Job Title:Generative AI Engineer Location:Phoenix AZ (Onsite/Hybrid) Duration: 12 Months
Job Summary
We are seeking a highly skilled Generative AI Engineer with deep expertise in Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) and Agentic AI systems. The ideal candidate will have a strong foundation in Python development and proven experience in designing and deploying scalable production-grade AI solutions. This role requires strong analytical thinking system design capabilities and a passion for building intelligent next-generation AI applications.
Key Responsibilities
Design develop and deploy scalable generative AI solutions using LLMs
Build and optimize RAG pipelines leveraging vector databases and semantic search techniques
Develop and implement agentic AI systems using modern frameworks
Fine-tune prompts and optimize model performance for accuracy and efficiency
Integrate AI models into production environments via APIs and microservices
Collaborate with cross-functional teams including data engineers architects and product stakeholders
Ensure robustness scalability and reliability of AI systems in production
Stay current with emerging trends and advancements in generative AI technologies
Required Qualifications
6 years of experience in software development with a focus on AI/ML
Strong proficiency in Python for AI/ML development
Hands-on experience with LLMs (OpenAI Anthropic or open-source models)
Experience building RAG pipelines using vector databases (e.g. FAISS Pinecone Chroma)
Experience with agentic frameworks such as LangChain LangGraph or AutoGen
Strong understanding of prompt engineering embeddings and semantic search
Proven experience designing scalable production-ready AI systems
Excellent problem-solving and system design skills
Preferred Qualifications
Experience with cloud platforms such as AWS Azure or GCP
Familiarity with MLOps practices and model lifecycle management
Knowledge of data engineering pipelines and distributed systems
Experience building and consuming REST APIs and microservices
Understanding of AI governance security and compliance frameworks
Required Experience:
Senior IC
Job Title: Generative AI EngineerLocation: Phoenix AZ (Onsite/Hybrid)Duration: 12 MonthsJob SummaryWe are seeking a highly skilled Generative AI Engineer with deep expertise in Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) and Agentic AI systems. The ideal candidate will have a s...
Job Title:Generative AI Engineer Location:Phoenix AZ (Onsite/Hybrid) Duration: 12 Months
Job Summary
We are seeking a highly skilled Generative AI Engineer with deep expertise in Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) and Agentic AI systems. The ideal candidate will have a strong foundation in Python development and proven experience in designing and deploying scalable production-grade AI solutions. This role requires strong analytical thinking system design capabilities and a passion for building intelligent next-generation AI applications.
Key Responsibilities
Design develop and deploy scalable generative AI solutions using LLMs
Build and optimize RAG pipelines leveraging vector databases and semantic search techniques
Develop and implement agentic AI systems using modern frameworks
Fine-tune prompts and optimize model performance for accuracy and efficiency
Integrate AI models into production environments via APIs and microservices
Collaborate with cross-functional teams including data engineers architects and product stakeholders
Ensure robustness scalability and reliability of AI systems in production
Stay current with emerging trends and advancements in generative AI technologies
Required Qualifications
6 years of experience in software development with a focus on AI/ML
Strong proficiency in Python for AI/ML development
Hands-on experience with LLMs (OpenAI Anthropic or open-source models)
Experience building RAG pipelines using vector databases (e.g. FAISS Pinecone Chroma)
Experience with agentic frameworks such as LangChain LangGraph or AutoGen
Strong understanding of prompt engineering embeddings and semantic search
Proven experience designing scalable production-ready AI systems
Excellent problem-solving and system design skills
Preferred Qualifications
Experience with cloud platforms such as AWS Azure or GCP
Familiarity with MLOps practices and model lifecycle management
Knowledge of data engineering pipelines and distributed systems
Experience building and consuming REST APIs and microservices
Understanding of AI governance security and compliance frameworks