Generative AI (Gen AI) Architect || Raritan, NJ (Onsite)

Raritan, NJ, US • Posted 1 hour ago • Updated 16 minutes ago
Contract Corp To Corp
Contract W2
Contract Independent
Travel Required
On-site
$85/hr
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Python
  • Open Source
  • LangChain
  • Semantics
  • Cloud Computing
  • Amazon Web Services
  • Vertex
  • Vector Databases
  • Microsoft Azure
  • Enterprise Integration
  • Generative Artificial Intelligence (AI)
  • Database
  • Privacy
  • Access Control
  • Artificial Intelligence
  • Performance Tuning
  • Scalability
  • Machine Learning Operations (ML Ops)
  • Continuous Integration
  • Continuous Delivery
  • Evaluation
  • IT Management
  • Design Review
  • Mentorship
  • Collaboration

Summary

Position: Generative AI (GenAI) Architect

Location: Raritan, NJ (Onsite)

Live Python Coding test during the Interview

Job Description :

Key Responsibilities

  • GenAI Architecture: Design end-to-end architectures for Generative AI applications, including LLMs, RAG pipelines, AI agents, and multi-agent systems.
  • LLM Integration: Work with models such as GPT, Claude, Gemini, and open-source models like Llama.
  • RAG Implementation: Build document ingestion, chunking, embedding, vector search, retrieval, reranking, and response-generation pipelines.
  • AI Agent Development: Design intelligent agents using frameworks such as LangChain, LangGraph, and Semantic Kernel.
  • Cloud AI Solutions: Architect and deploy solutions using Azure OpenAI, AWS Bedrock, or Google Vertex AI.
  • Vector Databases: Integrate vector stores such as Pinecone, Azure AI Search, Weaviate, or FAISS.
  • Enterprise Integration: Connect GenAI applications with APIs, databases, enterprise systems, and knowledge repositories.
  • Security and Governance: Implement data privacy, access controls, responsible AI practices, guardrails, and protection against prompt injection.
  • Performance Optimization: Optimize model latency, token consumption, inference costs, scalability, and response quality.
  • MLOps and LLMOps: Establish CI/CD pipelines, model evaluation, monitoring, observability, and production deployment practices.
  • Technical Leadership: Define architecture standards, conduct design reviews, mentor developers, and collaborate with business and engineering teams.

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: 10457702
  • Position Id: 2026-39385
  • Posted 1 hour ago
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