Top Remote Software Engineer Jobs in Tampa Bay, FL

Build and evolve scalable backend systems and APIs for a large SaaS platform. Partner with Product, Design, and QA from ideation through deployment, contribute to microservices architecture, improve testing and observability, identify operational risks, and mentor teammates. The role emphasizes reliable, maintainable solutions, strong collaboration, architectural decision-making, and continuous improvement.

Senior full-stack product engineer responsible for owning features end to end, from clarifying requirements and defining acceptance criteria through development, testing, deployment, monitoring, and production support. The role builds across React, TypeScript/Node.js, PostgreSQL, and AWS, uses AI-assisted development and QA tools, writes unit and end-to-end tests, and collaborates closely with tax-domain product owners in a small engineering pod.

Leads and grows the engineering organization, sets technical strategy and roadmap, oversees execution across multiple teams, and provides technical direction on architecture, scalability, reliability, security, and quality. Partners with Product, Design, Operations, Risk, and the CTO to deliver customer-focused financial products. Responsibilities include recruiting and developing engineering leaders, improving processes, removing organizational bottlenecks, and balancing product delivery with long-term platform and infrastructure investments.

Own the architecture, development, and maintenance of Nebulock’s customer-facing security platform across the full stack. Build product experiences including threat intelligence and detection query tools, improve scalability and maintainability, establish engineering standards, shape the technical roadmap, collaborate across product and security teams, and mentor engineers.

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.

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.

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.

Administers and develops Oracle EPM Cloud and Hyperion financial planning systems. Responsibilities include managing security and user access, maintaining nightly and close processes, troubleshooting integrations, developing enhancements with Groovy and EPM Automate, coordinating patching and regression testing, writing technical specifications and test plans, supporting data governance, analyzing issues, and creating stakeholder training materials. The role collaborates with IT and business teams to deliver reliable, scalable financial systems.

Design, build, maintain, and scale production backend services and integrations. Debug cross-service production issues, lead architecture and technical decisions, mentor engineers, improve engineering standards and tooling, release backward-compatible APIs, implement auto-scaling services, and architect real-time systems for syncing large data volumes.

Develop open source SDKs, enterprise APIs, UIs, and backend systems supporting large-scale computer vision datasets. Build scalable, maintainable, performant, and well-tested software for unstructured data and AI workflows. Contribute to enterprise deployments across customer clouds and on-premises environments, while improving tooling, automation, engineering practices, and open source community initiatives in a remote-first team.