Overview
Skills
Job Details
Role: AI/ML Engineer
Duration: 6+ months
Location: Remote
Top 3 Required Technical Skills:
AI/ML**: Amazon Bedrock, AgentCore, LangChain, vector databases
- **AWS Services**: Lambda, API Gateway, Step Functions, EventBridge, S3, DynamoDB
- **Languages**: Python, TypeScript, SQL
- **Infrastructure**: AWS CDK, CloudFormation, Docker
- **Monitoring**: CloudWatch, X-Ray, custom metrics and dashboards
Organization/Team Culture: Culture is trying to advance it's technical maturity in advanced engineering practices and technology stacks. Not interested in someone who does not have a desire to do quality work, prove themselves or collaborate. The right fit is someone who geeks out a bit on technology and understands how to troubleshoot and solve problems on their own. Ideal candidate could be a long term consultants.
Environment will be flexible with people if they are an A player.
Team Size/Structure: This is a growing team of Engineering working on multiple POC's in AI within 8 Digital Data Products
Specific Industry/Company experience required: Ag experience could be a great touch.
Job Description:
- Design and implement agentic AI systems using Amazon Bedrock and AgentCore
- Build multi-agent orchestration platforms with tool integration (MCP, function calling)
- Architect enterprise AI solutions with proper security, monitoring, and governance
- Develop AI agents that autonomously execute complex business workflows
- Integrate AI systems with existing enterprise applications and data sources
- Optimize agent performance, reliability, and cost efficiency
- Collaborate with product teams to translate business requirements into AI solutions
Key Requirements:
- 5+ years software engineering experience with 2+ years in AI/ML systems
- Deep expertise with Amazon Bedrock (Claude, Titan, custom models)
- Hands-on experience with AWS AgentCore or similar agent frameworks
- Strong AWS architecture skills (Lambda, API Gateway, Step Functions, EventBridge)
- Experience building production AI systems with proper MLOps practices
- Proficiency in Python, TypeScript/JavaScript, and infrastructure as code (CDK/Terraform)
- Understanding of LLM prompt engineering, RAG, and fine-tuning techniques
- Experience with enterprise security, compliance, and governance requirements
Technical Stack
- **AI/ML**: Amazon Bedrock, AgentCore, LangChain, vector databases
- **AWS Services**: Lambda, API Gateway, Step Functions, EventBridge, S3, DynamoDB
- **Languages**: Python, TypeScript, SQL
- **Infrastructure**: AWS CDK, CloudFormation, Docker