Agentic AI Developer

Tekvivid Inc
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Remote

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Application Services
Azure
Cloud Computing
Databases
Continuous Integration
Python
Machine Learning
Language Modeling
Natural Language Processing
Google Cloud Platform
Large Language Models
Multi-Agent Systems
Prompt Engineering
Generative AI
Backend
Kubernetes
Virtual Agents
REST
GPT
Docker

Job description

We are looking for an Agentic AI Developer to design, develop, and deploy AI-powered agents that can automate tasks, make decisions, and interact with various systems. The ideal candidate should have experience with Large Language Models (LLMs), Generative AI, AI Agent frameworks, and backend development. Key Responsibilities

  • Design and develop AI agents for business process automation.
  • Build and integrate applications using LLMs such as GPT, Claude, Gemini, or Llama.
  • Develop and optimize prompts, workflows, and AI agent logic.
  • Integrate AI solutions with APIs, databases, and third-party applications.
  • Implement Retrieval-Augmented Generation (RAG) and vector database solutions.
  • Monitor, test, and improve AI agent performance and accuracy.
  • Collaborate with product, engineering, and business teams to deliver AI-driven solutions.

Requirements

  • Strong proficiency in Python.
  • Experience with Generative AI and Large Language Models (LLMs).
  • Hands-on experience with Lang Chain, Lang Graph, Crew AI, Auto Gen, or similar frameworks.
  • Knowledge of Prompt Engineering and RAG architectures.
  • Experience with REST APIs and backend development.
  • Familiarity with vector databases such as Pinecone, Chroma DB, Weaviate, or FAISS.
  • Understanding of cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Experience with Git and version control systems., * Experience building and deploying AI applications in production environments.
  • Knowledge of Machine Learning and Natural Language Processing (NLP).
  • Familiarity with Docker, Kubernetes, and CI/CD pipelines.
  • Experience with multi-agent systems and workflow automation.

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