Data & AI Platform Engineer

Posted Yesterday
Hiring Remotely in United States
Remote
95K-155K Annually
Senior level
Greentech • Renewable Energy
The Role
Design, build, and maintain scalable data and AI platform infrastructure including ETL pipelines, data warehouses/lakes, data modeling, SQL/Python development, and production MLOps/LLMOps (RAG, vector search, embeddings). Partner with data scientists, cloud architects, and engineers to ensure secure, observable, and auditable AI-enabled solutions and troubleshoot data quality and performance issues. Mentor junior staff.
Summary Generated by Built In

The Digital Solutions team at Brown and Caldwell (BC) is seeking a Data & AI Platform Engineer to strengthen our cloud platform, deployment, and AI/data infrastructure capabilities. This role bridges traditional MLOps and data platform engineering with the demands of production-grade AI including retrieval-augmented generation (RAG) pipelines, multi-agent orchestration, and LLMOps to support the full lifecycle of analytics, modeling, and AI-enabled delivery workflows. 

We are looking for someone with depth in platform engineering, DevOps/MLOps, and cloud infrastructure, who can also operationalize AI systems with rigor. You will partner closely with data scientists, AI engineers, cloud architects, and domain SMEs to deliver scalable, maintainable, and auditable solutions across environmental and water-resources projects. 

The Data & AI Platform Engineer role will design, develop, and maintain data pipelines and architectures that enable effective data integration, storage, and analysis. The role’s responsibilities will include data modeling, ETL development, and performance tuning of data systems. The role will also be involved in troubleshooting and resolving data-related issues with a focus on data quality and accessibility. Additionally, the role will be responsible for architecting pipelines in compliance with BC and clients’ data security and industry standards.  

Responsibilities

  • Design, create and maintain data pipelines to collect, clean, transform, and load data from various sources, including sensor data, historical records, and geospatial information to facilitate data warehousing.
  • Collaborate with interdisciplinary teams of environmental engineers, data scientists, and software developers to understand data requirements and develop scalable data solutions.
  • Participate in the design of and execute the creation and management of data warehouses, data lakes, and databases to ensure efficient data storage, retrieval, and management.
  • Develop, deploy, execute, and monitor ETL (Extract, Transform, Load) processes to support data analysis, visualization, and machine learning model training.
  • Develop and maintain data models and engage in SQL database management and querying with the objective of efficiently handling stored data.
  • Design and execute testing plans for data pipeline and data warehousing implementation efforts.
  • Implement processes for improving data quality and managing data governance for enhanced reliability and accessibility.
  • Collaborate with IT infrastructure and cybersecurity teams to implement and operate data pipelines within approved data infrastructure, performance, and security guidelines.
  • Design and execute processing tasks using Python and maintain up-to-date understanding of big data processing frameworks.
  • Perform regular data audits and updates to ensure high level of data accuracy and integrity.
  • Flexibility to adapt and execute various additional assignments based on evolving needs.

Mentorship

  • May provide mentorship, guidance, support, and knowledge-sharing to help less experienced team members develop their skills and grow within their roles.

Skills and Competencies

  • Understanding in building and optimizing data pipelines, architectures, and data sets.
  • Strong working SQL knowledge and skills in implementing and managing relational databases.
  • Proficient in ETL processes creation and management and techniques for data cleaning and validation.
  • Proficient in Python and other scripting languages applicable for data engineering.
  • Proficient with best practices for writing clean, maintainable, and scalable code while applying software engineering best practices including use of version control systems (e.g., Git).
  • Demonstrated abilities with data warehousing solutions, data lake solutions, and cloud platforms.

Experience

  • Typically, a minimum of 5 years of data engineering or related experience.
  • Typically certified in BC's SMS Framework and progressing through the SMS competencies.

Preferred Experience 

  • Hands‑on experience supporting production LLM‑ or RAG‑based systems in a platform, data, or MLOps capacity, including retrieval pipelines, vector search and embeddings, document chunking strategies, and orchestration patterns such as routing, tool use, and context management. Experience with services like Azure AI Search and agentic or multi‑agent workflows is a plus.
  • Familiarity with LLMOps practices and operational tooling, including evaluation frameworks, prompt and configuration versioning, model or output drift detection, observability, and monitoring approaches (e.g., OpenTelemetry).
  • Exposure to analytics platforms and integration‑heavy systems, including APIs, workflow orchestration tools (e.g., Airflow), and modern cloud data platforms such as Databricks or Snowflake—particularly where AI‑assisted analytics or natural‑language interfaces are used to support data exploration and insight generation.
  • Experience deploying and operating AI‑enabled or analytics-heavy services in Docker‑based containerized runtimes on managed cloud platforms, using infrastructure as code with cloud providers (Azure preferred, with AWS and GCP acceptable); Kubernetes environments (AKS or equivalent) a plus where applicable.
  • Familiarity with geospatial data and analysis, such as ESRI ArcGIS, PostGIS, or geopandas.
  • Interest or experience in environmental, water resources, or scientific computing domains, with the ability to collaborate effectively across disciplines and contribute to mentoring or supporting junior team members and interns.

Education 

  • A degree in data engineering, computer science, information technology, or related field or equivalent experience is required. 

Salary Range: The anticipated starting pay range for this position is based on the employee’s primary work location and may be more or less depending upon skills, experience, and education.  These ranges may be modified in the future.  

Location A: $95,000 - $129,000
Location B: $104,000 - $142,000
Location C: $114,000 - $155,000

You can view which BC location applies to you here. If you have any questions, please speak with your Recruiter.  

Benefits and Other Compensation:  We provide a comprehensive benefits package that promotes employee health, performance, and success which includes medical, dental, vision, short and long-term disability, life insurance, an employee assistance program, paid time off and parental leave, paid holidays, 401(k) retirement savings plan with employer match, performance-based bonus eligibility, employee referral bonuses, tuition reimbursement, pet insurance and long-term care insurance. Click here to see our full list of benefits.  

About Brown and Caldwell   

Headquartered in Walnut Creek, California, Brown and Caldwell is a full-service environmental engineering and construction services firm with 50 offices and over 2,100 professionals across North America and the Pacific. For more than 75 years, we have created leading-edge environmental solutions for municipalities, private industry, and government agencies. We strive to be the company of choice—to our clients, who benefit from our passion for delivering exceptional quality, and to our employees, present and future, who share our commitment to client service, collaboration, and innovation. Join us, and you will find a home where you can do your best work, reach new levels of expertise, and enjoy exceptional development opportunities. For more information, visit www.brownandcaldwell.com  

This position is subject to a pre-employment background check and a pre-employment drug test.   

Notice to Third Party Agencies: Brown and Caldwell does not accept unsolicited resumes from recruiters or employment agencies. In the event a recruiter or agency submits a resume or candidate without a previously signed agreement and approved engagement request with Brown and Caldwell, Brown and Caldwell reserves the right to pursue and hire those candidate(s) without any financial obligation to the recruiter or agency.    

Brown and Caldwell is proud to be an EEO/AAP Employer. Brown and Caldwell encourages protected veterans, individuals with disabilities, and applicants from all backgrounds to apply. Brown and Caldwell ensures nondiscrimination in all programs and activities in accordance with Title VI of the Civil Rights Act.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

Skills Required

  • Minimum of 5 years of data engineering or related experience
  • Proficiency in Python for data processing and pipeline tasks
  • Strong SQL skills and experience managing relational databases
  • Experience designing, developing, and maintaining ETL processes and data pipelines
  • Experience with data warehousing, data lakes, and data modeling
  • Experience with cloud platforms (Azure preferred; AWS/GCP acceptable) and cloud infrastructure
  • Experience with version control systems (e.g., Git) and software engineering best practices
  • Ability to operationalize AI/ML systems, including MLOps and production deployment practices
  • Education degree in data engineering, computer science, IT, or equivalent experience
  • Certified in BC's SMS Framework and progressing through SMS competencies
  • Hands-on experience with RAG, vector search, embeddings, retrieval pipelines, or LLM-based production systems
  • Familiarity with LLMOps practices, observability (e.g., OpenTelemetry), and evaluation/versioning tooling
  • Experience with Databricks or Snowflake and analytics/workflow orchestration tools (e.g., Airflow)
  • Experience deploying containerized services (Docker) and Kubernetes (AKS)
  • Familiarity with geospatial data tools (ESRI ArcGIS, PostGIS, geopandas)
  • Experience using infrastructure as code to manage cloud resources
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The Company
HQ: Walnut Creek, California
2,554 Employees
Year Founded: 1947

What We Do

Headquartered in Walnut Creek, Calif., Brown and Caldwell is an employee-owned firm with 2,100+ professionals serving clients locally and globally from 52 locations. We are the largest engineering and construction firm solely focused on the U.S. water and environmental sectors. Our creative designs and progressive solutions have helped municipal, federal and private organizations overcome their most complex environmental challenges. We offer a comprehensive range of engineering, scientific, consulting and construction services and all the essential ingredients® for a successful project and a standout experience. We are passionate about delivering exceptional service, collaborating with clients, adding value through innovation and building relationships that last. This passion dates back to Ken Brown and Dave Caldwell, who, since founding the company in 1947, stood out for their ability to solve engineering challenges, apply technology to emerging environmental problems, and serve their community. Service, great technical solutions, innovation. These are the qualities our founders carried forward as the world changed and the company grew into what it is today. Now, more than 75 years later, these qualities are just as important – essential, really – to Brown and Caldwell and to our clients.

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