Agentic AI Developer

Cortex41; United States; Remote; USD 130,000 - 190,000; Full time

Job summary

Cortex41 is seeking an Agentic AI Developer to design, build, and deploy autonomous AI agents and workflows. You will work with LLMs, multi-agent architectures, and RAG pipelines to create AI-powered applications that understand user instructions, reason, and act with minimal human intervention.

The role involves integrating with external tools and APIs, optimizing prompts and performance, and ensuring secure, scalable production deployments in a modern cloud environment.

Qualifications

• Proficiency in Python and AI/ML development.
• Hands-on with LLMs, agents, RAG, and multi-agent architectures.
• Strong API design, tooling, and scalability mindset.

Responsibilities

• Design, develop, and deploy autonomous AI agents and multi-agent systems.
• Build agentic workflows using LangChain, LangGraph, CrewAI, AutoGen or similar frameworks.
• Develop LLM-powered apps with OpenAI, Claude, Gemini, Llama and other models.
• Implement RAG pipelines using vector databases and tooling.
• Develop AI systems with tool calling, memory management, and orchestration.
• Integrate AI agents with external APIs, databases and enterprise apps.
• Build conversational AI apps, assistants, and task automation.
• Optimize prompts, latency, and token usage; ensure monitoring and production readiness.

Skills

Python

LLMs / AI frameworks

REST APIs / FastAPI

Asynchronous programming

OOP & design

Git & Docker

Cloud deployment

Education

Bachelor's or Master's in CS/AI

Tools

LangChain

LangGraph

CrewAI

AutoGen

LlamaIndex

Qdrant

Pinecone

Weaviate

ChromaDB

Milvus

LangSmith/Langfuse

Docker

PostgreSQL

Redis

AWS/Azure/GCP

Job description

About the Role

We are looking for a skilled Agentic AI Developer to design, develop, and deploy intelligent AI agents and autonomous workflows. The ideal candidate should have hands‑on experience with Large Language Models (LLMs), AI agents, Retrieval‑Augmented Generation (RAG), multi‑agent architectures, and modern AI development frameworks.

You will be responsible for building AI‑powered applications that can understand user instructions, reason, make decisions, use external tools and APIs, and execute complex tasks with minimal human intervention.

Key Responsibilities

• Design, develop, and deploy autonomous AI agents and multi‑agent systems.
• Build agentic workflows using LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
• Develop LLM‑powered applications using OpenAI, Claude, Gemini, Llama, and other foundation models.
• Implement Retrieval‑Augmented Generation (RAG) pipelines using vector databases.
• Develop intelligent AI systems with tool calling, function calling, memory management, and planning capabilities.
• Integrate AI agents with third‑party APIs, databases, enterprise applications, and external services.
• Build conversational AI applications, AI assistants, and task automation systems.
• Implement agent orchestration, task delegation, state management, and inter‑agent communication.
• Optimize prompts, model performance, inference latency, and token consumption.
• Implement evaluation, monitoring, logging, and debugging mechanisms for AI applications.
• Ensure AI applications are scalable, secure, reliable, and production‑ready.
• Work with engineering teams to integrate AI solutions into existing products and platforms.

Required Technical Skills

• Programming
• Strong proficiency in Python.
• Experience with FastAPI, REST APIs, and asynchronous programming.
• Good understanding of OOP, data structures, and software design principles.
• Experience with Git, Docker, and Linux.
• Generative AI & LLMs
• Hands‑on experience with OpenAI API, Anthropic Claude, Google Gemini, or open‑source LLMs.
• Strong understanding of prompt engineering and context management.
• Experience with structured outputs, function calling, and tool use.
• Understanding of LLM inference, embeddings, tokenization, and model limitations.
• Agentic AI Frameworks
• Practical experience with one or more of:
• LangChain
• LangGraph
• CrewAI
• Microsoft AutoGen
• LlamaIndex
• Understanding of agent planning, reasoning, memory, tool execution, and orchestration.
• Experience building multi‑agent systems and autonomous workflows.
• RAG & Vector Databases
• Experience developing RAG‑based applications.
• Knowledge of embedding models and semantic search.
• Experience with vector databases such as:
• Qdrant
• Pinecone
• Weaviate
• ChromaDB
• Milvus
• Understanding of document processing, chunking, retrieval, reranking, and hybrid search.
• Backend & Deployment
• Experience with FastAPI or similar backend frameworks.
• Knowledge of PostgreSQL, Redis, and other databases.
• Experience with Docker and cloud deployment (AWS, Azure, or GCP).
• Understanding of authentication, API security, scalability, and distributed systems.

Preferred Skills

• Experience with Model Context Protocol (MCP).
• Knowledge of AI agent evaluation and observability tools.
• Experience with LangSmith, Langfuse, or similar platforms.
• Knowledge of fine‑tuning, LoRA, and QLoRA.
• Experience with speech‑to‑text, text‑to‑speech, and voice‑based AI agents.
• Understanding of browser automation and computer‑use agents.
• Experience with multimodal AI applications involving text, images, audio, or video.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
• 2–5 years of software development experience, preferably with hands‑on AI/ML development.
• Strong problem‑solving and analytical skills.
• Ability to independently design, develop, test,…