Sr. Software Engineer AWS & AI
Description:
Sr. Software Engineer AWS & AI
If the candidate completes the assessment and does well we have a 3 hour block for screening on Monday.
Hybrid - malvern pa -
Senior Software Engineer (AWS & AI)
About the Role
We are seeking a hands-on Senior Software Engineer with deep experience in AWS cloud-native development and emerging AI technologies. This role blends software architecture, full-stack engineering, optimized hands-on development and applied AI with a strong focus on LLM-driven use cases and Proofs of Concept that advance our digital experience capabilities. You will define the technical approach, lead implementation, implement/code solutions and help shape the future of AI adoption across the enterprise.
Responsibilities:
- Architect, design, and develop AI-powered applications and services leveraging AWS Bedrock and other AWS native services (Lambdas, Glue, S3, Athena, Kinesis(Not needed), AWS Textract and other AWS AI services like Amazon Q etc.).
- Explore, evaluate, and operationalize LLM and agent-based solutions for real business workflows.
- Enhance and operationalize existing AI POCs into scalable production systems.
- Build secure, well-architected microservices using Python and/or Java, UI coding languages would be a value add.
- Integrate with AWS Bedrock agents, embeddings, and foundation models via secure APIs.
- Partner with Product, Architecture, Security, and Data Science to shape AI solution strategy.
- Implement cloud solutions using AWS Lambda, ECS, EC2, RDS, IAM, SQS, SNS, API Gateway, Step Functions, DynamoDB, and more.
- Maintain AWS best practices for performance, resiliency, and cost optimization.
- Support and contribute to existing non-AI platform modernization initiatives when needed.
- Drive software engineering excellence through code reviews, standards, and automation.
Technical Skills
- 8+ years software development experience with Python (primary) and Java.
- Strong AWS engineering expertise in AWS Bedrock (Hands-on required: agents, embeddings, model orchestration) along with AWS Textract and other AWS AI services.
- Strong AWS engineering expertise in AWS Lambdas, IAM, API development, and authentication patterns.
- Solid practical understanding of Agentic architectures, LLM evaluation, and Cloud-native and event-driven architectures.
- Strong grasp of general engineering patterns (microservices, CI/CD, observability).
- Strong monitoring tool experience with Splunk or similar tools.
-Strong in solving the complex coding problem and build optimized solutions.
- Ability to independently drive technical decisions from concept to deployment.
- Strong architectural and solution design background.
- Experience collaborating in Agile engineering teams.
- Excellent communication and problem-solving skills.
Good to Have
- Experience with Vector Databases (Pinecone, Aurora Postgres pgvector).
- Familiarity with GraphQL, container orchestration (ECS, EKS).
- Prior experience in financial services, Operations process or regulated industries.
- Knowledge of evaluation frameworks and responsible AI practices.
Job Responsibilities
Responsibilities:
- Architect, design, and develop AI-powered applications and services leveraging AWS Bedrock and other AWS native services (Lambdas, Glue, S3, Athena, Kinesis(Not needed), AWS Textract and other AWS AI services like Amazon Q etc.).
- Explore, evaluate, and operationalize LLM and agent-based solutions for real business workflows.
- Enhance and operationalize existing AI POCs into scalable production systems.
- Build secure, well-architected microservices using Python and/or Java, UI coding languages would be a value add.
- Integrate with AWS Bedrock agents, embeddings, and foundation models via secure APIs.
- Partner with Product, Architecture, Security, and Data Science to shape AI solution strategy.
- Implement cloud solutions using AWS Lambda, ECS, EC2, RDS, IAM, SQS, SNS, API Gateway, Step Functions, DynamoDB, and more.
- Maintain AWS best practices for performance, resiliency, and cost optimization.
- Support and contribute to existing non-AI platform modernization initiatives when needed.
- Drive software engineering excellence through code reviews, standards, and automation.