• Own single-threaded leadership (STL): Serve as the accountable product leader for the transaction rail, driving alignment, prioritisation, and execution across all teams involved in the payment lifecycle. • Think end-to-end across the value chain: Understand and optimize the handoffs between domains — how a routing decision in Payment Orchestration affects approval rates, how the Transaction Core's state machine feeds Money Operations' reconciliation, and how Risk, Trust & Vault gates every authorization. • Drive agentic strategy: Define the “what” and “why” for platform features that move client onboarding toward low-to-no coding effort, from provider certification to routing rules. • Protect the stability floor: Enforce a “Stop the Line” mentality for quality, maintaining a Stability Floor of highly automated quality assurance across every domain in the rail. • Provide cross-functional leadership: Lead a high-ownership set of pods staffed with elite engineers across the five domains, partnering with Staff Engineers and the CTO Office to eliminate silos. • Embed a YBIYRI culture: Evangelize and operationalize the YBIYRI mindset across all five domains, ensuring teams design for multi-tenancy, elastic scaling, and automated observability. • Prioritize with evidence: Use the RICE framework to turn ambiguous, cross-domain requirements into a single, structured, executable roadmap that balances architectural integrity against market opportunism.

• Join the Tilt team • Help expand Tilt’s credit modeling and risk analytics capability for our Philippines-based business, Cashalo. • Build and refine underwriting models as well as other models, working at the intersection of credit, data science, and leadership. • Collaborate with a lean but growing team, applying advanced modeling techniques to predict loss performance, leverage alternative data sources, and build next-generation tools that shape credit access for millions. • Partner directly with cross-functional teams across credit, engineering, and leadership, bringing strong project and stakeholder management skills to a lean, fast-growing team.

Role Description TEKsystems is partnered with a software company in Raleigh that needs to hire a Senior Data Scientist for their flagship product, a leading global provider of information and analytics. Recently our client has focused on the general availability of their product for U.S. customers, a generative AI solution designed to transform legal work. Their product delivers trusted results in a familiar, easy-to-use interface with linked hallucination-free legal citations that combine the power of generative AI with proprietary search technology, Shepard’s® Citations functionality, and authoritative content. This role leads the design and development of an advanced multi-agent AI platform that powers intelligent research, drafting, and reasoning capabilities for large-scale enterprise knowledge environments. You will architect agent frameworks, optimize retrieval-augmented generation pipelines, fine-tune language models, and build the infrastructure that enables AI systems to collaborate, plan, and execute complex tasks reliably. The work directly shapes the next generation of AI-driven professional tools used by experts in high-stakes domains. Core Responsibilities - Architect and implement multi-agent systems capable of planning, tool use, and coordinated task execution. - Design and optimize RAG pipelines including embeddings, hybrid retrieval, reranking, and context-window strategies. - Fine-tune and evaluate small, medium, and large language models for domain-specific reasoning and summarization. - Develop prompt engineering frameworks, guardrails, and automated evaluation suites for agent reliability. - Build scalable ML services and APIs for production deployment in distributed environments. - Collaborate with product, engineering, and domain experts to translate complex workflows into agentic AI solutions. - Establish best practices for model evaluation, observability, safety, and compliance. - Mentor DS/ML engineers and contribute to long-term AI strategy and architecture. Qualifications - 6–12+ years in Data Science / ML Engineering, with deep experience in LLM-based systems. - Proven experience building agentic architectures (planner-executor, tool-use agents, ReAct-style reasoning). - Strong background in RAG, embeddings, retrieval optimization, and evaluation. - Expertise in NLP, transformers, deep learning, and model fine-tuning. - Proficiency with PyTorch, HuggingFace, LangChain/LlamaIndex, Ray, Kubernetes, and vector databases. - Experience designing production-grade ML systems with monitoring, evaluation, and observability. - Strong communication skills and ability to lead technical direction. Preferred Qualifications - Experience in enterprise search, knowledge management, or high-compliance domains. - Experience with model distillation, LoRA/QLoRA, PEFT, and model compression. - Experience building evaluation frameworks for hallucination, grounding, and agent reliability. - Familiarity with knowledge graphs, symbolic reasoning, or hybrid neuro-symbolic systems. - Publications, patents, or open-source contributions in LLMs or agent systems. - Strong coding skills in Python (7+ years). - Natural problem solver, able to take a lead in collaborating to resolve issues. - Proficiency in IDE debugging: VSCODE and PYCHARM. - 5+ years of experience in AI and machine learning. - Deep understanding of machine learning algorithms, classification models, diagnostic testing of models. - Experience working directly with Transformer-based architectures including BERT, RoBERTa, T5, etc., and familiarity with large language models and fine-tuning. - Experience with conversational search / semantic search, reinforcement learning, prompt engineering, hallucination mitigation. - Working understanding of the business risks associated with applying LLM (LangChain) in a business. - Experience working with AWS, RAG, SageMaker, SQL. Requirements - Expert Level experience. - Contract to Hire position based out of Raleigh, NC. Benefits - Medical, dental & vision. - Critical Illness, Accident, and Hospital. - 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available. - Life Insurance (Voluntary Life & AD&D for the employee and dependents). - Short and long-term disability. - Health Spending Account (HSA). - Transportation benefits. - Employee Assistance Program. - Time Off/Leave (PTO, Vacation or Sick Leave). Workplace Type This is a fully remote position. Application Deadline This position is anticipated to close on Jul 31, 2026.

Role Description We are seeking an experienced Product Owner with strong expertise in Snowflake or Databricks to oversee the delivery of an enterprise data lake initiative. This role combines product ownership, technical understanding, and data platform knowledge. The ideal candidate will collaborate closely with engineering, architecture, and business teams to convert requirements into actionable plans and drive the successful deployment of a scalable enterprise data platform. - Lead the end-to-end delivery of an enterprise data lake built on Snowflake or Databricks—from initial setup through production release - Translate business and data requirements into well-defined user stories, acceptance criteria, and sprint deliverables - Oversee the development of data ingestion and integration pipelines from SaaS platforms and other enterprise systems - Manage the full development lifecycle, ensuring timely completion of milestones and deliverables - Prioritize and maintain the product backlog based on business value, feasibility, and operational needs - Develop and manage a comprehensive delivery roadmap, including MVP releases and phased enhancements - Collaborate with cloud infrastructure and DevOps teams to ensure the platform is scalable, secure, and cost-efficient - Monitor and report key platform performance metrics such as pipeline success rates, processing times, and system reliability - Ensure a smooth transition to analytics and data science teams through proper documentation and operational readiness Qualifications - Proven experience as a Product Owner or Product Manager in data platforms, analytics, or cloud-based systems - Strong expertise in Snowflake or Databricks, including data modeling, data pipelines, and cloud architecture - Experience working with engineering, data, and DevOps teams in Agile/Scrum environments - Ability to translate complex business requirements into actionable technical plans - Familiarity with data ingestion, ETL/ELT workflows, and API-based integrations - Excellent communication and stakeholder management skills - Experience in HRMS or large-scale enterprise environments is a strong plus