AI/LLM Engineer

About the role

We are seeking a highly skilled AI/LLM Engineer to design, develop, and deploy intelligent agent-based systems capable of reasoning, planning, and executing tasks autonomously.

Responsibilities

• Agent & AI System Development
  • Design and develop AI agent systems using LangChain, LangGraph, or similar frameworks.
  • Build intelligent components capable of reasoning, planning, and autonomous task execution.
  • Implement agentic patterns such as ReAct (Reasoning + Acting).
  • Develop multi-step LLM workflows and agent orchestration.
• LLM Capabilities & Enhancements
  • Implement memory, tool usage, context management, and MCP capabilities.
  • Develop solutions using tool calling, chaining, and workflow orchestration.
  • Work with prompt engineering teams to improve LLM response quality and performance.
  • Optimize LLM applications for scalability, reliability, and cost.
• Software Engineering
  • Develop high-quality, scalable, and maintainable Python applications, including asynchronous programming.
  • Build and maintain APIs and microservices for AI and agent-based applications.
  • Integrate AI services with enterprise applications and backend systems.
  • Develop production-ready solutions with appropriate testing, monitoring, and error handling.
• Guardrails & Responsible AI
  • Design and implement guardrails and safety mechanisms for LLM-powered applications.
  • Handle edge cases, failures, hallucinations, and unintended model outputs.
  • Implement appropriate validation, security, and access controls for AI systems.
• Data & Platform Integration
  • Integrate AI solutions with modern data platforms, including Snowflake and Databricks.
  • Work with Lakehouse architectures and enterprise data pipelines.
  • Enable LLM applications to securely access and leverage enterprise data.
  • Collaborate with Data Engineering, ML Engineering, and Cloud teams on scalable AI architectures.

Requirements

• 5+ years of experience in software engineering, AI/ML engineering, or a related field.
• Strong hands-on experience with Python and asynchronous programming.
• Experience building LLM and generative AI applications.
• Strong experience with LangChain, LangGraph, or similar agent frameworks.
• Understanding of AI agents, ReAct, tool calling, memory, context management, and MCP.
• Experience developing REST APIs and microservices.
• Experience integrating AI applications with Snowflake, Databricks, or Lakehouse platforms.
• Strong understanding of scalable, production-ready software architectures.
• Knowledge of LLM guardrails, responsible AI, security, and failure handling.
• Strong problem-solving, communication, and collaboration skills.

Preferred Skills

• Experience with multi-agent systems and agent orchestration.
• Knowledge of vector databases and RAG architectures.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with LLM observability, evaluation, and performance optimization.
• Experience deploying AI applications in enterprise production environments.