← Serch more jobs

AI Engineer (Fulltime)

Jobs via Dice • Salt Lake City, UT

Not Applicable Posted April 2, 2026 Job link

Thinking about this job

Responsibilities

Commitments

Responsibilities

AI & Generative AI Development
Design and build AI and Generative AI solutions using LLMs, NLP, and deep learning models
Develop applications using OpenAI APIs, Azure OpenAI, HuggingFace, LangChain, Amazon Bedrock, and similar platforms
Implement Retrieval Augmented Generation (RAG) pipelines using vector databases such as FAISS and Pinecone
Finetune models using techniques like LoRA and QLoRA
Build AIpowered features such as:
Chatbots and virtual assistants
Text summarization and extraction
Build and deploy ML models using:
Regression and classification algorithms
Neural networks and ensemble techniques
Develop deep learning models using TensorFlow, PyTorch, CNNs, RNNs, LSTMs, GANs, BERT and transformer architectures
Evaluate model performance using metrics such as Perplexity, BLEU, and ROUGE
Prompt Engineering
Design and optimize prompts for:
Text summarization
Information extraction
Question & Answer systems
Apply advanced prompting techniques such as:
ChainofThought (CoT)
Knowledgebase grounded prompts
Data & Backend Integration
Work with relational and NoSQL databases:
MS SQL Server, MySQL, PostgreSQL, MongoDB, Cassandra, HBase
Build AI services and APIs using Pythonbased frameworks
Integrate AI models with enterprise applications and workflows
Ensure data quality, security, and compliance in AI pipelines
Production & Cloud Readiness
Deploy AI solutions on cloud platforms (Azure / AWS preferred)
Implement scalable and secure AI architectures
Monitor, optimize, and retrain models as required
Use AIassisted development tools such as Microsoft Copilot to accelerate development responsibly

Not Met Priorities

What still needs stronger evidence

Requirements

AI & Generative AI Development
Design and build AI and Generative AI solutions using LLMs, NLP, and deep learning models
Develop applications using OpenAI APIs, Azure OpenAI, HuggingFace, LangChain, Amazon Bedrock, and similar platforms
Text summarization and extraction
Machine Learning & Deep Learning
Supervised and unsupervised learning
Regression and classification algorithms
Neural networks and ensemble techniques
Develop deep learning models using TensorFlow, PyTorch, CNNs, RNNs, LSTMs, GANs, BERT and transformer architectures
Evaluate model performance using metrics such as Perplexity, BLEU, and ROUGE
Prompt Engineering
Text summarization
Information extraction
MS SQL Server, MySQL, PostgreSQL, MongoDB, Cassandra, HBase
Production & Cloud Readiness
Deploy AI solutions on cloud platforms (Azure / AWS preferred)
Use AIassisted development tools such as Microsoft Copilot to accelerate development responsibly
Programming & Frameworks
Strong proficiency in Python
NumPy, Pandas, Scikitlearn, TensorFlow, PyTorch, spaCy, NLTK
Experience building productiongrade AI pipelines
AI / ML / GenAI
LLMs and Generative AI
NLP techniques
RAG architectures
Embeddings (Word2Vec, GloVe, ELMo)
Vector databases
Cloud & Tools
Azure OpenAI / AWS Bedrock
HuggingFace ecosystem
LangChain
Model finetuning and evaluation tools
NicetoHave Skills
Experience with enterprise AI platforms
Knowledge of MLOps pipelines
Understanding of AI governance, ethics, and security
Prior experience in financial services or enterprise domains
Strong problemsolving and analytical thinking
Ability to translate business problems into AI solutions
Excellent communication with technical and nontechnical stakeholders
Fast learner with a mindset to adapt to evolving AI technologies
3-6 years for midlevel AI Engineer
7+ years for senior / lead AI Engineer roles (with handson AI/ML and GenAI experience)

Preferred Skills

Supervised and unsupervised learning
Regression and classification algorithms
Neural networks and ensemble techniques
Prompt Engineering
Text summarization
Information extraction
Question & Answer systems
ChainofThought (CoT)
Model finetuning and evaluation tools
NicetoHave Skills
Experience with enterprise AI platforms
Knowledge of MLOps pipelines
Understanding of AI governance, ethics, and security
Prior experience in financial services or enterprise domains
Ability to translate business problems into AI solutions
Excellent communication with technical and nontechnical stakeholders
Fast learner with a mindset to adapt to evolving AI technologies

Education

(Not required) – 3-6 years for midlevel AI Engineer

Dice is the leading career destination for tech experts at every stage of their careers. Our client, 4i Americas, is seeking the following. Apply via Dice today!
Job Description - AI Engineer
Location: Salt Lake City, UT
Duration: 12 Months Contract
Role Overview
An AI Engineer is responsible for designing, building, deploying, and optimizing AI, Machine Learning, and Generative AI solutions that solve real business problems. This role bridges data, models, and applications , ensuring AI solutions are scalable, reliable, and productionready.
AI Engineers work closely with product owners, data engineers, software engineers, and client stakeholders to translate requirements into intelligent systems.
Key Responsibilities

AI & Generative AI Development
Design and build AI and Generative AI solutions using LLMs, NLP, and deep learning models
Develop applications using OpenAI APIs, Azure OpenAI, HuggingFace, LangChain, Amazon Bedrock, and similar platforms
Implement Retrieval Augmented Generation (RAG) pipelines using vector databases such as FAISS and Pinecone
Finetune models using techniques like LoRA and QLoRA
Build AIpowered features such as:
Chatbots and virtual assistants
Text summarization and extraction
Questionanswering systems
SpeechtoText and TexttoSpeech solutions
Machine Learning & Deep Learning
Build and deploy ML models using:
Supervised and unsupervised learning
Regression and classification algorithms
Neural networks and ensemble techniques
Develop deep learning models using TensorFlow, PyTorch, CNNs, RNNs, LSTMs, GANs, BERT and transformer architectures
Evaluate model performance using metrics such as Perplexity, BLEU, and ROUGE
Prompt Engineering
Design and optimize prompts for:
Text summarization
Information extraction
Question & Answer systems
Apply advanced prompting techniques such as:
Fewshot prompting
ChainofThought (CoT)
Knowledgebase grounded prompts
Data & Backend Integration
Work with relational and NoSQL databases:
MS SQL Server, MySQL, PostgreSQL, MongoDB, Cassandra, HBase
Build AI services and APIs using Pythonbased frameworks
Integrate AI models with enterprise applications and workflows
Ensure data quality, security, and compliance in AI pipelines
Production & Cloud Readiness
Deploy AI solutions on cloud platforms (Azure / AWS preferred)
Implement scalable and secure AI architectures
Monitor, optimize, and retrain models as required
Use AIassisted development tools such as Microsoft Copilot to accelerate development responsibly
Required Technical Skills
Programming & Frameworks

Strong proficiency in Python
NumPy, Pandas, Scikitlearn, TensorFlow, PyTorch, spaCy, NLTK
Experience building productiongrade AI pipelines
AI / ML / GenAI

LLMs and Generative AI
NLP techniques
RAG architectures
Embeddings (Word2Vec, GloVe, ELMo)
Vector databases
Cloud & Tools

Azure OpenAI / AWS Bedrock
HuggingFace ecosystem
LangChain
Model finetuning and evaluation tools
NicetoHave Skills

Experience with enterprise AI platforms
Knowledge of MLOps pipelines
Understanding of AI governance, ethics, and security
Prior experience in financial services or enterprise domains
Soft Skills & Expectations

Strong problemsolving and analytical thinking
Ability to translate business problems into AI solutions
Excellent communication with technical and nontechnical stakeholders
Fast learner with a mindset to adapt to evolving AI technologies
Typical Experience Range

3-6 years for midlevel AI Engineer
7+ years for senior / lead AI Engineer roles (with handson AI/ML and GenAI experience)