AI Engineer

November 6

🌽 Illinois – Remote

Although this job is listed in Illinois, this company may be open to hiring remote in other states.

💵 $125k - $175k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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Contruent

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Construction • Enterprise • SaaS

Contruent is a leading provider of lifecycle cost management solutions designed to optimize project spend and performance for large-scale construction projects. Their intuitive, configurable software-as-a-service (SaaS) is immediately deployable and helps engineering and construction firms enhance collaboration and visibility, thus minimizing risk and maximizing project success. With over 25 years of industry expertise, Contruent serves a wide range of industries including mining, oil and gas, infrastructure, and energy, providing tools for cost management, project controls, contract management, and more. Their solutions foster better decision-making through advanced data orchestration, executive dashboards, and integration with enterprise resource planning (ERP) systems.

201 - 500 employees

Founded 1994

🏢 Enterprise

☁️ SaaS

📋 Description

• Partner with the Manager of Data Science & AI Engineering to scope and deliver AI-driven product features and internal tools. • Design and implement machine learning and generative AI solutions using cloud services such as AWS Bedrock, SageMaker, and Amazon Q in QuickSight. • Integrate AI services into web and application layers (e.g., via REST APIs, LangChain, or Bedrock SDK). • Develop proof-of-concepts for natural language querying, document summarization, forecasting, and user experience enhancements using AI. • Work with structured and unstructured data stored in AWS RDS, SQL Server, and other data sources. • Collaborate with data engineering and analytics teams using tools like Power BI, QuickSight, and Python-based data pipelines. • Ensure responsible AI design, including model monitoring, bias testing, and performance validation. • Stay current with emerging technologies in AI (LLMs, vector databases, RAG architectures, and MLOps best practices).

🎯 Requirements

• 3–5 years of experience as an AI Engineer, Data Scientist, or Machine Learning Engineer. • Practical experience with agentic AI. • Strong proficiency in Python (e.g., NumPy, Pandas, scikit-learn, LangChain, PyTorch, or TensorFlow). • Experience with AWS AI/ML ecosystem, including Bedrock, SageMaker, Lambda, and Step Functions. • Experience with LLM integration and prompt engineering (e.g., OpenAI, Anthropic Claude, Amazon Titan, etc.). • Experience with SQL and data modeling using AWS RDS or SQL Server. • Comfort working across analytics and visualization tools such as Power BI or Amazon QuickSight (with Q). • Understanding of MLOps concepts such as versioning, CI/CD, and monitoring. • Familiarity with prompt engineering. • Experience mapping domain business problems into building deep neural networks for predictive insights. • Ability to plan and implement a training validation strategy. • Strong problem-solving skills, product mindset, and ability to translate ambiguous business requirements into deliverable AI solutions.