Machine Learning Principal Solutions Architect

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role, you will lead the architecture, implementation, and lifecycle management of AI/ML applications that deliver measurable business value for our clients. You will take full ownership of strategic AI/ML projects from vision and solution design through deployment and ongoing optimization while ensuring that models can be trained, tuned, and operated reliably using client data. You will collaborate closely with clients, Sales, data scientists, ML engineers, and platform teams to deliver high-quality solutions and advance phData’s delivery excellence.

• →Act as a trusted advisor to senior and executive client stakeholders, shaping AI/ML roadmaps, influencing strategic decisions, and guiding long-term initiatives.
• →Lead multiple work streams concurrently, ensuring alignment across technical teams, business stakeholders, and account leadership.
• →Help define and refine practice standards, reusable assets, and delivery frameworks that improve consistency, quality, and scalability of AI/ML engagements.
• →Champion a culture of customer obsession, continually seeking ways to increase client impact and satisfaction.

• Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic client accounts, from model inference, retraining, and monitoring through to production operations.
• Translate business and data science requirements into scalable, secure, and resilient architectures that align with phData methodologies, standards, and best practices.
• Design and create environments for data scientists to build, train, test, and tune AI/ML models and applications using relevant client data.
• Work within customer systems to extract data from a variety of sources and place it within analytical environments to support model development, training, and tuning.
• Define deployment approaches and production infrastructure for AI/ML models and applications, ensuring that businesses can reliably consume and maintain the solutions we deliver.
• Demonstrate the business value of data by partnering with data scientists to manipulate and transform data into actionable insights and deployable machine learning models.
• Create and execute operational testing strategies, including QA validation, performance testing, and implementation plans to support testing and deployment of AI/ML solutions.
• Ensure the quality, reliability, and observability of delivered solutions through rigorous testing, documentation, and monitoring.

• Collaborate with cross-functional partners including data scientists, ML engineers, data engineers, platform/DevOps, and business stakeholders to deliver successful client engagements.
• Provide technical and strategic leadership during workshops, discovery sessions, architecture and design reviews, and project delivery.
• Partner closely with Sales and account leadership to drive account expansion, identify new opportunities, and ensure long-term client value on strategic accounts.
• Take full ownership of client success within AI/ML projects, including planning and vision-crafting, managing client expectations, and handling escalations in a proactive and outcome-oriented manner.
• Ensure high quality in deliverables through code reviews, documentation, testing, governance, and adherence to security and compliance standards.
• Serve as a visible technical leader and point of escalation for complex AI/ML challenges within key customer engagements.

• Contribute to internal initiatives such as IP development, accelerators, reference architectures, templates, and playbooks focused on AI/ML and MLOps.
• Mentor and guide ML engineers, data scientists, and other team members to elevate the overall technical and consulting capabilities of the practice.
• Represent phData with professionalism in all interactions, communicating clearly with both technical and non-technical stakeholders.

You are a customer-obsessed technical leader and consultant who enjoys solving complex data and AI/ML challenges while building trusted relationships with clients. You are equally comfortable discussing architecture with executives and diving deep into code, infrastructure, and data pipelines with engineering teams. You thrive in an outcomes-driven environment, manage multiple work streams with ease, and bring a blend of strong engineering skills, strategic thinking, and excellent communication to every engagement.

Preferred qualifications help candidates stand out but are not required for success in this role.

• A Master’s or other advanced degree in data science, computer science, or a related field.
• Hands-on experience with cloud and data ecosystem technologies such as Spark, Databricks, Snowflake, AWS, Azure, or GCP.
• Experience working with data science and machine learning libraries and frameworks such as H2O, TensorFlow, Keras, scikit-learn, or similar.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Experience with MLOps tooling such as AWS SageMaker, Azure ML, and MLflow, and with building enterprise-scale ML models.
• Prior experience in a consulting role or working closely with clients on strategic data and AI/ML initiatives.
• Relevant side projects such as contributions to open source technology stacks, technical communities, speaking, or writing.

• 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.

• Expertise in modern programming languages such as Python, Scala, Java, or similar, including experience developing APIs and web server applications using frameworks such as Flask, Django, or Spring.
• Ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets, with strong working knowledge of SQL and the ability to write, debug, and optimize complex and distributed queries.
• Hands-on experience with big data and analytics ecosystem technologies such as Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS, or similar platforms.
• Familiarity with multiple data source systems such as JMS, Kafka, RDBMS, data warehouses, MySQL, Oracle, and SAP.
• Systems-level knowledge of network and cloud architecture, Linux-based operating systems, and storage/compute platforms (e.g., AWS, Databricks, Cloudera).
• Proven experience deploying machine learning models into production environments and ensuring their performance, security, scalability, and reliability.
• Complete software development lifecycle experience, including design, documentation, implementation, testing, deployment, and ongoing operations.
• Excellent communication and presentation skills, with prior experience working directly with internal or external customers.

• Owning pre-sales and project scoping responsibilities
• Proven Account Growth / Revenue Generation experience for external clients
• Experience delivering projects for external or internal clients in a professional services, product, or consulting environment.
• Ability to break down complex, ambiguous problems into structured, actionable steps and drive them through to completion.
• Strong written and verbal communication skills in English, with the ability to present technical concepts to both technical and non-technical audiences.
• Demonstrated customer obsession and a strong desire to make clients successful.

• Demonstrated ability to work effectively with distributed and cross-functional teams, including Sales, data scientists, ML engineers, data engineers, and business stakeholders.
• Proven track record of taking ownership of client outcomes, managing multiple priorities and work streams, and delivering high-quality work with minimal supervision.
• Comfort operating in client environments, quickly learning new systems and tools, and adapting solutions to fit existing architectures and processes.

• Bachelor’s level degree in Computer Science or a related technical field, or equivalent practical experience preferred.

This role is based in the United States and operates primarily in the Central Time Zone.

• We are a remote-first company, and you should be comfortable working with a distributed global team.
• Some flexibility may be required to collaborate across time zones with colleagues and clients.
• Client needs may occasionally require flexibility in working hours to support key milestones or workshops.

• Impactful Work: Partner with leading organizations on meaningful data & AI initiatives.
• Collaborative Culture: Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.
• Growth Opportunities: Access to challenging projects, mentorship, and structured development pathways.