Senior Software Engineer

Software Engineer, PHP

The Software Engineer designs solutions and delivers backend features for our product platform using AI tools throughout the development lifecycle. As part of a small collaborative pod, this position is accountable for features end-to-end—leveraging AI assistance for specification, implementation, quality validation, deployment, and post-deployment support while ensuring quality outcomes at each stage. This is primarily a backend role focused on high-throughput data ingestion, PDF processing, and working with large datasets. The Software Engineer interfaces with Technical PMs and fellow engineers to deliver scalable, performant services with high velocity. This position also helps evolve our Al-assisted development practices and mentors Associate Engineers on effective AI tool usage.

What You’ll Do

Job Responsibilities

• Own specification quality for assigned features by ensuring specifications are complete, unambiguous, and include acceptance criteria and edge cases.
• Collaborate with Technical Product Managers (PMs) to translate product requirements into detailed technical specifications.
• Use AI coding tools (e.g., Claude Code) to generate implementations from technical specifications.
• Design and build data ingestion pipelines capable of reliably processing large volumes of structured and unstructured data.
• Implement PDF parsing, extraction, generation, and manipulation capabilities for high-volume document workflows.
• Design performant, memory-efficient software that scales efficiently with increasing data volumes while adopting a DevOps mindset.
• Review AI-generated code and peer contributions for correctness, security, performance, and architectural alignment.
• Validate AI-generated tests and ensure comprehensive test coverage.
• Design and implement REST APIs following established architectural patterns.
• Optimize database queries, schemas, and storage strategies for large relational datasets.
• Mentor Associate Engineers on effective AI tool usage and specification writing techniques.
• Share technical knowledge and best practices with the engineering team.
• Contribute to the evolution of AI-assisted development practices, including specification templates, prompt patterns, and validation workflows.
• Take ownership of domain knowledge within your pod's area of responsibility.
• Support and maintain backend services within your pod's domain.

Qualifications

Required

• Bachelor's degree in Computer Science (or equivalent practical experience) with a strong understanding of data structures and scalable software design.
• 3+ years of software engineering experience designing and implementing scalable backend applications in a product-centric environment.
• Strong proficiency in writing production-quality C++ code.
• Experience developing Windows applications using C++ and Windows development libraries (e.g., Win32 API, MFC, or ATL).
• Strong proficiency in .NET (C#).
• Strong proficiency in Python.
• Strong understanding of SQL and relational databases, particularly MySQL, including schema design and query optimization for large datasets.
• Knowledge of NoSQL databases such as MongoDB or DynamoDB.
• Experience building high-volume data ingestion and processing systems.
• Experience with PDF parsing, extraction, generation, or manipulation using established libraries or custom implementations.
• Ability to design and implement REST APIs.
• Experience building and deploying applications on AWS.
• Strong experience with source control management using Git or similar version control systems.
• Demonstrated experience using AI coding assistants such as Claude Code, Windsurf, or similar tools.
• Strong collaboration and communication skills, with the ability to work closely with Technical PMs and cross-functional teams to gather requirements and refine specifications.
• Strong code review skills, including the ability to validate correctness and identify issues in both AI-generated and human-written code.
• Preferred
• Experience with specification-driven, agentic AI workflows where engineers delegate autonomous tasks to AI tools while providing guidance and oversight.
• Experience with performance profiling, memory management, and optimizing throughput for data-intensive applications.
• Experience with message queues or streaming platforms (e.g., Kafka) for data ingestion pipelines.
• Experience mentoring junior engineers.
• Understanding of testable application design principles.
• Experience contributing to software development process improvements