Agentic AI Developer

ThunderSoft; California (MO); On-site; USD 90,000 - 130,000; Full time

Job summary

You will build AI agents capable of reasoning, tool use, orchestration, integrate with APIs, data sources, and databases, and contribute to backend services and model integrations. The role emphasizes rigorous testing and collaboration.

Ideal candidates have a CS-related degree and hands-on experience with LangChain, OpenAI APIs, PyTorch, and cloud platforms.

Qualifications

• Bachelor's degree or equivalent practical experience in a technical field.
• Experience with agentic AI or LLM orchestration frameworks.
• Experience developing multi-agent systems or AI applications involving autonomous task execution and tool use.
• Experience with OpenAI APIs, Hugging Face, Ollama, or similar platforms.
• Familiarity with RAG pipelines, vector databases, semantic search, or FAISS.
• Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience with backend frameworks such as FastAPI, Flask, or Node.js.
• Familiarity with SQL and NoSQL databases.
• Experience with Docker, CI/CD, GitHub Actions, or cloud platforms (AWS/GCP/Azure).

Responsibilities

• Develop and prototype agentic AI applications and workflows using LLMs and modern AI frameworks.
• Build AI agents capable of reasoning, tool use, task orchestration, information retrieval, and API interactions.
• Develop and integrate LLM-powered applications including RAG and multi-agent systems.
• Design and implement backend services and APIs to support AI applications and model integrations.
• Integrate LLMs with structured and unstructured data sources, APIs, databases, and software tools.
• Develop evaluation workflows to measure model and agent performance, accuracy, reliability, and tool-use behavior.
• Perform data processing, transformation, and analysis to support AI development.
• Experiment with prompt engineering, model configurations, retrieval techniques, and agent architectures.
• Write clean, maintainable, and well-tested code; participate in code reviews, testing, and CI/CD.
• Research developments in generative AI and apply relevant technologies to projects.
• Collaborate with engineers to translate requirements into functional AI solutions.

Skills

Agentic AI

LLM orchestration

Multi-agent systems

AI development tools

Education

Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems

Tools

LangChain

LangGraph

CrewAI

OpenAI APIs

Hugging Face

Ollama

RAG pipelines

vector databases

semantic search

FAISS

PyTorch

TensorFlow

scikit-learn

FastAPI

Flask

Node.js

Docker

CI/CD

GitHub Actions

AWS

GCP

Azure

SQL

NoSQL

Job description

• Develop and prototype agentic AI applications and workflows using large language models and modern AI frameworks.
• Build AI agents capable of reasoning, tool use, task orchestration, information retrieval, and interaction with external systems and APIs.
• Develop and integrate LLM-powered applications, including retrieval-augmented generation (RAG), multi-agent systems, and AI-assisted automation.
• Design and implement backend services and APIs to support AI applications and model integrations.
• Integrate LLMs with structured and unstructured data sources, APIs, databases, and software tools.
• Develop evaluation and validation workflows to measure AI model and agent performance, accuracy, reliability, and tool-use behavior.
• Perform data processing, transformation, and analysis to support AI development and evaluation.
• Experiment with prompt engineering, model configurations, retrieval techniques, and agent architectures to improve system performance.
• Write clean, maintainable, and well-tested code using modern software engineering practices.
• Troubleshoot application, model integration, and data pipeline issues.
• Participate in code reviews, testing, documentation, and continuous integration/deployment processes.
• Research emerging developments in generative AI, LLMs, agent frameworks, and AI development tools and apply relevant technologies to engineering projects.
• Collaborate with engineers and other technical stakeholders to translate requirements into functional AI solutions.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related technical field, or equivalent practical experience.
• Experience with agentic AI or LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar technologies.
• Experience developing multi-agent systems or AI applications involving autonomous task execution and tool use.
• Experience with OpenAI APIs, Hugging Face, Ollama, or other commercial or open-source LLM platforms.
• Familiarity with RAG pipelines, vector databases, semantic search, or FAISS.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience with backend frameworks such as FastAPI, Flask, or Node.js.
• Familiarity with SQL and/or NoSQL databases.
• Experience with Docker, CI/CD, GitHub Actions, or cloud platforms such as AWS, Google Cloud, or Azure.
• Exposure to AI model evaluation, benchmarking, automated validation, or data quality workflows.
• Experience using AI-assisted software development tools such as GitHub Copilot, Cursor, Claude Code, or similar tools.
• Demonstrated interest in generative AI through academic projects, hackathons, internships, research, or open-source contributions.