We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Sector, AI / ML Data Platforms Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading and cutting edge technology products in a secure, stable, and scalable way.
This technology includes AI / ML Platform Solutions using LLMs, public cloud and modern standards and patterns. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Develop cutting edge AI / ML Platform solutions using LLMs, public cloud and modern standards and patterns.
- Develop solutions using AWS Cloud Services for compute, storage, databases, and security and Azure Services
- Develop solutions using Generative AI Models
- Work closely with the Product team to design, build and deliver capabilities in agile sprints.
- Collaborate with cross-functional teams, including data scientists, software engineers, and designers, to integrate generative AI into various applications and products.
- Develop and implement state-of-the-art generative AI services leveraging Azure Open AI models and AWS Bedrock service.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Hands-on experience working on AWS Cloud Based applications development using EC2, EKS, Lambda, SQS, SNS, RDS Aurora MySQL & Postgres, DynamoDB, and Kinesis.
Strong understanding of AWS networking, security, IAM roles, monitoring and application debugging is critical.
- Deep expertise across application, data, security, and infrastructure disciplines
- Experience in setting up public cloud infrastructure using TerraForm.
- Experience working containerized services on Kubernetes or ECS
- Experience with Python, Java, and REST APIs.
- Solid understanding of improving and debugging backend performance bottlenecks.
- Experience with application production readiness, production monitoring, and production issue triaging
- Knowledge of industry standard software best practices, development lifecycle processes, Agile tools, methodologies, and security best practices.
- Strong engineering background in deploying and scaling ML and AI Models on Public cloud services.
- Proficiency in programming languages such as Python, Java
Preferred qualifications, capabilities, and skills
- Knowledge of AWS Sagemaker and data analytics tools will be a plus.
- Ability to adapt to new technologies and learn quickly in a fast-paced environment
- Experience with Single Sign On / OIDC integration and deep understanding of OAUTH, and JWT / JWE / JWS. IDAnywhere knowledge
- Knowledge or experience with working on Azure
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