Lead Cloud Data & AI Engineer / Solutions Architect

Job Title: Lead Cloud Data & AI Engineer / Solutions Architect (GCP)



Location: Reston, VA Onsite



Openings: 4



Duration: 6+ Months, with possibility of extension



Work Model: Onsite / Customer deployments as needed Job Summary

We are seeking an experienced Lead Cloud Data & AI Engineer / Solutions Architect with deep expertise in Google Cloud Platform (GCP), enterprise data architecture, AI/ML, and modern data engineering.

The ideal candidate will bring strong hands-on technical expertise along with the ability to lead architecture discussions, advise stakeholders, and design scalable cloud data and AI solutions for complex, security-conscious environments.

Key Responsibilities

• Design and architect scalable cloud-based data and AI solutions using GCP.
• Build and optimize large-scale data pipelines, lakehouse architectures, and distributed data platforms.
• Develop solutions using BigQuery, Dataflow, Dataproc, Cloud Composer, Pub/Sub, and dbt .
• Design and optimize relational and distributed database environments.
• Support database performance tuning, replication, modernization, and migration initiatives.
• Develop, deploy, and operationalize machine learning models and LLM-based pipelines.
• Implement and support MLOps practices for production AI/ML workloads.
• Provide technical leadership and architectural guidance to engineering and business stakeholders.
• Conduct technical workshops, architecture reviews, and solution-design sessions.
• Design solutions appropriate for highly regulated, security-conscious, and public-sector environments.

Required Qualifications

• 10+ years of experience working with relational and/or distributed database technologies.
• Advanced hands-on experience with the Google Cloud data ecosystem .
• Strong expertise in BigQuery , including architecture, IAM, performance, and large-scale data processing.
• Experience with Dataflow / Apache Beam .
• Experience with Dataproc, Serverless Spark, and PySpark .
• Experience with Cloud Composer / Apache Airflow .
• Experience with Pub/Sub and dbt .
• Strong database experience with technologies such as PostgreSQL, AlloyDB, Oracle, and Cloud SQL .
• Experience with database performance tuning, replication, and migrations.
• Strong programming experience with Python .
• Experience developing and operationalizing AI/ML models and LLM pipelines .
• Experience with frameworks and tooling such as PyTorch, TensorFlow, and MLOps platforms .
• Familiarity with security and compliance requirements applicable to highly regulated or public-sector cloud environments, including environments aligned with standards such as DoD IL5/IL6 .
• Excellent stakeholder communication, technical advisory, architecture consulting, and workshop facilitation skills.

Preferred Qualifications

GCP Professional certifications such as Professional Data Engineer, Professional Machine Learning Engineer, Professional Cloud Architect, or Professional Cloud Database Engineer are preferred.