Top Remote Senior Level Jobs in Washington DC,

Own product strategy, roadmap, backlog, and delivery for a technical healthcare data platform portfolio. Partner closely with engineering across the SDLC, translate customer and business needs into requirements, lead agile ceremonies, investigate data and architecture tradeoffs, use SQL and instrumentation for prioritization, and manage technical debt, scalability, and data quality. The role also communicates roadmap decisions to stakeholders and supports adoption of shipped capabilities.

Provide pre-sales technical support for Imprivata solutions across the Northeast: discovery, customized demos, proof-of-concepts, RFI/RFP responses, SOWs, channel enablement, and transition to services. Travel up to 50%.

Design, build, and operate scalable batch and streaming data pipelines, lakehouse and warehouse models, and data services. Own datasets end to end, improve Snowflake, Iceberg, Spark, and Flink performance and reliability, implement governance and observability, and support graph-serving data models. Partner with product and engineering teams, participate in on-call, review code and designs, and mentor junior engineers.

Own product strategy, roadmap, and business results for organic discovery and AI visibility across thousands of real estate websites. Lead engineering and design partners, translate customer needs into platform capabilities, measure search and AI citation impact, and connect outcomes to retention, revenue, and client growth. Partner cross-functionally with sales, marketing, and client success to launch and communicate product value.

Own Salesforce architecture and the broader revenue technology stack. Lead cross-functional initiatives involving lead routing, quote-to-cash, data hygiene, integrations, automation, and AI-driven GTM improvements. Design scalable processes, configure and deploy systems, optimize integrations with Outreach, Gong, and HubSpot, and serve as a technical partner to Revenue, Marketing, Finance, and Data teams.

Own Engine’s end-to-end rate distribution strategy across channels, partners, programs, and customer segments. Design rate distribution programs, segmentation, rate products, fencing rules, loading standards, and integrity monitoring. Partner with Product, Engineering, Operations, Finance, Supply, and Partnerships to create a scalable operating model, roadmap, tooling, and dashboards. Collaborate with account owners to position programs for chain and distribution partners while influencing cross-functional execution and tracking industry trends.

Leads complex U.S. federal and DoD capture efforts from opportunity shaping through contract closure. Develops capture, acquisition, proposal, negotiation, and contracting strategies; coordinates product, engineering, sales, security, contracts, and external stakeholders; applies federal procurement and compliance expertise; builds government relationships; and translates customer needs into product and sales priorities. Travel may be frequent, up to 30%.

Build the core AI platform for an AI-native trading experience. Develop a high-performance Rust backend supporting streaming responses, low-latency tool execution, caching, and model orchestration. Design secure, observable APIs and runtime components with authentication, authorization, rate limiting, auditing, tracing, retries, and fallbacks. Build safe trading action infrastructure with deterministic previews, confirmations, idempotency, and audit logs while partnering with product and frontend teams.

Own revenue for the West territory by activating and expanding broker, consultant, and employer partnerships in the 200–999 life segment. Build and manage your pipeline, run deals end-to-end, meet quota, and implement tracking and processes to keep territory performance predictable.

Build and deploy AI-powered tools for Rula’s business and clinical teams by observing workflows, rapidly delivering production software, measuring usage and impact, and enabling teams to operate tools independently. The role requires privacy-by-design practices, rigorous AI evaluation, customer-centric discovery, and integration with complex legacy systems. Staff engineers may optimize LLM costs and quality while creating reusable building blocks for future teams.