Senior-Level Google AI/Data Engineer

We are privately held, are repeatedly recognized as a top place to work, and have been on the Inc. 5000 Fastest Growing Private Companies list for the last 12 years. We practice servant leadership and believe that by focusing on the success of our clients, team members, and partners, we all achieve greater success.

Credence has an immediate need for a Senior Google AI/Data Engineer to join our growing AI and Automation practice. You will serve as a technical leader and architect in our AI and Automation practice, with a focus on designing and delivering scalable AI and data solutions on Google Cloud Platform (GCP). You’ll apply deep AI/ML and data engineering expertise to architect end-to-end solutions, lead technical teams, and deliver innovative cloud-native capabilities that advance federal missions. You’ll guide model and data pipeline lifecycles, shape technical standards, and mentor mid-level engineers while collaborating with federal stakeholders and senior AI leaders.

AI Solution Architecture & Model Development

1. Lead end-to-end AI solution design and development: data prep, model architecture, training, evaluation, and production deployment using Vertex AI and Google AI tools.
2. Architect scalable ML systems leveraging best practices for security, resilience, and cost optimization.

Data Engineering & Advanced Pipeline Development

1. Architect and optimize high-throughput data pipelines using BigQuery, Dataflow, Pub/Sub, and Dataproc.
2. Establish data engineering standards for quality, lineage, and governance.

Cloud & MLOps Leadership

1. Define and implement MLOps strategy on GCP, including CI/CD for models, automated workflows, IaC (Terraform, Deployment Manager), and Kubernetes (GKE).
2. Establish monitoring, retraining, and drift detection frameworks using Cloud Monitoring and Vertex AI.

Generative AI & Agentic Systems

1. Drive adoption of generative AI and LLMs using Google’s Generative AI Studio, Vertex AI Search, and Agent Builder.
2. Architect event-driven and agentic AI systems leveraging Cloud Run, Eventarc, and serverless workflows.

Innovation & Technical Strategy

1. Evaluate emerging Google AI/ML capabilities, pilot innovative approaches, and incorporate them into federal missions.
2. Lead design reviews, mentor team members, and enforce technical rigor across projects.

Collaboration & Stakeholder Engagement

1. Partner with federal mission leaders to translate requirements into AI/data solutions.
2. Collaborate with cross-functional teams—data scientists, software engineers, and security engineers—to ensure delivery of secure, production-ready systems.

What You Bring

1. Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or a related field (PhD a plus).
2. 7+ years of hands-on experience delivering AI/ML and data engineering solutions, with at least 3+ years on GCP.
3. Expertise in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).
4. Deep knowledge of Google Cloud services: BigQuery, Dataflow, Pub/Sub, Dataproc, Vertex AI, Cloud Functions, Cloud Storage, and GKE.
5. Proven track record in architecting AI/ML pipelines and data platforms at enterprise scale.
6. Strong experience with Kubernetes, Docker, and CI/CD workflows in GCP.
7. Mastery of MLOps practices: CI/CD, automated retraining, monitoring, and explainability.
8. Experience with generative AI and LLMs in Google’s AI ecosystem.
9. Ability to lead technical teams, mentor engineers, and shape standards.
10. Strong communication skills and experience interfacing with federal stakeholders.
11. U.S. Citizenship with eligibility for DoD Secret clearance.

Preferred

1. Experience architecting agentic AI systems with Vertex AI Agent Builder and event-driven GCP services (Eventarc, Cloud Run, Cloud Functions).
2. Familiarity with Google Cloud-native IaC tools and hybrid/multi-cloud integration patterns.
3. Experience with federal mission systems, cybersecurity standards (RMF, FedRAMP), and compliance frameworks.
4. Exposure to multi-agent frameworks and reusable archetypes for scaling AI solutions across federal programs.
5. Publications, open-source contributions, or recognized expertise in AI/ML/Cloud Engineering.

Locations: Remote, McLean VA, Hanscom AFB - Bedford Mass

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