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Senior AI Engineer

4 weeks ago
Argentina
Full-time
Senior
AI Engineer
Software Development
AWS Azure Feature Engineering GCP Go gRPC Hugging Face Kafka 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 20

Description

  • Design, build, and maintain production-grade LLM pipelines, including RAG, prompt engineering, output parsing, and chain orchestration.
  • Develop AI-powered features for spend categorization, document extraction, anomaly detection, financial Q&A, and automated reconciliation.
  • Implement structured output validation, fallback handling, and confidence scoring for financial AI decisions.
  • Evaluate and integrate AI frameworks and tools such as LangChain, LlamaIndex, OpenAI, Anthropic, HuggingFace, and vector databases.
  • 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 SLOs, input validation, and output monitoring.
  • Integrate AI services with backend microservices, add observability, and create human-in-the-loop review workflows for high-value actions.

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 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, with familiarity in at least one 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 experience with REST APIs, 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 another regulated industry where reliability and auditability matter.
  • Preferred familiarity with prompt evaluation frameworks, A/B testing AI outputs, and tracking 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 open-source contributions, technical writing, or conference talks in AI/ML.
  • Preferred startup or scale-up experience building foundational systems in ambiguous environments.

Interested in this position?

Apply directly on the company website

Apply Now

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