Software Engineer III - Python Backend, AI/ML Platforms on AWS

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)