Kafka

JPMorganChase•Jersey City, NJ

16h

About The Position

Join a team where you can play a crucial role in shaping the future of a world-renowned company and make a direct and meaningful impact in a space designed for top performers. As a Software Engineer III at JPMorgan Chase within the Cybersecurity Technology & Controls, you will join a team building model serving and agentic AI platforms on AWS. Job responsibilities Work with AWS services including Lambda, API Gateway, ECS, RDS/Aurora, DynamoDB, S3, and CloudWatch Develop backend services using Python (FastAPI, Flask) for model APIs, agent integrations, and automation workflows Contribute to building AI agent features and intelligent automation components Integrate LLM APIs (Amazon Bedrock, OpenAI) into backend services and workflows Implement message queuing and event handling using Amazon SQS, SNS, Kinesis, or Kafka (MSK) Assist in building model deployment pipelines and infrastructure automation using AWS services Write infrastructure-as-code using Terraform or AWS CloudFormation under guidance from senior engineers Implement logging and monitoring using CloudWatch, X-Ray, and other observability tools Write unit tests, integration tests, and participate in code reviews Collaborate with ML engineers and senior developers to understand requirements and implement solutions Learn and apply AWS best practices for security (IAM, VPC, Secrets Manager) and cost optimization

Requirements

Formal training or certification on software engineering concepts and 3+ years applied experience, including backend software development using Python
Working knowledge of AWS Cloud services with hands-on experience in at least 3-4 core services (Lambda, API Gateway, RDS, DynamoDB, S3, SQS/SNS, or CloudWatch)
Basic understanding of SQL databases (PostgreSQL, MySQL, or Aurora)
Experience building RESTful APIs and understanding of microservices principles
Familiarity with Docker and containerization concepts
Understanding of version control (Git) and basic CI/CD concepts
Eagerness to learn about AI/ML systems, agent-based architectures, and MLOps
Strong problem-solving mindset and attention to detail
Good communication and teamwork skills

Nice To Haves

AWS certification (Cloud Practitioner, Solutions Architect Associate, or Developer Associate)
Exposure to Kafka, Amazon Kinesis, MSK, or other messaging/streaming systems
Familiarity with LLM APIs (Amazon Bedrock, OpenAI, Anthropic) or AI frameworks (LangChain)
Basic understanding of ML model deployment, SageMaker, or MLOps concepts
Experience with Terraform or AWS CloudFormation
Knowledge of microservices architecture patterns and distributed systems
Exposure to Kubernetes (EKS) or container orchestration
Understanding of AWS security best practices (IAM roles, VPC, security groups)

Responsibilities

Work with AWS services including Lambda, API Gateway, ECS, RDS/Aurora, DynamoDB, S3, and CloudWatch
Develop backend services using Python (FastAPI, Flask) for model APIs, agent integrations, and automation workflows
Contribute to building AI agent features and intelligent automation components
Integrate LLM APIs (Amazon Bedrock, OpenAI) into backend services and workflows
Implement message queuing and event handling using Amazon SQS, SNS, Kinesis, or Kafka (MSK)
Assist in building model deployment pipelines and infrastructure automation using AWS services
Write infrastructure-as-code using Terraform or AWS CloudFormation under guidance from senior engineers
Implement logging and monitoring using CloudWatch, X-Ray, and other observability tools
Write unit tests, integration tests, and participate in code reviews
Collaborate with ML engineers and senior developers to understand requirements and implement solutions
Learn and apply AWS best practices for security (IAM, VPC, Secrets Manager) and cost optimization