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Google Ai Engineer Jobs (NOW HIRING)

Senior Google AI Engineer

Mclean, VA

$107K - $147K/yr

We are growing our Google Cloud AI engineering capability to support our Department of War (DoW) programs. You will design, build, and operationalize production grade AI systems on Google Cloud ...

Senior Google AI Engineer

Mclean, VA · On-site

$105K - $145K/yr

We are growing our Google Cloud AI engineering capability to support our Department of War (DoW) programs. You will design, build, and operationalize production grade AI systems on Google Cloud ...

Senior Google AI Engineer

Mclean, VA · On-site

$105K - $145K/yr

We are growing our Google Cloud AI engineering capability to support our Department of War (DoW) programs. You will design, build, and operationalize production grade AI systems on Google Cloud ...

Senior AI Engineer

Paramus, NJ

$105K - $145K/yr

Senior AI Engineer (Google AI & GenAI) We're looking for a Senior AI Engineer with strong experience in Generative AI and the Google AI ecosystem. This role requires 10+ years of software engineering ...

OR · On-site

Job Summary The Solutions Engineer - Google AI collaborates with account and specialty teams to assess customer cybersecurity needs. They will be a customer-facing cloud AI expert.They will take a ...

Job Summary The Solutions Engineer - Google AI collaborates with account and specialty teams to assess customer cybersecurity needs. They will be a customer-facing cloud AI expert.They will take a ...

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Google Ai Engineer information

See salary details

$39K

$101.8K

$137.5K

How much do google ai engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for google ai engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What are Google AI Engineers?

Google AI Engineers are professionals who design, develop, and implement artificial intelligence and machine learning solutions at Google. They work on a wide range of projects, from improving search algorithms to developing intelligent systems for products like Google Assistant, Photos, and Cloud AI services. Their responsibilities include data analysis, model building, testing, and deployment of AI models in production environments. These engineers often collaborate with researchers, data scientists, and product teams to solve complex problems using the latest advancements in AI and machine learning.

What are some common challenges faced by Google AI Engineers when deploying machine learning models to production?

Google AI Engineers often encounter challenges such as ensuring models are scalable and efficient enough to handle large-scale data, maintaining model performance over time, and addressing issues related to fairness and bias. Collaborating with cross-functional teams, such as product managers and software engineers, is crucial for aligning technical solutions with product goals. Additionally, AI Engineers must keep up with evolving frameworks and best practices to optimize deployment pipelines and monitor models post-launch for potential drift or degradation.

What is the difference between Google Ai Engineer vs Machine Learning Engineer?

AspectGoogle Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related fields; experience with AI frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentTech companies, research labs, AI-focused teamsTech firms, startups, data-driven organizations
Industry UsagePrimarily in AI product development at Google and similar companiesAcross various industries implementing ML solutions
Common Search/ComparisonYesYes

The Google AI Engineer and Machine Learning Engineer roles share many credentials and work environments, but AI Engineers focus more on developing advanced AI models and research, while ML Engineers often implement and optimize machine learning algorithms for practical applications across industries.

What are the key skills and qualifications needed to thrive as a Google AI Engineer, and why are they important?

To thrive as a Google AI Engineer, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree and experience in algorithm development. Familiarity with TensorFlow, Python, cloud computing platforms, and often certifications in AI or data science are essential for daily tasks. Problem-solving abilities, creativity, and effective collaboration are standout soft skills in this role. These skills are vital for developing innovative AI solutions that align with Google’s standards of performance, scalability, and impact.
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Senior Google AI Engineer

$107K - $147K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago


Job description

Overview

Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose.

We've been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges.

Position Summary

We have an immediate need for a highly skilled Senior Google AI Engineer. We are growing our Google Cloud AI engineering capability to support our Department of War (DoW) programs. You will design, build, and operationalize production grade AI systems on Google Cloud-accelerating mission outcomes for a high visibility program.

As a Senior Google AI Engineer, you will serve as a handson technical leader for AI solution delivery. You'll translate mission needs into secure, scalable AI/ML systems; guide data, platform, and application engineers; and ensure solutions meet DoW security and compliance requirements in production. The ideal candidate combines deep GCP/Looker/BigQuery/Vertex AI expertise with strong MLOps, data engineering fluency, and experience delivering in regulated environments.

Responsibilities include, but are not limited to the duties listed below:

  • Architect and deliver endtoend AI/ML solutions on Google Cloud using Vertex AI (Workbench, Pipelines, Training, Model Registry, Online/Batch Prediction, Feature Store, Model Monitoring) and Gemini/LLM services-optimized for performance, cost, and maintainability.
  • Develop production data pipelines with BigQuery, Dataflow, and Dataproc; integrate streaming via Pub/Sub; containerize and orchestrate with Cloud Run and GKE; automate CI/CD with Cloud Build and IaC.
  • Implement robust MLOps (experiment tracking, evaluation, bias/robustness testing, model versioning, canary/bluegreen rollouts, automated retraining, drift detection, and lineage).
  • Apply securebydesign patterns-VPCSC, private service access, CMEK, finegrained IAM, artifact signing, and secrets management-aligned to NIST 80053, RMF, and FedRAMP baselines.
  • Operationalize LLM/GenAI (RAG, tooluse/agents, safety filters, evaluation harnesses) including retrieval over structured/unstructured data; leverage DoWapproved AI toolchains where appropriate.
  • Partner with mission stakeholders to elicit requirements, frame measurable success criteria, and deliver iterative value; provide technical mentorship and lead design/code reviews for engineering teams.
  • Contribute to program roadmaps (including use cases), documenting architectures, controls, and SOPs for sustained operations.

Overview

Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose.

We've been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges.

Position Summary

We have an immediate need for a highly skilled Senior Google AI Engineer. We are growing our Google Cloud AI engineering capability to support our Department of War (DoW) programs. You will design, build, and operationalize production grade AI systems on Google Cloud-accelerating mission outcomes for a high visibility program.

As a Senior Google AI Engineer, you will serve as a handson technical leader for AI solution delivery. You'll translate mission needs into secure, scalable AI/ML systems; guide data, platform, and application engineers; and ensure solutions meet DoW security and compliance requirements in production. The ideal candidate combines deep GCP/Looker/BigQuery/Vertex AI expertise with strong MLOps, data engineering fluency, and experience delivering in regulated environments.

Responsibilities include, but are not limited to the duties listed below:

  • Architect and deliver endtoend AI/ML solutions on Google Cloud using Vertex AI (Workbench, Pipelines, Training, Model Registry, Online/Batch Prediction, Feature Store, Model Monitoring) and Gemini/LLM services-optimized for performance, cost, and maintainability.
  • Develop production data pipelines with BigQuery, Dataflow, and Dataproc; integrate streaming via Pub/Sub; containerize and orchestrate with Cloud Run and GKE; automate CI/CD with Cloud Build and IaC.
  • Implement robust MLOps (experiment tracking, evaluation, bias/robustness testing, model versioning, canary/bluegreen rollouts, automated retraining, drift detection, and lineage).
  • Apply securebydesign patterns-VPCSC, private service access, CMEK, finegrained IAM, artifact signing, and secrets management-aligned to NIST 80053, RMF, and FedRAMP baselines.
  • Operationalize LLM/GenAI (RAG, tooluse/agents, safety filters, evaluation harnesses) including retrieval over structured/unstructured data; leverage DoWapproved AI toolchains where appropriate.
  • Partner with mission stakeholders to elicit requirements, frame measurable success criteria, and deliver iterative value; provide technical mentorship and lead design/code reviews for engineering teams.
  • Contribute to program roadmaps (including use cases), documenting architectures, controls, and SOPs for sustained operations.
  • US citizenship with the ability to obtain successful DoW Secret security clearance required. Candidates with active Secret clearance preferred.
  • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field.
  • Advanced degree (Master's Degree or PhD) in AI/ML, Data Science, Computer Science, or a closely related discipline is preferred but not required, especially when balanced with substantial handson experience (5+ years) in AI/ML solution development.
  • 8+ years total software development/data experience with 5+ years focused on AI/ML engineering and MLOps, including production deployments on Google Cloud (GCP).
  • Proven experience architecting robust data ingestion, processing, and transformation workflows using Dataflow, Data Fusion, Dataproc, BigQuery, and Looker and integrating these platforms with Vertex AI for model training, deployment, and inference.
  • Must possess a current Google Associate Cloud Engineer (GCP-ACE) or Google Professional Cloud Architect (GCP-PCA) certification or be able to obtain it within 90 days of hire.
  • Must possess at least one current DoW Cyber Baseline Certification (e.g., Security+ Intermediate, SecurityX/CASP+ Advanced) or be able to obtain it within 90 days of hire.
  • Proven experience with extracting data from SAP Enterprise Business Applications.
  • Expert in Python (and/or Go/TypeScript) for AI services; strong with Vertex AI, BigQuery, Dataflow and/or Data Fusion, GKE/Cloud Run, Cloud Build, Cloud Storage, Pub/Sub.
  • Practical experience with LLMs/GenAI (e.g., Gemini), vector databases, prompt engineering, RAG patterns, and evaluation/guardrails.
  • Proven MLOps track record (Pipelines, CI/CD for ML, feature stores, monitoring/drift, automated retraining) and strong data engineering fundamentals.
  • Ability to design for security & compliance in DoW/Federal contexts (NIST 80053, RMF, FedRAMP; Zero Trust principles).
  • Handson experience with Vertex AI Agent Builder, Model Garden, embeddings/vector search (e.g., BigQuery Vector, AlloyDB AI), and evaluation frameworks.
  • Experience integrating GenAI safely within IL5 environments and familiarity with available government AI platforms.
  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • Family Leave (Maternity, Paternity)
  • Short Term & Long Term Disability
  • Training & Development
  • Wellness Resources