Principal Software Engineer

Role Overview

• Rapidly building trust with clients, demonstrating technical expertise and understanding of their domain and objectives.
• Guiding technical direction, solving complex problems, and demonstrating best practices while remaining deeply engaged within the codebase.
• Working pragmatically to balance technology choices while delivering high-quality work within deadlines.
• Advising clients on architecture, scalability and platform evolution, connecting technical decisions to product and business outcomes.
• Collaborating on systems that involve the full ML lifecycle from data ingestion and preprocessing, to model deployment, integration, and performance monitoring.
• Driving innovation by proactively surfacing new technical approaches and product solutions.
• Leading or initiating formal feedback conversations with teams and clients via retrospectives.
• Clearly articulating and documenting outcomes and driving forward action items.

Requirements

• You’ve shown long-term repeated success on a variety of projects, typically over the course of 10+ years.
• You are a trusted expert and leader, often called upon to guide ambiguous initiatives and architect scalable solutions.
• Demonstrated long-term success on high-stakes consulting engagements across multiple language paradigms, stacks, ecosystems, technical environments, and client industries.
• Built high-quality, maintainable software collaboratively, incrementally, and through an approach tailored towards the unique needs of the clients you’ve served.
• Led the development and delivery of production-grade software using a variety of languages and frameworks, including but not limited to: Python, Java, JavaScript, TypeScript, React, Ruby, Scala, R, SQL, and Go.
• Evaluated and strategically applied AI-assistive development tools to accelerate delivery and improve quality.
• A track record of understanding, assessing, and embracing new tooling and trends within the software industry.
• Experience building or integrating AI/ML-powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics).
• Used context-appropriate automated testing to inform software design choices and catch bugs.
• Successfully led modernization efforts to align legacy systems with short and long-term business needs.
• Remedied architecture-level concerns such as scalability, security, reliability, and performance.
• Provided mentorship and team support at scale, while sharing knowledge and improving team practices.

Tech Stack

• Java
• JavaScript
• Python
• React
• Ruby
• Scala
• SQL
• TypeScript
• Go

Benefits

• A robust L&D programme featuring unlimited access to thousands of books, courses, and expert-led training on the O'Reilly learning platform.
• Annual financial stipend and time allotment for learning & development
• Coworking support for our global team
• 12 weeks of new parent leave available for eligible employees