Technical Content Engineer

Own the Narrative: Write and edit logically structured, reader-focused documentation that aligns with our Style Guide, ensuring a consistent voice across all Pigment help resources, for both human readers and AI agents.

Architect Information: Design intuitive content layouts and visual aids within our knowledge base, making strategic decisions on content length and structure to maximize user comprehension and self-service. Structure content so it can be reliably chunked, retrieved, and cited by AI agents, not only read by people.

Innovate with AI: Stay ahead of the curve by exploring and implementing AI-driven workflows to streamline content creation, from drafting and quality checks to content audits, while keeping editorial judgment at the center.

Train and Tune the Documentation Agent: Partner with Product and Engineering to improve the Documentation Agent in the Pigment platform. Curate source content, write and refine agent instructions and evaluation prompts, review agent answers for accuracy, and feed gaps back into the knowledge base.

Run Docs as Code: Manage content through Git-based workflows (Markdown, pull requests, and automated checks for links, structure, and style) so documentation ships in step with product releases.

Automate and Scale Content Operations: Build lightweight automation and AI-assisted workflows that reduce repetitive work, and make it easier for Product, Engineering, and Professional Services colleagues to contribute accurate documentation.

Master the Product: Proactively explore new product functionalities and build clear, relevant use-case examples that help customers bridge the gap between feature and value.

Collaborate and Influence: Build trust and rapport with cross-functional teams including Product, Engineering, Customer Success, and Professional Services to navigate blockers, gather requirements, and ensure documentation is ready at the moment of release.

Drive Strategy and Impact: Use data-driven insights, including both traditional knowledge base analytics and measures of how well content performs for agents (such as answer accuracy and retrieval quality), to recommend improvements to our knowledge base.

Thrive in Agility: Effectively prioritize and organize your tasks to meet deadlines in our fast-paced environment, maintaining focus on project goals even when demands or product priorities shift.

Be a Mentor: Act as a main contributor to our team's documentation standards, including AI and docs-as-code practices, and provide guidance to peers to ensure high-quality output across the board.

3-5 years of experience in technical writing, content strategy, or documentation engineering, preferably within the SaaS, EPM, or FinTech space.

Strong command of authoring, hosting, and collaboration tools, such as Document360, Jira / Confluence, Git / GitHub, and Markdown (VS Code).

Hands-on experience with docs-as-code workflows (Git, pull requests, Markdown, and CI-based checks).

Practical experience using LLMs in a writing workflow, including prompting, critically reviewing output, and building repeatable workflows.

An understanding of what makes content machine-readable as well as human-readable (consistent structure, self-contained sections, clear metadata).

Strong editorial judgment, including the ability to verify AI-generated content for accuracy and to produce content that automation can't get to the right standard on its own.

Proven ability to independently learn complex product functionality and translate it into clear, concise instructions for both technical and non-technical audiences.

Excellent verbal and written communication skills and a can-do attitude when faced with complex technical puzzles.

Experience using data and insights to inform content decisions and measure the effectiveness of documentation.

Highly collaborative mindset with the ability to work across various time zones and departments to achieve a common goal.

Professional fluency in English is required; proficiency in French is a significant advantage, as many of our Product colleagues are French speakers.

Scripting ability (Python or JavaScript) for automation.

Familiarity with RAG concepts, llms.txt, or MCP.

Experience evaluating or improving the output of an AI assistant or agent.

Experience with OpenAPI or generating reference documentation from source.