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phData

Principal Applied AI Solutions Architect

RemoteUnited States only
Published
Role
Engineering Management
Experience
Principal
Employment
Full-time
Company size
Mid-size
Salary not disclosed
Check eligibility

Open to US only. Set where you work from to check your eligibility.

No BS summary

Principal-level technical leader to design and deliver end-to-end AI/ML solutions for enterprise clients. Requires 10+ years building and deploying production ML/data systems, strong Python, SQL, Spark/Snowflake/Databricks experience, and cloud architecture knowledge. US-remote role (phData hires across US, LATAM, India) with US benefits.

Core skills

Applied AIML model deployment

Required skills

PythonSQLSparkSnowflakeDatabricksRedshiftAmazon EMRHDFSJMSKafkaMySQLOracleSAPLinuxAWSAzureGCPDockerKubernetesAPI design

Optional skills

H2OTensorFlowKerasscikit-learnMLflowSageMakerAzure ML

What you'll do

  • Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic client accounts, ensuring reliable model deployment, retraining, monitoring, and production operations that create clear business impact.
  • Translate complex business and data science requirements into scalable, secure, and resilient AI/ML architectures, defining the environments, data flows, and infrastructure required for model development, training, tuning, and serving.
  • Lead technical and strategic client engagements, including workshops, discovery sessions, and architecture reviews, to align stakeholders on AI/ML roadmaps, deployment approaches, and production-readiness standards.
  • Ensure the quality, reliability, and observability of AI/ML solutions through robust testing strategies, documentation, monitoring, and governance that meet security, compliance, and performance expectations.
  • Contribute to and leverage reusable assets such as reference architectures, accelerators, templates, and playbooks, while mentoring team members and partnering with Sales and account leadership to grow strategic AI/ML engagements.

What they require

  • 10+ years of experience as a Machine Learning Engineer, Software Engineer, Data Engineer, or Data Scientist building and deploying production data and machine learning solutions.
  • Strong proficiency in a modern programming language such as Python (or similar) for building production-grade data and ML solutions, including experience designing and integrating APIs and services that expose ML models.
  • Ability to build and operate robust data pipelines across diverse data sources and toolsets, with strong working knowledge of SQL and experience writing, debugging, and optimizing complex and distributed queries.
  • Hands-on experience with big data and analytics platforms such as Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS, or similar large-scale data processing and storage technologies.
  • Familiarity with multiple data source systems such as JMS, Kafka, RDBMS, data warehouses, MySQL, Oracle, and SAP, and how they integrate into analytical and ML environments.
  • Systems-level knowledge of network and cloud architecture, Linux-based operating systems, and storage/compute platforms (e.g., AWS, Databricks, Cloudera), with proven experience designing and operating production ML systems for performance, security, scalability, and reliability.
  • End-to-end software development lifecycle experience (design, documentation, implementation, testing, deployment, and ongoing operations) for data and ML solutions, including model deployment, monitoring, and lifecycle management.
  • Bachelor’s degree in a relevant technical field (such as Computer Science) or equivalent practical experience. (If desired)

Benefits

  • Remote-First Work Environment
  • 401k plan with company match
  • Dental and Vision insurance
  • Home Office Equipment Stipend
  • Annual stipend for Learning and Development
  • Competitive comp, excellent benefits, 4 weeks PTO plus 10 Holidays

Data and AI Consultancy

NullMid-size
Salary not disclosed