AI Engineer

Job Description AI Engineer
Location: Salt Lake City UT (Hybrid 4 days onsite)
Duration: Full-time
Note: Please apply only US Citizen and Green Card Holder

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 production ready.

AI Engineers work closely with product owners data engineers software engineers and client stakeholders to translate requirements into intelligent systems.

Key Responsibilities

1. 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
• Fine tune models using techniques like LoRA and QLoRA
• Build AI powered features such as:
  • Chatbots and virtual assistants
  • Text summarization and extraction
  • Question answering systems
  • Speech to Text and Text to Speech solutions

2. 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

3. Prompt Engineering

• Design and optimize prompts for:
  • Text summarization
  • Information extraction
  • Question & Answer systems
• Apply advanced prompting techniques such as:
  • Few shot prompting
  • Chain of Thought (CoT)
  • Knowledge base grounded prompts

4. Data & Backend Integration

• Work with relational and NoSQL databases:
  • MS SQL Server MySQL PostgreSQL MongoDB Cassandra HBase
• Build AI services and APIs using Python based frameworks
• Integrate AI models with enterprise applications and workflows
• Ensure data quality security and compliance in AI pipelines

5. 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 AI assisted development tools such as Microsoft Copilot to accelerate development responsibly

Required Technical Skills

Programming & Frameworks

• Strong proficiency in Python
  • NumPy Pandas Scikit learn TensorFlow PyTorch spaCy NLTK
• Experience building production grade 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 fine tuning and evaluation tools

Nice to Have 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 problem solving and analytical thinking
• Ability to translate business problems into AI solutions
• Excellent communication with technical and non technical stakeholders
• Fast learner with a mindset to adapt to evolving AI technologies

Typical Experience Range

• 3 6 years for mid level AI Engineer
• 7 years for senior / lead AI Engineer roles (with hands on AI/ML and GenAI experience)