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
Required qualifications, capabilities, and skills
- 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
Preferred qualifications, capabilities, and skills
- 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)
