Python Developer

Bright Vision Technologies•Fremont, CA

5d•$100,000 - $150,000•Remote

About The Position

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications. As we continue to grow, we’re looking for a skilled Python Developer to join our dynamic team and contribute to our mission of transforming business processes through technology. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies. This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved. We do not engage in C2C, 1099, or third-party arrangements for this role. Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables. New H1B sponsorship may be available for qualified candidates for this role. Candidates who are currently on a valid H1B visa and require a transfer are also welcome to apply. We will support H1B transfers for qualified candidates. For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience. We are seeking an experienced Python Developer to design, build, and continuously enhance complex enterprise-grade applications, data-intensive services, and automation platforms. This is a hands-on engineering role focused on delivering robust, secure, and high-performance Python systems that operate reliably within distributed and mission-critical production environments. The ideal candidate will bring deep Python expertise combined with strong fundamentals in software architecture, data engineering, and operational support, and will partner closely with product, data, and infrastructure teams to translate ambiguous business problems into well-engineered technical solutions. You will be expected to think beyond surface-level fixes, identify root causes of complex issues, and proactively raise the engineering bar across the team.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
Five or more years of applied Python development experience in enterprise-grade environments.
Strong experience building and maintaining large-scale production applications with significant uptime and reliability requirements.
Hands-on experience with relational database systems such as Oracle, MS SQL Server, PostgreSQL, or Sybase, including query tuning and schema design.
Strong understanding of the full software development lifecycle (SDLC), including requirements, design, build, test, release, and ongoing support.
Proven hands-on experience across system design, application development, automated testing, and operational support.
Strong working knowledge of data structures, algorithms, and computational efficiency, with the ability to make sound design trade-offs.
Demonstrated experience debugging and maintaining complex, enterprise-level applications in production.
Solid understanding of Agile methodologies, CI/CD practices, application resiliency patterns, and secure coding standards.
Ability to manage multiple concurrent projects in dynamic, fast-changing environments while keeping stakeholders well informed.
Strong written and verbal communication skills, with experience collaborating with both technical and business teams.

Nice To Haves

Strong shell scripting skills in UNIX/Linux environments and comfort working with command-line tooling.
Solid grounding in mathematical and statistical concepts and the ability to translate them into code.
Hands-on experience with the Python data and ML ecosystem, including NumPy, Pandas, SciPy, Scikit-Learn, TensorFlow, and PyTorch.
Working exposure to AWS cloud services and cloud-native storage technologies such as S3, RDS, DynamoDB, and Glue.

Responsibilities

Provide end-to-end design, development, and advanced technical troubleshooting for complex enterprise-grade Python applications, reaching beyond routine approaches to solve novel and non-trivial technical problems.
Develop secure, high-quality, production-ready Python code and implement algorithms that perform reliably within distributed systems, with thoughtful consideration of concurrency, fault-tolerance, and observability.
Produce architecture and design artifacts for complex applications, ensuring that day-to-day development adheres to defined design constraints, performance requirements, and enterprise standards.
Develop and optimize data processing logic for large-scale datasets, including extraction, transformation, validation, deduplication, enrichment, and performance tuning to support both batch and near-real-time workloads.
Gather, analyze, and synthesize large and diverse datasets to support continuous improvement of applications and business processes, surfacing insights that lead to measurable improvements in product, reliability, or cost.
Develop reporting mechanisms, dashboards, and data visualizations where required to support operational insights, leveraging libraries and tools appropriate to the stakeholder audience.
Identify hidden defects, performance bottlenecks, and architectural weaknesses, and proactively implement improvements to coding standards, system reliability, and overall maintainability.
Contribute substantively to engineering best practices, conduct thorough peer code reviews, and participate constructively in architectural design discussions, mentoring less-senior engineers along the way.
Participate fully in Agile development cycles and CI/CD processes, ensuring consistent, stable, and frequent deployments with appropriate testing, rollback, and monitoring strategies in place.
Collaborate closely with cross-functional stakeholders — product managers, data scientists, operations engineers, and business analysts — to clarify requirements and translate them into scalable technical solutions.
Support operational stability through structured incident response, debugging, log analysis, and post-incident reviews in enterprise environments, contributing actionable preventative measures.