[Hiring] Applied AI Solutions Architect @phData

Role Description

The Applied AI Solutions Architect is a client-facing technical role within phData’s Applied AI practice. You’ll help customers translate business challenges into practical, production-ready solutions across machine learning, generative AI, AI applications, data platforms, and cloud infrastructure.

• Work with client stakeholders, project teams, and senior architects to understand requirements, design solution approaches, and guide implementation.
• Contribute across the full engagement lifecycle—from discovery and architecture through development, deployment, and production support.
• Lead technical workstreams, contribute hands-on when needed, and grow your impact through collaboration, delivery excellence, and continuous learning.

Qualifications

• 8+ years of experience designing, building, or delivering Data, Analytics, Cloud, Software, Machine Learning, or AI solutions.
• At least 5 years of experience designing or leading AI, machine learning, MLOps, or data-intensive solutions in production.
• Experience translating business and technical requirements into architecture, solution designs, and implementation plans.
• Strong understanding of Applied AI and modern machine learning systems, including predictive ML, MLOps, generative AI, LLM applications, RAG, or agentic architectures.
• Hands-on experience with production AI/ML systems, including considerations for evaluation, observability, security, governance, and operational support.
• Experience with modern cloud, data, and AI ecosystems, including technologies such as Snowflake, Databricks, AWS, Azure, Google Cloud, dbt, Anthropic, OpenAI, or other modern AI frameworks.
• Experience with programming and software development, preferably Python, as well as strong working knowledge of SQL.
• Ability to collaborate effectively with business stakeholders and highly technical engineering teams.
• Strong written and verbal communication, presentation, facilitation, and problem-solving skills.
• Experience working in a consulting, professional services, product, or client-facing delivery environment.
• Demonstrated ability to take ownership, manage multiple priorities, and deliver high-quality work with appropriate guidance.
• Willingness to travel as needed to support customers, workshops, and strategic engagements.

Requirements

• Experience with agentic AI systems, including orchestration, tool use, planning, memory, multi-agent patterns, or protocols such as MCP.
• Experience designing and deploying enterprise RAG systems, semantic retrieval, AI applications, or intelligent workflow automation.
• Experience with cloud-native AI/ML services such as AWS Bedrock and SageMaker, Azure AI/ML, Google Vertex AI, or Snowflake Cortex.
• Experience with model registries, feature stores, data and model lineage, model monitoring, drift detection, AI evaluations, prompt management, or AI gateways.
• Experience building reusable accelerators, modular architectures, or solutions deployed across multiple clients.
• Industry experience building AI or machine learning solutions in life sciences, retail, financial services, manufacturing, or other enterprise environments.
• Experience presenting technical solutions to customers or contributing to proposals, RFIs, RFPs, workshops, or demonstrations.
• Contributions to open-source projects, technical communities, blogs, podcasts, or other technical thought leadership.
• Bachelor’s or master’s degree in computer science, engineering, data science, or a related technical field—or equivalent practical experience.

Benefits

• Impactful work with leading organizations on meaningful Data and Applied AI initiatives.
• A collaborative, global team that values transparency, autonomy, curiosity, ownership, and continuous improvement.
• Opportunities to work across predictive machine learning, MLOps, generative AI, agentic systems, and intelligent applications.
• Access to challenging projects, mentorship, technical communities, and ongoing professional development.
• A culture focused on psychological safety, community, and doing the right thing for our clients, teams, and partners.
• phData celebrates diversity and is committed to creating an inclusive environment for all employees.