L
AI Engineer
Auburn Hills, MI
Full-time
Posted Today
Not Applicable
On-site
AIPrompt EngineeringEngineering and Information TechnologyInformation Services
Job Description
Position: AI Engineer
Location: Auburn Hills, MI
Duration: 6+ Months
Shift: Onsite
Interview Mode: Video
Job Description
We are looking for a skilled AI Engineer with experience in Generative AI, LLMs, AWS cloud services, and enterprise AI integrations. The ideal candidate will work on developing, deploying, and supporting AI-powered applications, multi-agent systems, and cloud-native AI solutions.
Key Responsibilities
AI/LLM Development & Engineering
Develop and implement AI/LLM-based applications using LangChain, LangGraph, and Model Context Protocol (MCP)
Build and optimize Retrieval-Augmented Generation (RAG) pipelines and semantic search solutions
Work on prompt engineering, agent orchestration, and AI workflow automation
Implement AI agent patterns such as ReAct, Chain-of-Thought, and multi-agent collaboration
Integrate enterprise data sources for AI-powered solutions across structured and unstructured data
AWS AI & Cloud Implementation
Develop and deploy AI solutions using Amazon Bedrock, SageMaker, Bedrock Agents, and Bedrock Knowledge Bases
Build and maintain cloud-native applications using AWS services such as Lambda, ECS Fargate, EKS, API Gateway, EventBridge, SNS/SQS, Kinesis, S3, DynamoDB, Aurora, OpenSearch, and Athena
Support infrastructure automation using Terraform, CloudFormation, and AWS CDK
Monitor application performance, observability, and cloud resource utilization using CloudWatch and related AWS monitoring tools
MLOps & AgentOps
Support MLOps and AgentOps processes for model deployment, monitoring, evaluation, and continuous improvement
Implement CI/CD pipelines and automated testing for AI applications
Ensure secure development practices including dependency scanning, logging, and API security controls
Salesforce & SaaS Integration
Integrate AI solutions with Salesforce Agentforce, Einstein, Data Cloud, and Service Cloud
Develop API integrations and support data exchange between Salesforce, AWS, and third-party platforms
Work with Apex, Flow, and Platform Events for AI-enabled business workflows
Collaboration & Support
Collaborate with architects, developers, security teams, and business stakeholders to deliver AI solutions
Participate in architecture discussions, code reviews, and technical troubleshooting
Create technical documentation and support knowledge-sharing initiatives across teams
Required Skills
Strong experience with Python and AI/ML frameworks
Hands-on experience with Generative AI, LLMs, LangChain, LangGraph, and RAG architectures
Experience with AWS AI/ML and cloud-native services
Knowledge of API integration, microservices, and distributed systems
Experience with DevOps, CI/CD, Terraform, and containerized deployments
Familiarity with Salesforce integrations is a plus
Good understanding of AI security, governance, and monitoring best practices
Location: Auburn Hills, MI
Duration: 6+ Months
Shift: Onsite
Interview Mode: Video
Job Description
We are looking for a skilled AI Engineer with experience in Generative AI, LLMs, AWS cloud services, and enterprise AI integrations. The ideal candidate will work on developing, deploying, and supporting AI-powered applications, multi-agent systems, and cloud-native AI solutions.
Key Responsibilities
AI/LLM Development & Engineering
Develop and implement AI/LLM-based applications using LangChain, LangGraph, and Model Context Protocol (MCP)
Build and optimize Retrieval-Augmented Generation (RAG) pipelines and semantic search solutions
Work on prompt engineering, agent orchestration, and AI workflow automation
Implement AI agent patterns such as ReAct, Chain-of-Thought, and multi-agent collaboration
Integrate enterprise data sources for AI-powered solutions across structured and unstructured data
AWS AI & Cloud Implementation
Develop and deploy AI solutions using Amazon Bedrock, SageMaker, Bedrock Agents, and Bedrock Knowledge Bases
Build and maintain cloud-native applications using AWS services such as Lambda, ECS Fargate, EKS, API Gateway, EventBridge, SNS/SQS, Kinesis, S3, DynamoDB, Aurora, OpenSearch, and Athena
Support infrastructure automation using Terraform, CloudFormation, and AWS CDK
Monitor application performance, observability, and cloud resource utilization using CloudWatch and related AWS monitoring tools
MLOps & AgentOps
Support MLOps and AgentOps processes for model deployment, monitoring, evaluation, and continuous improvement
Implement CI/CD pipelines and automated testing for AI applications
Ensure secure development practices including dependency scanning, logging, and API security controls
Salesforce & SaaS Integration
Integrate AI solutions with Salesforce Agentforce, Einstein, Data Cloud, and Service Cloud
Develop API integrations and support data exchange between Salesforce, AWS, and third-party platforms
Work with Apex, Flow, and Platform Events for AI-enabled business workflows
Collaboration & Support
Collaborate with architects, developers, security teams, and business stakeholders to deliver AI solutions
Participate in architecture discussions, code reviews, and technical troubleshooting
Create technical documentation and support knowledge-sharing initiatives across teams
Required Skills
Strong experience with Python and AI/ML frameworks
Hands-on experience with Generative AI, LLMs, LangChain, LangGraph, and RAG architectures
Experience with AWS AI/ML and cloud-native services
Knowledge of API integration, microservices, and distributed systems
Experience with DevOps, CI/CD, Terraform, and containerized deployments
Familiarity with Salesforce integrations is a plus
Good understanding of AI security, governance, and monitoring best practices
Source: LinkedIn
156 applicants
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