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Senior AI Engineer

2 months, 1 week ago
Mexico
Full-time
Senior
AI Engineer
Software Development
AWS Azure Feature Engineering GCP Go gRPC Kafka Machine Learning 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 18

Description

  • Design, build, and maintain production-grade LLM integration pipelines, including RAG, prompt engineering, output parsing, and chain orchestration.
  • Develop AI features for core financial products 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 right tool for each use case.
  • Establish prompt versioning and evaluation practices to keep AI outputs accurate and consistent over time.
  • Design and maintain vector search and document ingestion pipelines for financial documents and transaction records.
  • Optimize retrieval quality through embedding selection, chunking strategy, metadata filtering, and re-ranking.
  • Collaborate with data scientists to move ML models from notebooks into production serving infrastructure.
  • Build and maintain model serving endpoints with latency SLOs, input validation, and output monitoring.
  • Integrate AI services with backend microservices and build monitoring, tracing, dashboards, 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 with 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, validation, latency budgeting, and monitoring.
  • Solid backend engineering fundamentals, including REST APIs, PostgreSQL or other relational databases, async patterns, and cloud infrastructure.
  • Experience with observability tooling such as structured logging, distributed tracing, and dashboards for AI system health.
  • Preferred: experience in fintech, financial services, or another regulated industry where AI reliability and auditability matter.
  • Preferred: familiarity with prompt evaluation frameworks, AI A/B testing, and monitoring model performance degradation in production.
  • 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, published technical writing, or conference talks.
  • Preferred: prior startup or scale-up experience building systems from scratch in ambiguous environments.

Interested in this position?

Apply directly on the company website

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