AI/LLM Engineer

The role requires strong Python engineering expertise and hands-on experience with modern agent frameworks, along with a solid understanding of data platforms and scalable architectures. We are looking for a highly skilled AI/LLM Engineer to design and build intelligent agent-based systems that can reason, plan, and act autonomously.

Location: New York (Need to come to office for F2F Round and work from office 3 days a week)
Requirement ID: 93120-1
Title: AI/LLM Engineer – Agent Frameworks & Intelligent Systems
Experience Required: 8-10 Years
Pay Range: $70 - $75/hr
Duration: 6 months
 
Skills:

• Digital : Artificial Intelligence (AI)
• Digital : Snowflake
• Digital : Databricks
• AI Agents

 
Role Summary
We are looking for a highly skilled AI/LLM Engineer to design and build intelligent agent-based systems that can reason, plan, and act autonomously. The role requires strong Python engineering expertise and hands-on experience with modern agent frameworks, along with a solid understanding of data platforms and scalable architectures.
 
Key Responsibilities

• Agent & AI System Development
• Design and build agent-based systems using frameworks such as LangChain, LangGraph, or similar.
• Develop intelligent components capable of reasoning, planning, and executing tasks autonomously.
• Implement advanced cognitive patterns such as ReAct (Reasoning + Acting).

LLM Capabilities & Enhancements

• Develop and integrate memory, tool usage, and context management capabilities (MCP).
• Build systems that leverage tool calling, chaining, and orchestration of LLM workflows.
• Collaborate with prompt engineers to enhance model responses and performance.

Engineering & Development

• Write high-quality, scalable code using Python (including async programming).
• Build and maintain APIs and microservices for AI/agent-based applications.
• Ensure systems are efficient, reliable, and production-ready.

Guardrails & Responsible AI

• Design and implement guardrails and safety mechanisms for LLM-driven systems.
• Ensure robust handling of edge cases, failure scenarios, and unintended outputs.

Data & Platform Integration

• Work with modern data platforms such as:
  • Snowflake
  • Databricks
  • Lakehouse Architectures
• Integrate AI solutions with enterprise data pipelines and systems.