G
Cloud Data and AI Engineer, Professional Services
Reston · Virginia · United States
2-5
127,000 – 183,000 USD
7h ago
70%
Strong
Job description
MINIMUM QUALIFICATIONS:
* Bachelor’s degree in Engineering, Computer Science, a related field, or
equivalent practical experience.
* 3 years of experience with software development in Python, Java, or C++, and
relational database technologies.
* Experience implementing data and AI solutions (including LLMs) and providing
technical leadership to business stakeholders and education to partners.
* Active, or the ability to obtain, a TS/SCI security clearance.
* Ability to travel up to 30% of the time.
PREFERRED QUALIFICATIONS:
* Experience with database and AI integrations.
* Experience with MLOps, data warehousing, and data pipeline development,
including ETL and ELT.
* Experience working with cloud databases such as RDS, Aurora, ElastiCache,
CloudSQL, AlloyDB, Datastore, or Bigtable.
* Experience in database administration techniques including storage,
clustering, availability, disaster recovery, security, logging, performance
tuning, monitoring and auditing.
* Experience developing, deploying, and managing machine learning models,
including experience writing software in one or more languages, such as Java,
Python, or Golang.
* Experience with database management tools for backups, recovery, snapshot
management, sharding, partitioning and as well as database performance
tuning.
ABOUT THE JOB:
As a Cloud Data and AI Engineer, you will guide Public Sector customers to
develop, configure and deploy their data and AI solutions. Together with the
team, you will support customer implementations of Google Cloud products through
architecture guidance, best practices, data migration, capacity planning,
implementation, troubleshooting, monitoring, and more. You will consult with
customers on how to best design their data and AI solutions including
development and deployment of ML models, and integrations with leading Google
technologies. You will travel to customer sites to deploy solutions and deliver
workshops to educate and empower customers. Additionally, you will work closely
with Product Management and Product Engineering to drive excellence in Google
Cloud products and features.
Google Public Sector
[https://about.google/intl/ALL_us/public-sector/#:~:text=We're%20committed%20to%20advancing,%2C%20research%2C%20and%20edtech%20companies.]
brings the magic of Google to the mission of government and education with
solutions purpose-built for enterprises. We focus on helping United States
public sector institutions accelerate their digital transformations, and we
continue to make significant investments and grow our team to meet the complex
needs of local, state and federal government and educational institutions.
The US base salary range for this full-time position is $127,000-$183,000 +
bonus + equity + benefits. Our salary ranges are determined by role, level, and
location. Within the range, individual pay is determined by work location and
additional factors, including job-related skills, experience, and relevant
education or training. Your recruiter can share more about the specific salary
range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the
base salary only, and do not include bonus, equity, or benefits. Learn more
about benefits at Google [https://careers.google.com/benefits/].
RESPONSIBILITIES:
* Be highly collaborative and work closely with data producers, consumers and
Data and AI Engineering teams across public sector customers and teams to
understand the data needs, provide consultation, and design and develop
solutions.
* Analyze on-premise and cloud database environments, consulting on the optimal
design for performance and deployment on Google Cloud Platform. Design,
build, and maintain data and AI solutions.
* Create and deliver best practices recommendations, tutorials, blog articles,
sample code, and technical presentations, adapting to different levels of key
business and technical stakeholders.
* Translate business requirements into conceptual, logical, and physical data
models.