Wastewater Process and AI Engineer

Brown and Caldwell (BC), a leading environmental engineering firm, is seeking a Wastewater Process and AI Engineer to help advance innovation and digital transformation in wastewater treatment. This unique role combines wastewater process engineering expertise with hands-on application of artificial intelligence (AI), machine learning (ML), advanced process modeling, digital twins, and process optimization to solve real-world treatment challenges. Working closely with the Director of Technical Delivery, Innovation and Transformation, the successful candidate will help develop, test, and implement innovative solutions that improve treatment performance, operational efficiency, reliability, and decision-making.

The role is intended for an engineer who is equally comfortable understanding treatment processes and data, developing new technical solutions, and working with project teams and utility clients to move those solutions from concept into practical application.

• Collect and analyze data, creating basis process models and drawings.
• Conduct evaluations of existing processes, perform data analysis and suggest optimizations.
• Prepare concise and accurate process engineering related tasks/project information.
• Under direction of senior staff, lead simple tasks for larger projects.
• Understand the requirements of Quality Management Plans (QMPs) for related projects.
• Develop chemical/physical/biological process models, analyze data to identify trends.
• Perform basic troubleshooting of facilities, identify root causes of issues, and suggest solutions.
• Perform setup of experiments, collecting data, and evaluate technologies for feasibility.
• Perform chemical/physical/biological testing, analyze and report on results.
• Learn about and support innovative solutions.
• Flexibility to adapt and execute various additional assignments based on evolving needs.
• May provide mentorship, guidance, support, and knowledge-sharing to help less experienced team members develop their skills and grow within their roles.

• Basic understanding of engineering principles, proficiency in data analysis tools, strong analytical skills.
• Understanding of BC standards.
• Skilled in technical approaches and solutions.
• Growing proficiency in process modeling and calculation skills, basic troubleshooting skills, and problem-solving abilities.

• Typically, a minimum of 2 years related work experience in process engineering or related field.
• Prior experience with process evaluations and optimizations.
• Typically will become certified in BC's Subject Matter Specialist (SMS) Framework and progress through the SMS competencies.

• 5+ years of relevant experience at the intersection of wastewater process engineering, modeling, optimization, data science, or digital technology.
• Strong understanding of wastewater treatment fundamentals, particularly biological treatment and nutrient removal.
• Ability to connect process engineering, data science, and operational needs to develop practical solutions for wastewater facilities.
• Strong analytical, problem-solving, and technical communication skills, with the ability to work across engineering, operations, technology, and project teams.
• Ability to independently develop technical approaches while collaborating with multidisciplinary teams to advance solutions from concept through implementation.
• Proficiency in Python programming for process model development and application of machine learning techniques to data-driven modeling and analysis of wastewater treatment processes.
• Experience with one or more of the following:
  • AI & Machine Learning:
    Develop and deploy AI/ML solutions for predictive analytics, anomaly detection, process monitoring, and optimization.
  • Process Engineering & Optimization:
    Apply wastewater process expertise to optimize biological treatment, nutrient removal, aeration, energy use, and chemical dosing.
  • Digital Twins & Process Modeling:
    Develop dynamic process models, digital twins, and hybrid mechanistic/AI models using real-time plant data.
  • Advanced Analytics & Control:
    Develop predictive models, real-time optimization tools, and advanced process control strategies.
  • Digital Innovation:
    Identify emerging technologies and translate innovative concepts and prototypes into practical, scalable solutions.
  • Hands-On Technical Development:
    Perform programming, data analysis, process simulation, algorithm development, model training, validation, and deployment.
  • Technical Platforms:
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