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Sophos
India · remote · Salary not listed
We are looking for a Principal Software Engineer to provide hands-on technical leadership for the Central Platform Group. You will lead the architecture, design, and delivery of customer-facing capabilities spanning user interfaces, backend services, APIs, and shared cloud platforms.
You will also help build secure, reliable AI experiences that connect customers with assistants and agents across Sophos products. This is a senior individual-contributor role with responsibility for production code, cross-team architecture, engineering quality, and technical direction.
AI-driven engineering is a core expectation for this role. You will use AI coding agents as part of day-to-day software development and help establish effective agentic workflows that improve delivery speed and quality while preserving security, human review, and engineering accountability.
Apply on source siteListed via Himalayas
Lead the architecture, design, and delivery of end-to-end customer-facing features across web UI, backend services, APIs, and integrations.
Write production code, build prototypes, review designs and code, and remain directly involved in solving the most complex engineering problems.
Evolve shared frontend and backend platform capabilities so product teams can deliver consistent, accessible, and maintainable customer experiences.
Define clear service boundaries, APIs, data contracts, integration patterns, and versioning strategies for capabilities used across multiple Sophos products.
Design cloud-native, multi-tenant systems for security, scalability, availability, performance, resilience, and cost efficiency.
Apply secure-by-design principles to authentication, authorization, role-based access, tenant isolation, privacy, auditability, and customer-data handling.
Build a consistent and secure experience for customers to discover and interact with AI assistants and agents across Sophos products.
Develop reusable AI platform capabilities for request routing, context management, tool integration, orchestration, access control, and human oversight.
Establish practical approaches for AI evaluation, guardrails, regression testing, observability, latency, cost management, and safe failure behavior.
Use AI coding agents throughout the software development lifecycle for codebase exploration, design, implementation, refactoring, test generation, debugging, code review, and documentation; rigorously validate agent-generated changes before release.
Establish repeatable agentic development practices for task decomposition, context management, human review, automated verification, and the safe use of coding agents across engineering teams.
Translate product goals and ambiguous technical problems into architectural direction and incremental delivery plans.
Mentor engineers, raise engineering standards, and build alignment across product, UX, security, applied AI, and platform teams.
Originally posted on Himalayas