F2F Interview Must - "GenAI Engineer" - Alpharetta, GA (Hybrid Onsite)

Hybrid in Alpharetta, GA, US • Posted 14 hours ago • Updated 14 hours ago

Contract Corp To Corp

Contract W2

Hybrid

Depends on Experience

Fitment

Dice Job Match Score™

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Job Details

Skills

GenAi
RAG Vector
LangChain
LangGraph
document chunking
Hugging Face
Semantic search pipelines
DB Embeddings
MLOps
AWS SageMaker
Azure AI
NLP
Deep Learning
Pandas
NumPy

Summary

Role: GenAI Engineer

Locations: Alpharetta, GA (Hybrid Onsite)

Duration: 12+ Months Contract

F2F Interview MUST

Note: Candidate needs to be in the office 3-4 Days every week. Local or candidates from adjacent states only.

Role Overview:

Candidates must have experience delivering enterprise AI solutions in production environments (NOT only POC or personal projects/ Educational Projects)
We are seeking a Senior GenAI Engineer with strong experience in machine learning, generative AI and enterprise scale AI platform development.
The ideal candidate should have hands-on experience building production grade AI systems including Retrieval Augmented Generation (RAG) platforms, vector search pipelines, autonomous AI agents and scalable ML model deployment.
The role requires expertise in Python based ML development, LLM frameworks, vector databases and AI orchestration frameworks such as LangChain, LangGraph and Hugging Face.

Required Skills:

Experience with enterprise level projects only.
Strong Python development experience 7 years.
Hands-on experience with RAG Vector, DB Embeddings and document chunking, Semantic search pipelines.
Experience with LangChain, LangGraph and Hugging Face.
Experience with Pandas, NumPy and data preprocessing pipelines.
Experience deploying ML models as REST APIs and integrating AI with enterprise systems.

Preferred Skills:

Experience with Natural Language Processing NLP and Deep Learning
Familiarity with Transformers and Large Language Models LLMs
Experience with Cloud ML platforms such as Azure AI, AWS SageMaker, etc.

Nice to Have:

Experience building AI agents or autonomous systems.
Knowledge of vector databases Pinecone Weaviate Milvus FAISS.
Experience with MLOps practices Docker and Kubernetes.
Exposure to multimodal AI systems.

In compliance with the salary transparency law, the expected pay range for this role is $57.00 $62.00/hr. Actual compensation depends on experience and interview evaluation.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10120856
Position Id: 8918651
Posted 14 hours ago

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