AI Engineer Agentic AI

AI Engineer – Agentic AI

Duration: 5–6 Months
Engagement: Contract
Location:  Remote 

Job Overview

We are seeking an experienced AI Engineer – Agentic AI to design, develop, and productionize agentic AI capabilities for an active client project. The ideal candidate will have strong hands-on experience building LLM- and agent-based applications using LangChain and Python, with a proven ability to take AI solutions from prototype through production.

The engineer will work on agent orchestration, tool calling, retrieval-augmented generation (RAG), enterprise integrations, workflow management, testing, observability, and AI safety/guardrails.

Key Responsibilities

• Design and develop production-grade Agentic AI and LLM applications using LangChain and Python.
• Build AI agents capable of interacting with enterprise tools, APIs, data sources, and services.
• Develop agent orchestration, tool/function calling, structured workflows, and state-management capabilities.
• Implement RAG (Retrieval-Augmented Generation) solutions and integrate agents with enterprise data.
• Develop APIs and backend services to support AI/LLM applications.
• Integrate LLM applications with enterprise systems, databases, APIs, and external services.
• Take AI solutions from proof of concept/prototype to production-ready implementation.
• Implement testing strategies for LLM and agent-based applications.
• Build error handling, observability, monitoring, and guardrails for reliable AI applications.
• Troubleshoot and optimize agent workflows, LLM interactions, retrieval pipelines, and API integrations.
• Collaborate with engineering, product, and client teams to translate business requirements into scalable AI solutions.
• Follow best practices for security, reliability, scalability, and maintainability of enterprise AI applications.

Required Skills

• Strong hands-on experience with LangChain.
• Strong Python development experience.
• Experience building LLM / Generative AI / Agentic AI applications.
• Hands-on experience with AI agents and agent orchestration.
• Experience with tool calling / function calling.
• Experience designing structured AI workflows and state management.
• Strong understanding of RAG / Retrieval-Augmented Generation patterns.
• Experience integrating AI agents with enterprise data, APIs, and services.
• Experience developing REST APIs / backend services.
• Ability to take AI solutions from prototype to production.
• Experience with testing, observability, error handling, and guardrails for LLM applications.

Preferred / Nice-to-Have Skills

• LangSmith experience.
• LangGraph experience.
• Temporal / Temporal.io experience.
• Experience with multi-agent architectures.
• Experience with vector databases and semantic search.
• Experience with cloud-based AI/ML platforms.
• Experience deploying AI applications in enterprise production environments.

Ideal Candidate Profile

The ideal candidate is a hands-on AI engineer who understands both LLM application development and production software engineering. Candidates should be comfortable designing agent workflows, integrating tools and enterprise systems, implementing RAG, and building reliable AI applications that can operate in production environments.

Key Technology Stack

Python | LangChain | LangGraph | LLM | Generative AI | Agentic AI | RAG | Tool Calling | Function Calling | APIs | LangSmith | Temporal