Credence company
Overview
Credence is seeking a Senior Google AI/Data Engineer to join our growing AI and Automation practice. The role focuses on designing and delivering scalable AI and data solutions on Google Cloud Platform (GCP). You will guide model and data pipeline life-cycles, shape technical standards, mentor mid-level engineers, and collaborate with federal stakeholders and senior AI leaders. Responsibilities 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. Architect scalable ML systems with security, resilience, and cost optimization in mind. Architect and optimize high-throughput data pipelines using BigQuery, Dataflow, Pub/Sub, and Dataproc. Establish data engineering standards for quality, lineage, and governance. Define and implement MLOps strategy on GCP, including CI/CD for models, automated workflows, IaC (Terraform, Deployment Manager), and Kubernetes (GKE). Establish monitoring, retraining, and drift detection frameworks using Cloud Monitoring and Vertex AI. Drive adoption of generative AI and LLMs using Googles Generative AI Studio, Vertex AI Search, and Agent Builder. Architect event-driven and agentic AI systems leveraging Cloud Run, Eventarc, and serverless workflows. Evaluate emerging Google AI/ML capabilities, pilot innovative approaches, and incorporate them into federal missions. Lead design reviews, mentor team members, and enforce technical rigor across projects. Partner with federal mission leaders to translate requirements into AI/data solutions. Collaborate with cross-functional teamsdata scientists, software engineers, and security engineersto deliver secure, production-ready systems.
Education, Requirements and Qualifications What You Bring
Bachelors or Masters in Computer Science, AI/ML, Data Science, or a related field (PhD a plus). 7+ years of hands-on experience delivering AI/ML and data engineering solutions, with at least 3+ years on GCP. Expertise in Python and ML libraries (TensorFlow, PyTorch, scikit-learn). Deep knowledge of Google Cloud services: BigQuery, Dataflow, Pub/Sub, Dataproc, Vertex AI, Cloud Functions, Cloud Storage, and GKE. Proven track record in architecting AI/ML pipelines and data platforms at enterprise scale. Strong experience with Kubernetes, Docker, and CI/CD workflows in GCP. Mastery of MLOps practices: CI/CD, automated retraining, monitoring, and explainability. Experience with generative AI and LLMs in Googles AI ecosystem. Ability to lead technical teams, mentor engineers, and shape standards. Strong communication skills and experience interfacing with federal stakeholders. U.S. Citizenship with eligibility for DoD Secret clearance.
Preferred
Experience architecting agentic AI systems with Vertex AI Agent Builder and event-driven GCP services (Eventarc, Cloud Run, Cloud Functions). Familiarity with Google Cloud-native IaC tools and hybrid/multi-cloud integration patterns. Experience with federal mission systems, cybersecurity standards (RMF, FedRAMP), and compliance frameworks. Exposure to multi-agent frameworks and reusable archetypes for scaling AI solutions across federal programs. Publications, open-source contributions, or recognized expertise in AI/ML/Cloud Engineering.
Working Conditions
Please join us, as together we build a better world one mission at a time powered by Technology and its People! #LI-Onsite #Credence #veteranemployment #militaryspouse #milspouse #hireavet #militaryveteran #militaryfriendly #transitioningmilitary #veterans #militarytransition #militaryfamilies #msep #militarytocivilian #military #federalcontractingjobs #defensecontracting #defenseindustryjobs Seniority level: Mid-Senior level Employment type: Full-time Job function: Consulting, Analyst, and Information Technology Industries: Data Infrastructure and Analytics and IT Services and IT Consulting #J-18808-Ljbffr
Credence is seeking a Senior Google AI/Data Engineer to join our growing AI and Automation practice. The role focuses on designing and delivering scalable AI and data solutions on Google Cloud Platform (GCP). You will guide model and data pipeline life-cycles, shape technical standards, mentor mid-level engineers, and collaborate with federal stakeholders and senior AI leaders. Responsibilities 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. Architect scalable ML systems with security, resilience, and cost optimization in mind. Architect and optimize high-throughput data pipelines using BigQuery, Dataflow, Pub/Sub, and Dataproc. Establish data engineering standards for quality, lineage, and governance. Define and implement MLOps strategy on GCP, including CI/CD for models, automated workflows, IaC (Terraform, Deployment Manager), and Kubernetes (GKE). Establish monitoring, retraining, and drift detection frameworks using Cloud Monitoring and Vertex AI. Drive adoption of generative AI and LLMs using Googles Generative AI Studio, Vertex AI Search, and Agent Builder. Architect event-driven and agentic AI systems leveraging Cloud Run, Eventarc, and serverless workflows. Evaluate emerging Google AI/ML capabilities, pilot innovative approaches, and incorporate them into federal missions. Lead design reviews, mentor team members, and enforce technical rigor across projects. Partner with federal mission leaders to translate requirements into AI/data solutions. Collaborate with cross-functional teamsdata scientists, software engineers, and security engineersto deliver secure, production-ready systems.
Education, Requirements and Qualifications What You Bring
Bachelors or Masters in Computer Science, AI/ML, Data Science, or a related field (PhD a plus). 7+ years of hands-on experience delivering AI/ML and data engineering solutions, with at least 3+ years on GCP. Expertise in Python and ML libraries (TensorFlow, PyTorch, scikit-learn). Deep knowledge of Google Cloud services: BigQuery, Dataflow, Pub/Sub, Dataproc, Vertex AI, Cloud Functions, Cloud Storage, and GKE. Proven track record in architecting AI/ML pipelines and data platforms at enterprise scale. Strong experience with Kubernetes, Docker, and CI/CD workflows in GCP. Mastery of MLOps practices: CI/CD, automated retraining, monitoring, and explainability. Experience with generative AI and LLMs in Googles AI ecosystem. Ability to lead technical teams, mentor engineers, and shape standards. Strong communication skills and experience interfacing with federal stakeholders. U.S. Citizenship with eligibility for DoD Secret clearance.
Preferred
Experience architecting agentic AI systems with Vertex AI Agent Builder and event-driven GCP services (Eventarc, Cloud Run, Cloud Functions). Familiarity with Google Cloud-native IaC tools and hybrid/multi-cloud integration patterns. Experience with federal mission systems, cybersecurity standards (RMF, FedRAMP), and compliance frameworks. Exposure to multi-agent frameworks and reusable archetypes for scaling AI solutions across federal programs. Publications, open-source contributions, or recognized expertise in AI/ML/Cloud Engineering.
Working Conditions
Please join us, as together we build a better world one mission at a time powered by Technology and its People! #LI-Onsite #Credence #veteranemployment #militaryspouse #milspouse #hireavet #militaryveteran #militaryfriendly #transitioningmilitary #veterans #militarytransition #militaryfamilies #msep #militarytocivilian #military #federalcontractingjobs #defensecontracting #defenseindustryjobs Seniority level: Mid-Senior level Employment type: Full-time Job function: Consulting, Analyst, and Information Technology Industries: Data Infrastructure and Analytics and IT Services and IT Consulting #J-18808-Ljbffr