

Xforia Global Talent & Technology Solutions
GenAI Lead , Remote
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GenAI Lead, a long-term remote position requiring 8+ years of software engineering experience, including 3+ years in Generative AI. Key skills include Java, Python, LangChain, Kubernetes, and Azure cloud services. Leadership experience is essential.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
August 1, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Dallas, TX
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🧠 - Skills detailed
#Java #Leadership #Azure cloud #OpenSearch #Cloud #Project Management #Azure #Langchain #Databases #Regression #AI (Artificial Intelligence) #Kubernetes #Python #Scala
Role description
Job Title: GenAI Lead Developer
Location: Remote
Duration: Long Term
Job Description:-
We are looking for GenAI Lead at our onsite to lead development of production-grade AI systems powered by LLMs and autonomous agents.
Candidate should have prior experience in leading teams and large-scale engineering initiatives.
The role combines strong technical leadership, strong Project Management skills, cross team communication, architecture, and execution.
Core Responsibilities
• Design, develop, and deploy production-grade AI Agents and multi-agent systems.
• Build and maintain complex workflows using LangGraph.
• Develop and integrate MCP (Model Context Protocol) servers/clients and A2A (Agent-to-Agent) communication.
• Build scalable, distributed AI systems with a focus on performance, reliability, and fault tolerance.
• Develop RAG pipelines, context engineering strategies, and prompt engineering best practices.
• Implement AI evaluation frameworks (quality, hallucination, regression, latency, etc.).
Must Have
• 8+ years of software engineering experience with 3+ years in Generative AI/LLM applications.
• 3+ years of experience with leading teams and large-scale engineering initiatives.
• Strong Java and Python development experience (Mandatory).
• Hands-on experience with LangChain and LangGraph.
• Experience building AI Agents and multi-agent workflows.
• Experience with Kubernetes and Azure cloud services.
• Experience with Azure OpenAI (or OpenAI APIs).
• Strong understanding of Prompt Engineering and Context Engineering.
• Experience implementing RAG pipelines.
• Experience with one or more Vector Databases: Pinecone, Weaviate, FAISS, or OpenSearch.
• Experience with MCP (Model Context Protocol) and/or A2A integrations.
• Knowledge of AI evaluation techniques and frameworks.
Job Title: GenAI Lead Developer
Location: Remote
Duration: Long Term
Job Description:-
We are looking for GenAI Lead at our onsite to lead development of production-grade AI systems powered by LLMs and autonomous agents.
Candidate should have prior experience in leading teams and large-scale engineering initiatives.
The role combines strong technical leadership, strong Project Management skills, cross team communication, architecture, and execution.
Core Responsibilities
• Design, develop, and deploy production-grade AI Agents and multi-agent systems.
• Build and maintain complex workflows using LangGraph.
• Develop and integrate MCP (Model Context Protocol) servers/clients and A2A (Agent-to-Agent) communication.
• Build scalable, distributed AI systems with a focus on performance, reliability, and fault tolerance.
• Develop RAG pipelines, context engineering strategies, and prompt engineering best practices.
• Implement AI evaluation frameworks (quality, hallucination, regression, latency, etc.).
Must Have
• 8+ years of software engineering experience with 3+ years in Generative AI/LLM applications.
• 3+ years of experience with leading teams and large-scale engineering initiatives.
• Strong Java and Python development experience (Mandatory).
• Hands-on experience with LangChain and LangGraph.
• Experience building AI Agents and multi-agent workflows.
• Experience with Kubernetes and Azure cloud services.
• Experience with Azure OpenAI (or OpenAI APIs).
• Strong understanding of Prompt Engineering and Context Engineering.
• Experience implementing RAG pipelines.
• Experience with one or more Vector Databases: Pinecone, Weaviate, FAISS, or OpenSearch.
• Experience with MCP (Model Context Protocol) and/or A2A integrations.
• Knowledge of AI evaluation techniques and frameworks.





