Contract || AI/ML Engineer || Austin, TX || Charlotte, NYC (Hybrid: 3 days onsite, 2 days remote)

Hi,
 
Hope you are doing well!
 
If you are interested, please share given below details:

• Updated resume..?
• Visa status..?
• Rate expectation..?
• Current Location..?

1st round of interview is Hacker rank Coding test; this is Mandatory for this role.

So, if you are not comfortable to do Hacker rank test then please ignore this role.

Job Title: AI/ML Engineer
Location: Austin, TX || Charlotte, NYC (Hybrid: 3 days onsite, 2 days remote)
Job Type: Contract 
 
Interview Process:
1st Round Hacker Rank Coding Test
2nd round – Internal L2 and L3
3rd Round: Client Interview

Job description

We are seeking a highly skilled AI Engineer with hands-on experience in agent development, Retrieval-Augmented Generation (RAG), agentic workflows, and platforms such as Cursor AI. The ideal candidate will have a strong developer mindset and expertise in integrating APIs and building intelligent systems that can reason, act, and interact across tools and data sources.

Key Responsibilities

• Design, develop, and optimize AI agents capable of reasoning, decision-making, and tool usage
• Implement and fine-tune RAG pipelines for contextual knowledge integration
• Develop, integrate, and manage agentic workflows across APIs, vector stores, and third-party tools
• Leverage Cursor AI and similar platforms to prototype and deploy agent-based applications
• Collaborate with product teams to implement AI-driven features with seamless developer experience
• Build scalable APIs for model access, integration, and service orchestration
• Stay updated with the latest in LLMs, agent orchestration frameworks, and AI tooling

Required Skills & Qualifications

• Strong programming skills in Python or equivalent (Go/Node.js is a plus)
• Experience in developing autonomous agents and agentic workflows using frameworks like LangChain, AutoGen, or similar
• Hands-on with Cursor AI for development, debugging, and agent orchestration
• Experience building and consuming RESTful APIs
• Proficiency in RAG architectures, including vector stores (e.g., FAISS, Pinecone, Weaviate), embedding models, and retrieval tuning
• Experience with prompt engineering, tool calling, and multi-agent collaboration setups
• Solid understanding of LLMs, their fine-tuning strategies, and evaluation frameworks