Top Remote Python Jobs

Own client data workflows from intake through validated delivery. Ingest, clean, transform, and validate healthcare datasets using Python and SQL; build automation scripts; troubleshoot pipelines with Engineering; ensure HIPAA-compliant, accurate outputs; package results with clinical context; track client metrics; and improve delivery playbooks and documentation.

Provide primarily technical Oracle EBS support and development, with some functional responsibilities involving HR, payroll, and Oracle HCM Cloud. This is a remote contract role initially lasting three months, with potential for long-term extension. Candidates should be available to start as soon as possible and have experience working across Oracle enterprise applications and HR/payroll systems.

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.

Develop and maintain secure full-stack web applications, APIs, integrations, databases, and production infrastructure. Rapidly prototype with AI-assisted development tools, then audit, refactor, test, secure, deploy, and monitor the resulting software. Integrate healthcare, CRM, billing, communications, and enterprise systems while protecting PHI and supporting HIPAA safeguards. Collaborate with executives, analysts, vendors, and operational teams to translate business needs into maintainable technical solutions, troubleshoot incidents, and continuously improve reliability and delivery speed.

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.

Design and build scalable backend services, data systems, pipelines, cloud infrastructure, and AI-enabled features for an enterprise SaaS platform. Lead technical projects, improve reliability and security, automate engineering workflows, and collaborate with product, design, and data teams. The role requires hands-on ownership in a fast-moving startup environment, with a focus on distributed systems, architecture, performance, compliance, and operational excellence.

Leads and coaches a software engineering team, supports career development, participates in hiring, removes delivery roadblocks, and shapes technical direction. The manager ensures reliable, high-performing systems while driving daily adoption of agentic AI tools and collaborating with Product and Business Technology stakeholders. The role requires a strong full-stack engineering background, architectural expertise, experience delivering quality software, and demonstrated success leading AI adoption.

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.

Build and maintain scalable financial data infrastructure, including ingestion, validation, normalization, and integrations. Develop systems that calculate portfolio performance metrics efficiently across high-volume datasets, improve reliability and observability, and support distributed processing. Create internal tools, dashboards, reusable schemas, asset data feeds, and self-service analytics capabilities. Collaborate cross-functionally to expand market-data coverage, support B2B integrations, and strengthen operational resilience.

Administer and optimize SQL Server and PostgreSQL production databases, including backup and recovery, high availability, security, monitoring, capacity planning, maintenance, upgrades, and incident response. Plan and execute cloud database migrations to Azure while optimizing performance, resiliency, recoverability, and cost. Establish database standards, improve reliability practices, collaborate with engineering teams, and mentor less experienced administrators.