AI Engineer

Provenir•New York, NY

11d•Remote

About The Position

Provenir is a global fintech company seeking a highly skilled and motivated AI Engineer to join our team. You will design, develop, and deploy machine learning models and AI systems that solve real-world problems. You’ll work closely with data scientists, engineers, and product teams to turn data into actionable insights and intelligent solutions. This role can be performed remotely; however, candidates located in or able to travel to the NYC metro area are preferred and should expect to attend in-person meetings at our NJ office approximately once a month. We are only considering candidates who are authorized to work in the United States without the need for current or future visa sponsorship.

Requirements

5 Years of experience as AI Engineer
Strong Python development skills, including experience with modern frameworks (FastAPI preferred) and testing practices (pytest, unittest)
Proven ability to take ML/LLM models from prototype to production in containerized, cloud-native environments
Hands-on experience with deploying and managing services on Kubernetes (EKS) and Docker-based workflows
Expertise with AWS services : Bedrock, SageMaker, Lambda, EKS, S3, IAM, CloudWatch
Familiarity with Generative AI frameworks (LangChain, LlamaIndex) and Agent development (tool integration, RAG workflows)
Knowledge of vector databases and embeddings (e.g., Pinecone, FAISS, OpenSearch)
Experience with CI/CD pipelines (GitHub Actions preferred) and Infrastructure as Code (Terraform, CloudFormation)
Solid foundation in object-oriented programming with a language such as Java, C#, or C++ (in addition to Python)
Understanding of MLOps practices including monitoring, logging, scaling, and secure deployment in production

Responsibilities

Designing and developing APIs and reusable components for ML and GenAI deployment
Building and scaling ML/GenAI pipelines on AWS (Bedrock, SageMaker, Step Functions, Argo, Kubeflow on EKS)
Productionising LLMs, generative AI applications, and predictive models on Amazon Bedrock
Developing and integrating AI Agents with frameworks like LangChain for orchestration and tool use
Writing robust, testable, and maintainable Python code for backend services, SDKs, and ML workflows
Packaging and deploying containerized services on Kubernetes (EKS) with attention to scalability, resilience, and observability
Working in a modern MLOps environment with CI/CD, monitoring, and version control best practices
Supporting and maintaining cloud-native SaaS solutions at scale on AWS