Job Description:
Out of the successful launch of Chase in 2021, we’re a new team, with a new mission. We’re creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We’re people-first. We value collaboration, curiosity and commitment.
As a Data& AI Engineer at JPMorgan Chase within the Accelerator, you are the heart of this venture, focused on getting smart ideas into the hands of our customers. You have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By your nature, you are also solution-oriented, commercially savvy and have a head for fintech. You thrive in working in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.
While we’re looking for professional skills, culture is just as important to us. We understand that everyone's unique – and that diversity of thought, experience and background is what makes a good team, great. By bringing people with different points of view together, we can represent everyone and truly reflect the communities we serve. This way, there's scope for you to make a huge difference – on us as a company, and on our clients and business partners around the world.
Job responsibilities:
- Design, build, and maintain scalable data platforms and pipelines that support analytics and AI/ML use cases.
- Own and optimise Retrieval-Augmented Generation (RAG) pipelines to enable LLMs to safely and accurately use enterprise data.
- Implement and integrate GenAI capabilities using platforms such as AWS Bedrock, Google Vertex AI, Azure AI, or equivalent services.
- Develop robust data processing workflows using batch and streaming systems.
- Design and implement testing strategies across data and AI systems, including unit, integration, end-to-end, and performance testing.
- Ensure solutions meet enterprise standards for security, privacy, compliance, and governance.
- Collaborate with data, platform, and product teams to deliver reliable and scalable data and AI services.
- Mentor team members on engineering best practices, system design, and maintainable software development.
Preferred qualifications, capabilities and skills
- Strong proficiency in Java or JVM-based programming languages & good working knowledge of python.
- Experience building and operating data pipelines and analytical systems using technologies such as Google BigQuery, Amazon Athena, or ClickHouse.
- Experience with distributed data processing frameworks such as Apache Spark and/or Apache Flink.
- Experience with messaging and streaming systems such as Apache Kafka or Apache Pulsar.
- Experience working with cloud-based platforms (AWS, GCP, or Azure) and distributed systems architectures.
- Familiarity with cloud-native GenAI platforms such as Vertex AI, AWS Bedrock, or Azure OpenAI.
- Strong understanding of containerization and orchestration technologies such as Docker and Kubernetes.
- Understanding of Retrieval-Augmented Generation (RAG) systems and AI-assisted application architectures.
- Familiarity with embeddings, semantic search, vector databases, and context window limitations in LLM systems.
- Exposure to agent-based architectures and emerging protocols such as the Model Context Protocol (MCP).
- Experience with MLOps tools and platforms (e.g., MLflow, Amazon SageMaker, Google VertexAI, Databricks, BentoML, KServe, Kubeflow)
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