Principal Software Engineer (London-Hybrid)

Principal Engineer

Location: Waterloo, London, England, UK | Hybrid (1 day per week in office).

Responsibilities

• Rapidly build trust with clients, demonstrating technical expertise and understanding of their domain and objectives
• Guide technical direction, solving complex problems and demonstrating best practices while remaining deeply engaged within the codebase
• Work pragmatically to balance technology choices while delivering high‑quality work within deadlines
• Advise clients on architecture, scalability and platform evolution, connecting technical decisions to product and business outcomes
• Collaborate on systems involving the full ML lifecycle from data ingestion and pre‑processing to model deployment, integration, and performance monitoring
• Drive innovation by proactively surfacing new technical approaches and product solutions
• Lead or initiate formal feedback conversations with teams and clients via retrospectives
• Clearly articulate and document outcomes and drive forward action items
• Contribute to the health of the team and culture by modeling the company values
• Design and manage high‑level technical roadmaps for large engagements
• Build your network and maintain relationships with clients and other industry leaders within your domain
• Coach client engineering teams, transferring knowledge and leveling up practices
• Influence client CTOs and executive decisions, planning and executing technical work that involves stakeholders outside the project boundaries
• Participate in account planning and opportunity identification
• Facilitate retrospectives, strategy sessions, and technical deep‑dives to improve team and project outcomes
• Identify, mitigate, and resolve blockers to team progress
• Serve as a mentor, lead or design workshops, represent the company in the community, or support hiring processes
• Demonstrate leadership in scalable system design, modular architecture, and platform‑ or product‑oriented development
• Bring depth in testing strategies, observability, fault tolerance, and secure engineering practices
• Apply architectural patterns to evaluate trade‑offs and drive clear, documented design rationale

Qualifications

• 10+ years of experience with long‑term success on high‑stakes consulting engagements across multiple language paradigms, stacks, ecosystems, technical environments, and client industries
• Experience building high‑quality, maintainable software collaboratively, incrementally, and tailored to client needs
• Proven track record delivering production‑grade software in languages and frameworks including 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
• 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 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
• Facilitated alignment and collaboration across technical and non‑technical stakeholders to move initiatives forward amid ambiguity and complexity while balancing technical and user needs
• Provided mentorship and team support at scale, sharing knowledge and improving practices
• Actively sought out and effectively gave feedback
• Collaboratively led stakeholders to balance technical considerations with product and user needs

Preferred Skills

• Delivering and advising on enterprise‑grade AI systems, including RAG pipelines, vector search, and agentic frameworks (e.g., LangChain, LlamaIndex, Crew AI, AutoGen, n8n)
• Experience with DevSecOps and DevOps practices
• Experience with MLOps
• Experience with Infrastructure as Code
• Experience with data engineering platforms like Databricks for processing and analytics

Benefits

• Wellness package with a whole‑person focus
• 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 the global team
• 12 weeks of new parent leave for eligible employees

Compensation

Pay range: £92,818–£116,122 GBP (London).

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