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Senior AI Engineer

5 months, 2 weeks ago
Brazil
Full-time
Senior
AI Engineer
Software Development
AWS Azure Feature Engineering GCP Go gRPC Hugging Face Kafka LLM Microservices MLflow Node.js PostgreSQL Python REST API SageMaker Vertex AI
Apply Now
Jeeves

Jeeves

Jeeves is a global financial infrastructure company that offers open business accounts, corporate cards, cross-border payments, and expense management through a borderless platform. With operations in 25+ countries, Jeeves simplifies and centralizes fi...

Diversified Financial Services
251-1K
$368M raised
View All Jobs 31

Description

  • Design, build, and maintain production-grade LLM integration pipelines, including RAG, prompt engineering, output parsing, and chain orchestration.
  • Develop and operate AI features such as spend categorization, document extraction, anomaly detection, financial Q&A, and automated reconciliation.
  • Implement structured output validation, fallback handling, and confidence scoring for financial AI use cases.
  • Evaluate and integrate AI frameworks and tools, and choose the appropriate stack for each problem.
  • Establish prompt versioning and evaluation practices to keep AI outputs accurate and consistent over time.
  • Design and maintain vector search pipelines to support semantic search and RAG-based features.
  • Build document ingestion and chunking pipelines for invoices, receipts, policy documents, and transaction records.
  • Collaborate with data scientists to move ML models from notebooks into production serving infrastructure.
  • Build and maintain model serving endpoints with latency, validation, and monitoring requirements.
  • Integrate AI services with backend microservices and implement observability, alerting, and human-in-the-loop review workflows.

Requirements

  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
  • 5+ years of professional software engineering experience, including at least 3 years focused on AI/ML systems in production.
  • Hands-on experience building and deploying LLM-powered applications in production using APIs such as OpenAI, Anthropic, or Cohere.
  • Experience designing and operating RAG pipelines, including chunking strategies, embedding models, and vector database integration.
  • Strong proficiency in Python for AI/ML workloads.
  • Familiarity with at least one AI orchestration framework such as LangChain or LlamaIndex.
  • Experience with ML model serving infrastructure, including REST or gRPC inference endpoints, input/output validation, latency budgeting, and monitoring.
  • Solid backend engineering fundamentals, including REST APIs, PostgreSQL or other relational databases, async patterns, and cloud infrastructure such as AWS, GCP, or Azure.
  • Experience with observability tooling such as structured logging, distributed tracing, and dashboards for system health.
  • Preferred experience in fintech, financial services, or other regulated industries where reliability and auditability are important.
  • Preferred experience with prompt evaluation frameworks, A/B testing AI outputs, and tracking production model degradation.
  • Preferred experience with ML lifecycle tools such as MLflow, Weights & Biases, Vertex AI, or SageMaker.
  • Preferred knowledge of real-time data streaming tools such as Kafka or Kinesis.
  • Preferred contributions to open-source AI tooling, technical writing, or conference talks.
  • Preferred startup or scale-up experience building foundational systems in ambiguous environments.

Interested in this position?

Apply directly on the company website

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