Note: The job is a remote job and is open to candidates in USA. phData is a remote-first data and AI consultancy company that partners with industry leaders to solve complex data and AI challenges. They are seeking a Principal Solutions Architect to lead the architecture, implementation, and lifecycle management of AI/ML applications, ensuring high-quality solutions and client success.
Responsibilities
- 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
- 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
Skills
- 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
- 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
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 plan plus 10 Holidays (and other cool perks)
Company Overview
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