Jobs at TMS LLC

Leads actuarial forecasting and quantitative risk modeling for mobile-device claims, inventory valuation, and physically settled supply contracts. Develops stochastic claims and exposure models, depreciation and residual-value analyses, Monte Carlo scenarios, contract valuations, portfolio optimization, and tail-risk assessments. Partners with Finance, Procurement, Treasury, Legal, Accounting, Supply Chain, and Risk to guide inventory decisions, risk limits, hedging thresholds, and reserve inputs. Serves as senior technical authority while remaining an individual contributor.

Build, deploy, monitor, and improve production-grade AI agents using Python, Claude Agent SDK, and AWS Bedrock AgentCore. Design golden datasets and LLM-as-a-Judge evaluations, integrate automated quality gates into CI/CD, and implement Langfuse or OpenTelemetry observability. Evaluate agent accuracy, task completion, tool execution, and performance while supporting RAG pipelines and AWS data workflows. The role also involves troubleshooting, continuous evaluation, and potentially agentic red-teaming.

Develop and maintain SureCommercial integrations, REST APIs, web services, data mappings, and migration components. Support on-premises-to-cloud migration, data integrity, testing, troubleshooting, performance optimization, deployment, documentation, and collaboration with architecture, business analysis, QA, and infrastructure teams. The role requires hands-on insurance platform integration experience and familiarity with cloud, hybrid environments, and DevOps practices.

Develop and maintain Insurity SureCommercial integrations, migrate on-premises applications and interfaces to cloud environments, and build REST APIs and web services. Responsibilities include analyzing architecture and data flows, supporting data migration and integration testing, troubleshooting defects, optimizing performance, documenting procedures, and collaborating with architecture, QA, business, and infrastructure teams. The role also emphasizes secure, scalable, reliable, and compatible cloud solutions.

Build and optimize scalable data pipelines and cloud-based data solutions using Python, PySpark, SQL, and Snowflake. Integrate REST APIs and external data sources, develop ETL/ELT workflows, optimize Snowflake queries, and implement data quality, validation, monitoring, and automation. Collaborate with engineering and analytics teams to deliver reliable data platforms.

Designs and develops resilient, secure, scalable cloud-native .NET applications. The hands-on architect will code critical components, establish engineering standards, lead architecture using microservices, DDD, and CQRS, build Azure-based systems and CI/CD pipelines, mentor 5–10 developers, conduct code reviews, and collaborate with product stakeholders to translate requirements into technical solutions.