Principal Software Engineer

Job Title: Principal Software Engineer (AI,Fullstack)

Locations: Bengaluru

Reports to: Director of Software Engineering

A quick snapshot...

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.

Why it’s a big deal…

This role will help shape how Doc Auto uses AI across the software development lifecycle. You will identify high-value opportunities, validate them through hands-on implementation, and scale successful practices across the pillar. Your impact will extend beyond individual code contributions: you will mentor senior technical talent, build alignment across teams, and serve as the AI engineering champion for our India organization while keeping solutions secure, responsible, maintainable, and grounded in measurable business outcomes.

What you'll accomplish…

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 everyday 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 where approaches differ, 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.

Are you the person we’re looking for?

Principal-level technical leadership. You have a record of leading complex initiatives across multiple products, services, or engineering teams. You can work through ambiguity, anticipate future needs, build consensus, and influence decisions without relying on direct authority.

AI-enabled software engineering expertise. You have practical experience applying generative AI, large language models, coding assistants, agentic workflows, retrieval techniques, or related technologies to improve software engineering outcomes. You understand both the potential and limitations of these tools.

Hands-on software architecture and development. You have 10+ years of software engineering experience and a strong track record designing, building, and operating enterprise-grade SaaS solutions. You are comfortable moving from strategy to prototype to production-ready implementation.

Full-stack and cloud engineering. You have strong proficiency in C# and .NET, experience with REST APIs and distributed systems, and practical experience with modern web application frameworks such as React or comparable technologies. You also have meaningful experience building on AWS or Azure and understand how frontend, backend, platform, and delivery concerns work together.

Modern delivery practices. You have deep knowledge of CI/CD, automated testing, observability, secure development, code quality, and agile delivery. You can recognize workflow bottlenecks and implement scalable improvements that teams will use.

Responsible and secure AI adoption. You can evaluate privacy, security, intellectual property, reliability, and governance considerations and translate them into practical engineering guardrails.

Measurement and product thinking. You can define useful baselines and outcome measures, distinguish activity from impact, and prioritize solutions based on value, usability, adoption, and maintainability.

Communication and collaboration. You communicate complex technical ideas clearly to engineers, leaders, and cross-functional stakeholders. You are comfortable facilitating alignment, challenging assumptions constructively, and presenting recommendations with confidence and credibility.

Education. A bachelor's degree in Computer Science, Engineering, or a related field is preferred.

Here’s what will give you an edge…

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 without being limited to a single layer of the stack.

Experience supporting large-scale, multi-tenant SaaS products and modernizing established codebases and engineering workflows.

A demonstrated ability to coach others and turn experimentation into repeatable, broadly adopted engineering practices.

How success will be measured…

Adoption of effective AI-enabled practices across Doc Auto teams and workflows.

Demonstrated improvements in delivery efficiency, quality, developer experience, or operational effectiveness.

Reusable tooling, standards, and patterns that reduce duplicated effort across products and services.

Growth in practical AI capability among engineers and technical leaders in India.

Strong partnership and alignment across engineering, product, quality, security, and architecture stakeholders.

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