Machine Learning/AI Engineer

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Design, construct, and implement enterprise-level GenAI and Agentic AI solutions for intricate financial services workflows.

• Create workflows for exception classification, triage, root-cause analysis, impact assessment, and remediation advice.

• Develop agentic workflows that incorporate orchestration, tool/function calling, state management, and human-in-the-loop validation.

• Link new exceptions to historical issues, root causes, business rules, and transaction/data attributes.

• Develop Python and SQL services to query, transform, and analyze large structured enterprise datasets.

• Create reusable tools and services for AI-agent retrieval, investigation, analysis, and workflow execution.

• Integrate AI applications with enterprise APIs, databases, workflow/ticketing platforms, and internal data sources.

• Utilize RAG and context retrieval over regulatory documents, historical knowledge, and issue repositories.

• Implement confidence scoring, validation, guardrails, and traceability for AI-generated outcomes.

• Construct backend services and APIs using Python/FastAPI and deploy them on a prominent cloud platform.

• Enforce testing, logging, evaluation, observability, and production engineering practices.

• Collaborate with onshore and offshore engineers, architects, business analysts, data engineers, and application teams.

⛳️ Requirements

• Strong practical expertise in Python backend development and production-level services utilizing frameworks such as FastAPI.

• Proficient in SQL and data analysis with large structured datasets.

• Proven experience in building LLM/GenAI applications that go beyond proof-of-concept chatbots.

• Hands-on experience with an agent or workflow orchestration framework like LangGraph, Google ADK, CrewAI, AutoGen, Semantic Kernel, or similar.

• Knowledge of tool/function calling and reusable agent tools.

• Experience with RAG and retrieval techniques.

• Experience in implementing LLM evaluation, guardrails, and validation.

• Understanding of software engineering fundamentals including Git, testing, code review, and CI.

• Experience in deploying backend services on a major cloud platform; AWS preferred, GCP or Azure considered.

• Strong analytical, debugging, and root-cause analysis skills.

• Excellent command of English and ability to collaborate across distributed engineering and business teams.

• Pragmatic understanding of deterministic logic in contrast to LLM use.

• Experience level: Senior-level.

• Nice to have: experience in financial services, including regulatory reporting, capital markets, trade lifecycle, post-trade processing, transaction reporting, reconciliations, exception management, or risk and controls.

• Nice to have: familiarity with EMIR, MiFID II, or SFTR.

• Nice to have: Model Context Protocol (MCP) and reusable agent tool interfaces.

• Nice to have: Knowledge Graphs, Graph RAG, or data lineage.

• Nice to have: experience with vector databases, hybrid search, or re-ranking.

• Nice to have: AI observability and evaluation frameworks.

• Nice to have: AWS AI services like Bedrock and SageMaker; Docker, Kubernetes, and Terraform.

• Nice to have: ability to translate requirements into specifications, tasks, and acceptance criteria.

• Nice to have: familiarity with Claude Code or similar AI coding assistants.

• Nice to have: basic React or frontend integration experience.

• Must confirm if based in Brazil.

🏝️ Benefits

• People-first company culture.

• Supportive, trusted, and empowering work environment.

• Focus on team collaboration and long-term partnerships.

• Opportunity to work on impactful products and AI solutions.

• Chance to collaborate with global/onshore and offshore teams.