Solutions Engineer

• Design, build, and deploy intelligent backend services using Python and Azure AI Foundry.
• Consume Force Account outputs by API, ensuring the system can accurately display and act on data classification and extraction.
• Engineer and optimize Retrieval-Augmented Generation (RAG) pipelines over Standard Operating Procedures (SOPs) to provide contextual, accurate, and actionable insights to users.
• Deliver assistive intelligence directly on the case, seamlessly integrating AI outputs into the end-user's workflow.
• Design and strictly enforce a redact-before-model discipline, ensuring that all Personally Identifiable Information (PII) is stripped from payloads before data ever reaches a foundational model.
• Collaborate with product, design, and engineering teams to shape AI features and translate business goals into technical execution.
• Proactively identify AI-driven automation and product improvement opportunities, building prototypes to prove value.
• Mentor junior engineers and champion secure, responsible AI coding practices within your team.
• Troubleshoot AI-specific technical challenges, including prompt injection risks, model latency, and data leakage.
• Guide team members on model selection, evaluation, fine-tuning, and Gen AI usage.
• Actively evaluate emerging LLM tooling, agentic frameworks, and open-source developments for applicability to client engagements.
• Own the architecture of the team's agentic and LLM systems — agent orchestration, tool integration (e.g., Model Context Protocol), retrieval, and human-in-the-loop design.
• Design and implement evaluation frameworks for LLM and agentic systems — covering correctness, boundary, and intent checks — as a standard part of delivery.
• Drive adoption of the agentic SDLC across the team: select and roll out AI engineering tools, define usage and governance standards, and measure their impact on delivery velocity and quality.
• Establish responsible-AI and evaluation frameworks for agentic systems — guardrails, safety testing, human oversight, and model governance.

Lead AI Integration Engineer

• Support customer onboarding and technical implementations/integrations of TransUnion fraud solutions
• Work directly with clients via Salesforce tickets, email, and Microsoft Teams to provide technical guidance and resolve issues
• Troubleshoot and resolve integration-related incidents affecting customer environments
• Partner with customers’ technical teams to successfully integrate APIs and services into their systems
• Monitor and manage incoming support requests and prioritize based on urgency and impact
• Participate in incident response and help restore services in case of disruptions
• Provide ongoing support for integrations, ensuring stability and performance
• Collaborate with global teams across regions (e.g., US, UK, LATAM)

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Lead AI Integration Engineer

Integrations Engineer