Aiml Engineer Iii – Treasury And Lending Platforms

Fidelity National Information Services

Jacksonville, FL, US
On-site
Azure openai, vectordbs, rag, rlhf
Aws, azure, or gcp cloud infrastructure
Mlops pipelines on azure
Leverage a broad stack of Open Source and SaaS AI technologies such as Azure OpenAI, VectorDBs, RAG, RLHF, and more to build scalable AI solutions for financial workflows including cash flow forecasting, treasury operations, liquidity optimization and regulatory compliance

Job Summary

  • Leverage a broad stack of Open Source and SaaS AI technologies such as Azure OpenAI, VectorDBs, RAG, RLHF, and more to build scalable AI solutions for financial workflows including cash flow forecasting, treasury operations, liquidity optimization and regulatory compliance.
  • Design, implement, and maintain cloud-native infrastructure using AWS, Azure, or GCP, with a focus on container orchestration (EKS/ECS, GKE), infrastructure-as-code (Terraform, CloudFormation), and support for GPU/accelerated workloads.
  • Architect and optimize advanced MLOps pipelines on Azure, automating data ingestion, distributed GPU model training, versioning, CI/CD validation, AKS deployment, and monitoring to deliver secure, compliant, and scalable AI solutions for complex financial workflows.

Matching Summary

Leverage a broad stack of Open Source and SaaS AI technologies such as Azure OpenAI, VectorDBs, RAG, RLHF, and more to build scalable AI solutions for financial workflows including cash flow forecasting, treasury operations, liquidity optimization and regulatory compliance.

Skills & Requirements

Must-have

  • Azure OpenAI, VectorDBs, RAG, RLHF
  • AWS, Azure, or GCP cloud infrastructure
  • MLOps pipelines on Azure
  • Large-scale AI model performance optimization
  • Machine learning for financial risk forecasting
  • Interpretability and compliance for AI models

Nice-to-have

  • Research on emerging AI techniques
  • Code reviews and mentoring junior teammates
  • Automated testing and performance monitoring

Key Requirements

  • Bachelor's degree or foreign equivalent in Statistics, Mathematics, Computer Science or related field and six (6) years of experience
  • Master's degree in listed fields and four (4) years of experience
  • Experience applying AI/ML in financial services or regulated industries
  • Experience integrating commercial LLM APIs
  • Experience in financial services and fintech domain
  • Experience with Python, PyTorch, TensorFlow/Keras, Hugging Face Transformers, LangChain, fine-tuning, and RLHF
  • Experience with AI model evaluation, prompt engineering, and RAG techniques

Work Rights

Not specified

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