AI Engineer (Agentic AI & LLM Platforms)

Denver, CO, US • Posted 16 days ago • Updated 16 days ago

Full Time

On-site

Depends on Experience

Fitment

Dice Job Match Score™

🛠️ Calibrating flux capacitors...

Job Details

Skills

Generative Artificial Intelligence (AI)
Large Language Models (LLMs)
Machine Learning (ML)
Artificial Intelligence
Python
React.js
Prompt Engineering
Amazon Bedrock

Summary

Role Summary

We are seeking a Full Stack AI Engineer to design, build, and deploy next-generation agentic AI applications leveraging Large Language Models (LLMs), multi-agent orchestration frameworks, and cloud-native AWS services. This role requires deep expertise in Python-based AI backends, LLM fine-tuning and integration, modern frontend frameworks, and scalable AWS deployments.

The ideal candidate will operate across the entire AI application lifecycle from model fine-tuning and agent workflow design to frontend development and production-grade cloud deployment.

Key Responsibilities

AI / Agentic Systems

Design and implement multi-agent pipeline systems for complex reasoning, orchestration, and task execution.
Develop and manage agentic workflows using frameworks such as LangChain, AWS Strands, or similar.
Fine-tune and adapt LLMs using custom enterprise data on AWS Bedrock and/or OpenAI platforms.
Implement advanced prompt engineering strategies for task decomposition, tool calling, and agent collaboration.

Backend Engineering

Build and maintain Python-based backend APIs using Flask or FastAPI.
Integrate LLM inference, vector search, memory, and agent logic into scalable backend services.
Develop ML pipelines for data preprocessing, embedding generation, evaluation, and inference.
Read, analyze, and interface with existing Java-based services or codebases as required.

Frontend Development

Develop intuitive and responsive web interfaces using React.js or Vue.js.
Integrate frontend components with AI-driven backend APIs for real-time inference and agent interactions.
Collaborate with UX and product teams to translate AI workflows into usable customer experiences.

Cloud & Deployment

Deploy and operate full-stack AI applications on AWS, leveraging:

AWS Bedrock for LLM access and fine-tuning
S3 for data and artifact storage
Lambda for serverless workflows
EC2 for scalable compute workloads

Implement secure, scalable, and cost-optimized cloud architectures.
Support CI/CD pipelines and production monitoring for AI services.

Required Skills

AI / ML

Hands-on experience with LLM fine-tuning and inference (AWS Bedrock, OpenAI).
Strong expertise in AI agent development and prompt engineering.
Experience building production-grade GenAI applications.

Agent Frameworks

Practical experience with LangChain, AWS Strands, or equivalent agent orchestration frameworks.

Backend Development

Expert-level Python skills.
Experience with Flask/FastAPI, ML pipelines, and large-scale data processing.
Ability to read and analyze Java code for integration or enhancement.

Frontend

Strong working knowledge of React.js or Vue.js.
Experience building AI-integrated web applications.

Cloud (AWS)

Hands-on experience with AWS Bedrock, S3, Lambda, EC2.
Understanding of cloud security, scalability, and performance best practices.

Nice-to-Have Skills

Deep experience in GenAI application development beyond PoCs.
Exposure to multi-agent system architectures in production environments.
Experience designing agentic workflows for enterprise-scale use cases.
Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG).
MLOps and model evaluation experience.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91131484
Position Id: 8863887
Posted 16 days ago

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AI Engineer (Agentic AI & LLM Platforms)

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Job Details

Skills

Summary

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