Principal Forward Deployed Architect - AI Data Foundations

About the role

At TruStage, we're on a mission to make a brighter financial future accessible to everyone. We put people first, and work hand in hand with employees and customers to create a diverse and inclusive environment. Passionate about building insurance and financial services solutions, we push the boundaries of what's possible. We need you to help us shape what's next. You'll be encouraged to share your experiences, ideas and skills to help others take control of their financial future. Join a team that has received numerous awards for being a top place to work: TruStage awards and recognition Job Responsibilities: 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. Forward Deployment & Embedded Engagement 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. Architecture, Standards & Methodology 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. Scale Enablement & Adoption 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. Feedback Loop to Strategy 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. Platform & Ecosystem Strategy 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. Emerging Technologies & Trends: Assess vendor capabilities, strategic partnerships, and technology maturity to accelerate delivery while minimizing lock-in risk. Organizational Enablement & Capability Building 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. Reference Architecture Ownership - AI Data Foundations. Establish and maintain enterprise reference architectures for multi-agent systems, orchestration patterns, memory/context management, and integration with enterprise data platforms. The above statement of duties is not intended to be all inclusive and other duties will be assigned from time to time. Job 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 At this time, we're not considering applicants that need any type of immigration sponsorship (additional work authorization or permanent work authorization) now or in the future to work in the United States. This includes, but IS NOT LIMITED TO: F1-OPT,

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