Technical Content Writer, AI

Schneider Electric; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Schneider Electric seeks a senior Technical Writer with Documentation Architect or Systems Analysis experience to design and drive next‑gen documentation through AI, automation, and SDLC integration.

This role bridges Engineering, Product Management and Technical Publications to transform engineering artifacts into high‑quality, authoring-ready content. It includes XML/DITA CMS work and advancing documentation automation.

Qualifications

• Experience in Technical Writing, Technical Communication, Systems Analysis, Knowledge Management, or a related field.
• Strong understanding of software development processes, Agile, source control, CI/CD, and release management.
• Experience translating technical concepts into clear, structured documentation.

Responsibilities

• Design and evolve documentation processes that integrate with the software development lifecycle.
• Define strategies for collecting, structuring, and reusing information from tools such as GitHub, Azure DevOps, Jira, CI/CD pipelines, testing systems, and architecture repositories.
• Identify opportunities to leverage AI and automation to generate documentation drafts, release notes, feature descriptions, and other documentation assets.
• Collaborate with Engineering, Product Management, QA, DevOps, and Technical Publications teams to establish documentation requirements and information flows.
• Create roadmaps and implementation plans for documentation automation initiatives.
• Define governance, quality standards, and validation processes for AI-generated content.
• Analyze existing documentation workflows and recommend improvements to increase efficiency, consistency, and scalability.
• Support the evaluation, selection, and implementation of documentation and knowledge-management tooling.
• Establish metrics to measure documentation quality, coverage, automation effectiveness, and content reuse.

Skills

Technical Writing

Systems Analysis

Knowledge Management

AI-assisted content generation

Stakeholder management

Tools

GitHub

Azure DevOps

Jira

Confluence

Docs-as-Code

Job description

We are seeking a senior Technical Writer with Documentation Architect or Systems Analyst experience to design and drive the next generation of technical documentation through AI, automation, and software development lifecycle (SDLC) integration.

This role will be responsible for defining and implementing scalable documentation processes that transform engineering artifacts, including epics, user stories, pull requests, code changes, architecture decisions, testing outputs, and release data, into high-quality documentation assets and authoring-ready content.

The successful candidate will act as a bridge between Engineering, Product Management, and Technical Publications, ensuring that valuable information created throughout the development process is captured, structured, and leveraged effectively. By combining documentation expertise, systems thinking, and AI-assisted workflows, this role will empower technical writers to focus on accuracy, clarity, and user value while reducing manual information gathering and content creation efforts.

The role also includes working partly as a technical writer in our XML/DITA-based content management system with existing processes to get a better understanding of the authoring needs.

Key Responsibilities

• Design and evolve documentation processes that integrate with the software development lifecycle.
• Define strategies for collecting, structuring, and reusing information from tools such as GitHub, Azure DevOps, Jira, CI/CD pipelines, testing systems, and architecture repositories.
• Identify opportunities to leverage AI and automation to generate documentation drafts, release notes, feature descriptions, and other documentation assets.
• Collaborate with Engineering, Product Management, QA, DevOps, and Technical Publications teams to establish documentation requirements and information flows.
• Create roadmaps and implementation plans for documentation automation initiatives.
• Define governance, quality standards, and validation processes for AI-generated content.
• Analyze existing documentation workflows and recommend improvements to increase efficiency, consistency, and scalability.
• Support the evaluation, selection, and implementation of documentation and knowledge-management tooling.
• Establish metrics to measure documentation quality, coverage, automation effectiveness, and content reuse.

Required Qualifications

• Experience in Technical Writing, Technical Communication, Systems Analysis, Knowledge Management, or a related field.
• Strong understanding of software development processes, including Agile methodologies, source control, pull requests, CI/CD pipelines, and release management.
• Experience working with Git-based repositories and collaborating with software engineering teams.
• Demonstrated ability to analyze complex systems and design scalable processes.
• Strong stakeholder management and communication skills.
• Familiarity with AI-assisted content generation and automation technologies.
• Experience translating technical concepts into clear, structured documentation.

Preferred Qualifications

• Experience with Docs-as-Code practices and documentation automation.
• Understanding of APIs, software architecture, and modern development workflows.
• Experience working with Azure DevOps, Jira, GitHub, Confluence, or similar platforms.
• Familiarity with large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and AI governance principles.
• Experience leading process transformation initiatives across multiple teams.

What Success Looks Like

• Documentation creation is proactively driven by development activities rather than manual information gathering.
• Technical writers spend more time refining and validating content and less time collecting information.
• AI-generated drafts provide reliable, high-quality starting points for documentation deliverables.
• Documentation coverage, consistency, and timeliness improve without increasing authoring effort.
• Engineering, Product, and Documentation teams operate within a connected, measurable documentation ecosystem.