Top Remote Jobs in Baltimore, MD

Analyze insurance product and portfolio performance, build dashboards and reporting tools, validate data, and translate complex insurance questions into actionable recommendations. The role supports rate revisions, state expansion, product development, and profitable growth while partnering with Product, Engineering, Data, Underwriting, Compliance, and other teams. It also uses SQL, business intelligence platforms, and AI tools such as Claude to improve workflows and decision-making.

Own end-to-end quality for new features across the operator portal, backend platform, and endpoint agent. Translate requirements into runnable acceptance coverage, build and maintain parallel browser test frameworks, validate APIs and contracts, and integrate suites into CI release gates. Curate automated and AI-generated scenarios, assess test risk, report coverage and failures, and close quality gaps. The role also drives adoption of shared tooling and may involve containerized environments, cloud platforms, virtualization, performance testing, and security product testing.

Support accounts payable, state sales tax filings and registrations, broader tax compliance, and monthly close activities. Responsibilities include invoice review, payment processing, reconciliations, accruals, amortization, and coordinating with external tax advisors. The role also identifies opportunities to improve accounting processes, controls, and workflows in a fast-growing, remote technology company.

Manage a portfolio of enterprise customers, lead technical onboarding and integrations, drive product adoption and expansion, surface customer feedback to Product/Engineering, create technical documentation, and run cross-functional initiatives to scale success.

Leads operational standards, SOPs, process documentation, change management, and readiness activities across markets. Partners with IT, Legal, Compliance, Training, and Operations teams on system implementations, workflow design, testing, and adoption. Monitors adherence, performance dashboards, and operational metrics while identifying continuous-improvement opportunities and supporting corrective actions.

Manage Salesforce opportunity intake, qualification, classification, and routing across internal departments. Review RFPs, technical specifications, and installation scopes to identify requirements, deadlines, responsibilities, and project fit. Use approved AI tools to analyze documents and support data-driven triage. Collaborate with sales and operations, maintain accurate pipeline data, and apply knowledge of networking, physical security, audiovisual, and electrical systems while meeting quality and deadline expectations.

Supports sales teams by designing technical solutions, delivering complex product demonstrations, preparing proposals, and addressing customer requirements. Serves as a subject matter expert across networking, security, Microsoft, voice, cloud, UCaaS, and CCaaS technologies. Partners with Product, Engineering, and Sales teams, provides technical training, manages multiple enterprise opportunities, documents sales activity, and represents the company at sales events.

Lead assessment, redesign, and hands-on implementation of data pipelines, ML workflows, and platform infrastructure. Produce prioritized system designs, harden production pipelines, improve observability, reliability, and data quality, and mentor the data team.

Develop predictive machine learning models and generative AI applications using Azure, Python, pandas, and scikit-learn. Build and deploy production GenAI solutions, including RAG, hybrid search, evaluations, multi-agent systems, and user interfaces. Collaborate on dataset design, statistical modeling, process-control integration, and full-stack application development. Present findings to nontechnical audiences while addressing business problems across research, finance, manufacturing, legal, and environmental safety functions.

Designs the technical foundation for Dave’s AI Agent Factory, including agent architecture, MCP servers, governed data access, semantic-layer integrations, evaluation frameworks, deployment standards, observability, authentication, authorization, auditability, and PII protection. The role establishes scalable AI engineering standards and reusable infrastructure while partnering with Data, Engineering, Security, and Product teams to enable safe, reliable company-wide AI adoption.