Remote Software engineering Jobs

• Train and fine-tune text models (LLMs), deploying them on Google Cloud, and building automation around these models.
• Analyse business requirements for the desired output format and the logic the model must implement.
• Develop services and APIs (REST/gRPC) that expose the model to other systems.

Design, implement, and maintain Microservices using Go and/or Python. Design and develop cloud based software products conforming to industry best practices. Build systems, services, and tools to handle new Ocrolus products and business requirements that securely scale over millions of transactions.

• Build and maintain secure, high-traffic backend services supporting critical Veteran-facing features.
• Modernize legacy components, develop and refine REST APIs, and support identity and access workflows.
• Integrate with VA enterprise systems, troubleshoot backend issues, and collaborate with partners to deliver scalable functionality.

Lead a global cross-functional engineering team to deliver scalable SaaS solutions. Own technical design decisions and guide Development teams through AGILE SDLC. Oversee architectural design, coding standards, DevOps integration, CI/CD pipelines, and software delivery lifecycle.

• Drive end to end execution of technical projects, from ideation and design to deployment.
• Design and build resilient, large-scale systems from the ground up with a focus on reliability, scalability, and performance.
• Provide thought leadership and guide peers in navigating complex architectural and coding decisions.

• Lead the design, development, and deployment of AI/ML models.
• Build and maintain production-grade ML pipelines and model monitoring.
• Mentor and develop junior AI engineers, laying the foundation for AI best practices.

• Building features and maintaining back-end services using Go microservices.
• Deploying Weave software solutions into Google Cloud Platform.
• Designing and maintaining services that can scale and grow independently.

• Develop Machine Learning models and pipelines.
• Interact with databases and data infrastructure.
• Conduct in-depth data analytics and build statistical data inference models of biological processes.

The AI Engineer develops and deploys agentic AI solutions for clients. Implements components for document processing, workflow automation, data retrieval, and structured output generation. Contributes to monitoring, logging, metrics, and guardrail configurations for agentic systems.

• Design and deliver software solutions that enhance customer experiences and streamline operations.
• Work across the full stack, from database models to user-facing screens, collaborating closely with product, design, and data teams.
• Mentor peers, drive refactoring efforts to reduce technical debt, and ensure high-quality, maintainable code.