What are the responsibilities and job description for the AI/ML Engineer position at STAFFXPERT LLC?
Job Title: AI/ML Engineer
Location: Milpitas, CA (Hybrid 4 days onsite)
Duration: 6 Months
Job Summary
STAFFXPERT LLC is seeking an AI/ML Engineer on behalf of our client in Milpitas, CA to join a high-impact engineering team focused on building next-generation Generative AI systems.
In this role, you will transform advanced AI architectures into scalable, production-ready systems. You will work closely with senior AI architects to develop the core intelligence layer of an enterprise AI platform, with a strong emphasis on Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and high-performance data systems.
Key Responsibilities RAG Pipeline Development
Location: Milpitas, CA (Hybrid 4 days onsite)
Duration: 6 Months
Job Summary
STAFFXPERT LLC is seeking an AI/ML Engineer on behalf of our client in Milpitas, CA to join a high-impact engineering team focused on building next-generation Generative AI systems.
In this role, you will transform advanced AI architectures into scalable, production-ready systems. You will work closely with senior AI architects to develop the core intelligence layer of an enterprise AI platform, with a strong emphasis on Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and high-performance data systems.
Key Responsibilities RAG Pipeline Development
- Design and implement end-to-end Retrieval-Augmented Generation (RAG) pipelines
- Extract and process high-quality data from PDFs, wikis, FAQs, and enterprise knowledge sources
- Develop advanced chunking strategies and metadata enrichment techniques
- Improve retrieval accuracy and relevance through iterative tuning
- Work with vector databases such as Qdrant, Pinecone, or Weaviate
- Design hybrid search systems combining keyword and semantic retrieval
- Implement efficient indexing strategies (e.g., HNSW) and optimize similarity search performance
- Build agentic workflows using frameworks such as LangGraph, Agno, or Google ADK
- Develop tools, state management systems, and inter-agent communication logic
- Orchestrate multi-agent pipelines for complex business automation use cases
- Build scalable ETL pipelines for unstructured and semi-structured data
- Transform raw content into structured, searchable knowledge bases
- Maintain data quality, versioning, and governance standards
- Evaluate system performance using frameworks such as RAGAS or LangSmith
- Optimize prompts, retrieval pipelines, and orchestration logic
- Reduce hallucinations and improve response relevance and consistency
- Containerize applications using Docker
- Deploy low-latency, production-grade AI services
- Ensure scalability, reliability, and performance optimization in production environments
- Strong proficiency in Python (including Asyncio, FastAPI, and Pydantic)
- Hands-on experience with agentic AI frameworks (LangGraph, Agno, or Google ADK)
- Experience with vector databases such as Qdrant, Weaviate, Pinecone, or similar
- Strong understanding of similarity search, embeddings, and HNSW indexing
- Experience building RAG systems and working with LLM-based applications
- Strong background in processing and structuring unstructured data sources
- Familiarity with production deployment practices for AI systems