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# AI Engineer

- **Company:** Cgi Inc.
- **Location:** Houston, TX, United States
- **Salary:** $100,800.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Retrieval, Dataspaces, Decision Support Systems, Python (Programming Language), SQL Databases, Cloud Platform System, Data Ingestion, Large Language Models, Model Validation, Generative AI, Git, Data Lakes, AI Platforms, Data Lineage, Machine Learning Operations, Virtual Agents, Restful APIs, GPT, Data Pipelines, Databricks
- **Published:** September 28, 2026
- **Apply:** https://www.dice.com/job-detail/92d5dbec-c160-420d-8058-a8eb4366ecf1

## About the Role

Experience building AI assistants and decision support systems.
. Knowledge of MLOps, LLMOps, and AI governance practices.
. Experience in implementing production grade AI solutions using cloud environments.
. Databricks experience is crucial
. Good to have Microsoft AI Foundry experience

## Description

We are looking for a skilled AI Engineer with deep expertise in Agentic AI, Large Language Models (LLMs), and Databricks to help build next generation AI solutions that can transform complex business processes into AI executable workflows. The ideal candidate will have strong experience in designing and implementing Agentic AI solutions using enterprise AI platforms and modern LLM frameworks, while also possessing solid data engineering capabilities to build and support the underlying data ecosystem.
This role needs to be performed onsite at our client location in Houston, TX., Design and implement robust AI assistants capable of performing multi step reasoning and decision making.
. Translate complex business requirements and processes into AI executable workflows.
. Develop agentic architectures that coordinate data retrieval, tool usage, reasoning, and response generation.
. Design and optimize multi agent and tool based orchestration patterns.
. Build Retrieval Augmented Generation (RAG) solutions leveraging structured and unstructured enterprise data.
. Validate LLM output using prompt engineering strategies to improve accuracy, consistency, and explainability.
. Integrate LLM capabilities with enterprise data sources and business processes.
. Evaluate model performance, reliability, and scalability across business use cases.
. Measure response quality, hallucination rates, retrieval accuracy, and business effectiveness.
. Develop ETL/ELT pipelines for data ingestion, transformation, and curation.
. Build and maintain scalable data pipelines and integrate data from multiple system of records.
. Leverage Delta Lake architecture to support high quality data products.
. Ensure data lineage, traceability, and compliance requirements are met.

Technical Skills

. Python
. SQL
. Databricks
. Azure Cloud Services
. REST APIs
. Git / CI/CD