Principal Software Engineer

As a Principal Software Engineer within the Document Automation pillar, you will lead the practical adoption of AI-enabled engineering practices across multiple products, services, and teams. Your focus will be improving how software is designed, built, tested, reviewed, documented, released, and supported. You will combine hands-on engineering and prototyping with broad technical leadership to create reusable approaches, establish effective standards, and help teams achieve measurable improvements in productivity, quality, and delivery effectiveness. Reports to: Director of Software Engineering.

Responsibilities

Define and drive an AI-enabled engineering productivity strategy across multiple Document Automation products and services; identify and prioritize opportunities to apply AI across discovery, requirements refinement, architecture, coding, testing, code review, documentation, release, troubleshooting, and support workflows; build prototypes, reference implementations, reusable accelerators, integrations, and agentic workflows that teams can adopt at scale; establish practical standards, guardrails, and secure usage patterns for AI-assisted software engineering; partner with engineering leaders and teams to integrate successful practices into delivery workflows, CI/CD pipelines, and quality processes; define baselines and success measures, evaluate adoption and outcomes, and use evidence to continuously improve approaches; mentor Staff, Senior, and other engineers, facilitate hands-on learning, and build a sustainable community of practice in India; influence technical decisions across services and systems, build consensus, and communicate recommendations to engineering and product leadership; remain hands-on by contributing code, reviewing designs, troubleshooting complex issues, and demonstrating new development techniques in real product environments

Requirements

Principal-level technical leadership, with a record of leading complex initiatives across multiple products, services, or engineering teams; AI-enabled software engineering expertise, including practical experience with generative AI, large language models, coding assistants, agentic workflows, or retrieval techniques; 10+ years of software engineering experience with a strong track record designing, building, and operating enterprise-grade SaaS solutions; strong proficiency in C# and .NET; experience with REST APIs and distributed systems; practical experience with modern web application frameworks such as React or comparable technologies; meaningful experience building on AWS or Azure; deep knowledge of CI/CD, automated testing, observability, secure development, code quality, and agile delivery; ability to evaluate privacy, security, intellectual property, reliability, and governance considerations for AI adoption; ability to define baselines and outcome measures; strong communication and collaboration skills; bachelor's degree in Computer Science, Engineering, or a related field is preferred

Nice to have

Experience leading AI adoption or developer productivity initiatives in a large engineering organization; hands-on experience with tools and platforms such as GitHub Copilot, Azure Foundry, Azure OpenAI, Amazon Bedrock, OpenAI APIs, or comparable technologies; experience designing AI agents, tool integrations, evaluation frameworks, prompt and context strategies, or retrieval-augmented solutions; experience with developer platforms, internal tooling, CI/CD automation, frontend and API test generation, code review automation, knowledge systems, or engineering analytics; experience working across modern web interfaces, service APIs, backend systems, and cloud infrastructure; experience supporting large-scale, multi-tenant SaaS products and modernizing established codebases and engineering workflows; demonstrated ability to coach others and turn experimentation into repeatable, broadly adopted engineering practices