Top Remote Software Engineer Jobs in Baltimore, MD

Build and deploy AI solutions for clients, including agentic workflows, RAG systems, structured extraction, OCR and document-processing pipelines, retrieval systems, evaluation harnesses, and lightweight interfaces. Translate ambiguous client problems into production code, drive engagements from discovery through deployment, collaborate with stakeholders, and contribute to internal platform capabilities and engineering practices.

Build and deploy production-quality software integrations within customer aerospace and defense environments. Embed with engineering teams, connect CAD, CFD, FEM, simulation, and digital engineering workflows to Istari’s platform, develop reusable solutions, and serve as the primary technical interface. Translate customer needs into product insights, contribute to architecture and roadmap discussions, and support technical proposals. The role requires onsite customer work, U.S. citizenship, and clearance eligibility.

Lead architecture and delivery across Rails backends and React frontends, build Node.js and NestJS platform integrations, establish testing and code-quality standards, mentor engineers, review code, and improve reliability, performance, and developer experience. The role requires technical ownership across multiple backend technologies and leadership in AI-assisted development practices.

Design and deliver full-stack applications spanning user interfaces, data models, APIs, backend services, cloud infrastructure, and AI-enabled workflows. Build vector-store and RAG capabilities, deploy Azure services with Terraform and containers, and contribute to architecture, technical roadmaps, code reviews, testing, and system operations. Collaborate directly with business stakeholders to understand needs and deliver scalable, secure, enterprise-grade software. The role also involves identifying patentable innovations, preparing disclosures, and supporting patent prosecution.

Build responsive web applications and scalable frontend/backend services, design secure APIs and databases, implement AI-powered search and asset management features, collaborate on system architecture, and optimize performance and UX for a cloud-native DAM platform.

Build and scale backend APIs, services, event-driven workflows, queues, data models, caching, and integrations serving millions of users. Lead complex technical initiatives from discovery through production, improve reliability and performance, debug cross-system issues, and optimize databases and infrastructure interactions. Partner across Product, Design, Infrastructure, Platform, Data, and Support while mentoring engineers, influencing technical decisions, and raising engineering quality standards.

Lead design and implementation of core platform infrastructure for an Agentic AI platform. Build high-performance Rust systems, support production deployments, collaborate with ML engineers, design scalable data architectures, troubleshoot performance and scalability issues, and cultivate a collaborative, inclusive engineering culture.

Own and scale Adobe Experience Platform and Real-Time CDP implementations. Design data collection architecture using Web SDK, Edge Network, and datastreams; govern XDM schemas, identity, datasets, and data quality. Develop tagging, CJA connections and views, audience activation, privacy frameworks, and event-driven data layers. Troubleshoot ingestion and identity issues, integrate Adobe ecosystem tools and downstream systems, and collaborate with stakeholders on scalable technical solutions, governance, documentation, and enablement.

Build AI-powered product quality infrastructure for capturing, synthesizing, routing, and acting on customer feedback. Develop bug intake and triage systems, dashboards, data pipelines, analytics tooling, and integrations with ticketing, payment, CRM, and data warehouse systems. Partner with support engineers and domain specialists to improve product quality and ship internal tools quickly.

Leads the Bioinformatics Software Engineering team and owns engineering strategy, architecture, delivery, modernization, and production support for clinical genomics platforms. Oversees software engineers, bioinformatics workflows, data integration, automation, quality systems, release governance, reliability, and regulatory compliance. Partners with clinical, laboratory, scientific, quality, product, operations, and executive stakeholders to convert research methods into validated production workflows. Guides AI-enabled engineering initiatives while ensuring privacy, traceability, clinical-grade quality, and operational resilience.