Artificial Intelligence Engineer
Marlabs
•
Alpharetta, GA
0
0
0
0
Mid-Senior level
Posted March 14, 2026
Job link
Thinking about this job
Responsibilities
Commitments
Responsibilities
- Design and build agentic AI workflows and AI-driven applications
- Develop and optimize LLM pipelines , including RAG architectures, fine-tuning, and evaluation
- Build AI agents using frameworks such as LangChain, AutoGen, or similar MCP/agent orchestration tools
- Implement retrieval systems using embeddings, vector stores, and enterprise data sources
- Integrate AI services with REST APIs and backend systems
- Deploy AI solutions across AWS and Google Cloud environments , including Vertex AI
- Troubleshoot, tune, and optimize AI pipelines and model performance
- Contribute to the development of a centralized platform supporting enterprise AI solutions Required Qualifications
Commitments
Hybrid schedule: 3 days onsite in Alpharetta, GA
Fast-paced environment with production deployment targeted for June
Not Met Priorities
What still needs stronger evidence
Requirements
- Build AI agents using frameworks such as LangChain, AutoGen, or similar MCP/agent orchestration tools
- Integrate AI services with REST APIs and backend systems
- Deploy AI solutions across AWS and Google Cloud environments , including Vertex AI
- Contribute to the development of a centralized platform supporting enterprise AI solutions Required Qualifications
- 4–7 years of experience in AI engineering, machine learning engineering, or applied data science
- Strong experience building LLM-based systems and RAG architectures
- Experience working with agentic frameworks such as LangChain, AutoGen, or similar orchestration tools
- Experience with vector databases, embeddings, and retrieval pipelines
- Strong programming ability in Python for AI/ML development
- Experience deploying AI workloads in AWS and Google Cloud environments Preferred Qualifications
- Experience building or integrating AI agents
- Experience with Google Vertex AI
- Experience with knowledge graphs and AI-driven graph navigation
- Experience with LLM fine-tuning, evaluation, and optimization
- Collaborative engineering team building enterprise AI infrastructure
- Fast-paced environment with production deployment targeted for June
Preferred Skills
- Experience deploying AI workloads in AWS and Google Cloud environments Preferred Qualifications
- Experience with Google Vertex AI
- Experience with knowledge graphs and AI-driven graph navigation
- Experience with LLM fine-tuning, evaluation, and optimization
- Collaborative engineering team building enterprise AI infrastructure
Education
- (Not required) – 4–7 years of experience in AI engineering, machine learning engineering, or applied data science
- (Not required) – Master's degree in Computer Science, AI, Machine Learning, Data Science, or related technical field Work Environment
AI Engineer (Agentic AI / LLM Platforms) Location: Alpharetta, GA (Hybrid) In-person Interview required Overview We are seeking AI Engineers with strong data science and applied AI expertise to support the development of a large-scale enterprise AI platform. This platform will host internal AI solutions and requires engineers who understand the entire AI development pipeline , including LLM orchestration, retrieval architectures, and agentic workflows. This role is not focused on traditional software engineering . The team is looking for engineers who deeply understand how AI systems work and how to troubleshoot and optimize them , not just how to operate AI tools. The platform is targeted for production deployment by June , so candidates must be capable of contributing quickly in a fast-paced engineering environment. Responsibilities
Design and build agentic AI workflows and AI-driven applications
Develop and optimize LLM pipelines , including RAG architectures, fine-tuning, and evaluation
Build AI agents using frameworks such as LangChain, AutoGen, or similar MCP/agent orchestration tools
Implement retrieval systems using embeddings, vector stores, and enterprise data sources
Integrate AI services with REST APIs and backend systems
Deploy AI solutions across AWS and Google Cloud environments , including Vertex AI
Troubleshoot, tune, and optimize AI pipelines and model performance
Contribute to the development of a centralized platform supporting enterprise AI solutions Required Qualifications
4–7 years of experience in AI engineering, machine learning engineering, or applied data science
Strong experience building LLM-based systems and RAG architectures
Experience working with agentic frameworks such as LangChain, AutoGen, or similar orchestration tools
Experience with vector databases, embeddings, and retrieval pipelines
Strong programming ability in Python for AI/ML development
Experience deploying AI workloads in AWS and Google Cloud environments Preferred Qualifications
Experience building or integrating AI agents
Experience with Google Vertex AI
Experience with knowledge graphs and AI-driven graph navigation
Experience with LLM fine-tuning, evaluation, and optimization
Master's degree in Computer Science, AI, Machine Learning, Data Science, or related technical field Work Environment
Hybrid schedule: 3 days onsite in Alpharetta, GA
Collaborative engineering team building enterprise AI infrastructure
Fast-paced environment with production deployment targeted for June
Design and build agentic AI workflows and AI-driven applications
Develop and optimize LLM pipelines , including RAG architectures, fine-tuning, and evaluation
Build AI agents using frameworks such as LangChain, AutoGen, or similar MCP/agent orchestration tools
Implement retrieval systems using embeddings, vector stores, and enterprise data sources
Integrate AI services with REST APIs and backend systems
Deploy AI solutions across AWS and Google Cloud environments , including Vertex AI
Troubleshoot, tune, and optimize AI pipelines and model performance
Contribute to the development of a centralized platform supporting enterprise AI solutions Required Qualifications
4–7 years of experience in AI engineering, machine learning engineering, or applied data science
Strong experience building LLM-based systems and RAG architectures
Experience working with agentic frameworks such as LangChain, AutoGen, or similar orchestration tools
Experience with vector databases, embeddings, and retrieval pipelines
Strong programming ability in Python for AI/ML development
Experience deploying AI workloads in AWS and Google Cloud environments Preferred Qualifications
Experience building or integrating AI agents
Experience with Google Vertex AI
Experience with knowledge graphs and AI-driven graph navigation
Experience with LLM fine-tuning, evaluation, and optimization
Master's degree in Computer Science, AI, Machine Learning, Data Science, or related technical field Work Environment
Hybrid schedule: 3 days onsite in Alpharetta, GA
Collaborative engineering team building enterprise AI infrastructure
Fast-paced environment with production deployment targeted for June