Software Engineer III Python Backend, AIML 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 servicesincluding 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 handlingusing 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 serviceswith 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 andMLOps
• 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 toKafka 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 orMLOps 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)