Principal Forward Deployed Architect – AI Data Foundations

Role Overview

• Rapid POC & MVP Delivery (Agentic AI) Embedded into Data Strategy team, lead data engineering, platform, and business teams to identify high value Agentic AI use cases (e.g., Data Product Build, data quality automation, metadata management, governance assistance).
• Design and deliver rapid POCs and MVPs embedded in real TruStage data environments.
• Evaluate agent performance, reliability, controls, and human in the loop patterns.
• Act as a forward deployed resource, embedding with teams to co define problems, refine use cases, and adapt solutions in context.
• Translate ambiguous business and operational needs into practical AI driven data solutions.
• Ensure solutions fit TruStage’s operating model, risk posture, and regulatory expectations.
• Create architect design patterns, standards and methodology that will be followed by data management teams to scale Agentic/AI work.
• Closely collaborate with Enterprise AI architect for setting best practices, standards and governance process for MCP/AA/API based integration patterns.
• Document learnings from POCs and MVPs into: Reference architectures for Agentic AI; Design patterns and guardrails; Deployment and operating standards.
• Define processes and methodologies for developing, deploying, and governing Agentic AI in data domains in accordance and partnership with AI Governance team as needed.
• Establish criteria for scalability, security, observability, and cost management.
• Partner with central platform, data governance, and engineering leaders to industrialize validated patterns.
• Enable teams with clear playbooks, templates, and examples to scale Agentic AI safely and consistently.
• Influence roadmap priorities based on field learnings and adoption signals.
• Provide continuous feedback to D&A leadership on: What works vs. what doesn’t in real deployment; Capability gaps and tooling needs; Change management and operating model implications.
• Help TruStage evolve from experimentation to AI-enabled data operations at scale.
• Influence enterprise AI/data platform capabilities, AI tool selection, and integration standards.
• In collaboration with AI COE, evaluate emerging Agentic AI frameworks, orchestration platforms, vector technologies, and LLM tooling for enterprise fit.
• Assess vendor capabilities, strategic partnerships, and technology maturity to accelerate delivery while minimizing lock-in risk.
• Mentor architects, engineers, and data teams on Agentic AI patterns and architectural best practices for data management.
• Build internal communities of practice and reusable knowledge assets.
• Establish and maintain enterprise reference architectures for multi-agent systems, orchestration patterns, memory/context management, and integration with enterprise data platforms.

Requirements

• Bachelor’s degree in information technology, computer science, or related field, or equivalent combination of education and/or related professional work experience.
• 10+ years of strong background in data architecture, data engineering, and cloud platforms.
• 4 years of hands-on experience with AI/ML, LLMs, automation, or orchestration technologies.
• Proven ability to move from concept to prototype to production.
• Comfort working in ambiguous, fast-moving environments.
• Strong communication skills across technical and executive audiences.
• Deep appreciation for risk, governance, and trust in data and AI.
• Systems integration expertise.
• Cross-functional execution (engineering, product, security, operations, and business teams).
• Infrastructure and DataOps fluency.
• Change management and adoption.
• Graph technologies – ontologies, knowledge graphs, semantics, context graphs.
• Prefer prior experience in the insurance or finance industry.

Tech Stack

• Cloud

Benefits

• medical
• dental
• vision
• employee assistance program
• life insurance
• disability plans
• parental leave
• paid time off
• 401k
• tuition reimbursement