Founder & COO
CFO
VP of Revenue | Latam
About the role
At Simetrik we are building the foundation of an AI-powered ecosystem where agents transform financial operations. As an AI Engineer you will join the Agent Factory team to design, build, and deploy production ready AI agents that deliver tangible client value. The role blends software engineering rigor with data science depth. We want builders who thrive in ambiguity, move fast from concept to production, and are motivated by creating the first generation of scalable AI agents at Simetrik.
¿What does success look like in this role?
Your work reaches production with measurable outcomes such as agents deployed, client adoption, and user satisfaction. You balance speed and quality, communicate clearly, and adapt to changing priorities without losing execution momentum.
¿What is the impact and the scope of this position?
This team sits at the core of Simetrik’s future. The agents you ship can become a new business line larger than today’s company. You will be among the pioneers defining what the future looks like, moving agents from experiments to revenue.
What results do we expect in the first 3 to 6 months? Link: (Matriz)
You deliver at least six functional agents ready for production. You validate use cases with product and operations, measure value, and establish lightweight engineering practices that let pods replicate and scale delivery.
In this role you will
What are the main responsibilities for this role?
- Design, build, and deploy AI agents tailored to real customer problems.
- Work end to end from data preparation and model experimentation to backend integration and cloud deployment.
- Collaborate with product, data, and operations to identify high-value opportunities and iterate based on feedback.
- Ensure production readiness through testing, monitoring, and performance evaluation.
- Contribute reusable components and frameworks that speed up future agent development.
- Continuously explore state-of-the-art AI technologies and assess their production viability.
- Build functional agents aligned with business needs and client expectations.
- Maintain robust Python codebases using sound engineering practices.
- Integrate machine learning and large language models into scalable systems.
- Deploy and operate services in cloud environments with maintainability in mind.
- Partner with cross-functional pods to validate, iterate, and improve outcomes.
Must Have
What does this person need to have in terms of skills to be successful?
- Hands-on experience with API development and model serving (FastAPI, Flask, or Django).
- Hands-on experience with LLMs (e.g., OpenAI, Anthropic, Hugging Face, Cohere).
- Practical experience with LLM frameworks (ADK, LangChain, LlamaIndex, CrewAI, Autogen, or similar).
- Experience designing and building LLM Agents, applying techniques such as RAG, tool-use, and behavioral customizations (Swarm, MagenticOne, etc.).
- Familiarity with multi-agent communication standards and tooling (MCP – Model Context Protocol, A2A protocols).
- Familiarity with prompt engineering, RAG pipelines, and fine-tuning workflows.
- Knowledge of experiment tracking and evaluation frameworks (MLflow, Weights & Biases, or custom setups).
- Experience with containerized applications (Docker) and CI/CD pipelines. * Experience working with relational and non-relational databases.
- Comfortable collaborating in cross-functional, remote teams.
Nice to Have
- Familiarity with vector databases and retrieval systems (Pinecone, Weaviate, FAISS, Milvus).
- Proficiency in cloud services (AWS Lambda, S3, SageMaker, ECS, or similar).
- Experience with data versioning and dataset management (DVC, Delta Lake).
- Knowledge of caching strategies, model routing, and latency optimization for AI systems.
- Experience designing evaluation pipelines aligned with product and user metrics.
- Understanding of responsible AI principles: fairness, privacy, security, explainability.
- Fluency in written and spoken English and Spanish. * Startup experience is a plus. Responsibilities
- Design, build, and deploy LLM-powered agents with capabilities for reasoning, memory, and tool use.
- Adapt foundation models through prompting, RAG, fine-tuning, or hybrid approaches as required.
- Build evaluation pipelines to measure accuracy, consistency, safety, and alignment with business goals.
- Implement caching, model routing, and guardrails to optimize performance and ensure safe outputs.
- Develop scalable APIs and services that expose LLM and agent capabilities.
- Collaborate with product and engineering teams to integrate agents into real-world applications.
- Monitor, retrain, and refine agents using user feedback loops for long-term reliability.
- Document system architectures, data flows, and AI workflows for reproducibility and maintainability.
Qualifications
- Degree in Computer Science, Engineering, Mathematics, or a related field. Advanced degrees are a plus but not required.
- Three or more years of experience across data science, machine learning, or software engineering.
- Hybrid profiles are strongly valued.
- Professional proficiency in English and Spanish, Portuguese is a plus.
- Location in LATAM preferred. Remote friendly with distributed pods.
Benefits
- Well-funded and proven startup with large ambitions and competitive salaries.
- Uncapped commissions.
- Entrepreneurial culture where pushing limits, creating and collaborating is everyday business.
- Open communication with management and company leadership.
- Small, dynamic teams = massive impact.
- 100% Remote Work (You choose where to work from).
- 500USD a year for you to invest in learning.