AI Editorial & Content Pipeline Engineer

Duration: 3 Months

Stipend: ₹10,000/month + performance bonus · PPO pathway

Hardware: Mac Mini M2 Pro (Micro Spark) · DGX Spark for LLM processing

Stack: Python · LangChain · PubMed API · Whisper · WordPress REST API · Zoho Campaigns · FastAPI

AI Tools: This cohort will work in an AI-first development environment. You will use Claude Code and equivalent AI coding tools to implement architecture you design. Thinking and designing come first. AI handles implementation.

WHAT YOU WILL BUILD

This cohort will work in an AI-first development workplace. You will use Claude Code and equivalent AI coding tools to implement architecture you design. Thinking and designing come first. AI handles implementation.

TRD monitors hundreds of specialised journals, covers major industry events, and runs a contributor programme for domain professionals. The editorial pipeline — journal monitoring, content summarisation, contributor submission intake, article generation, newsletter distribution, and profile management — must run autonomously at scale. You build the factory.

The factory produces the content.

YOUR DELIVERABLES

- Build an autonomous journal monitoring pipeline: RSS and API sources → new publication detection → specialty classification → LLM summarisation → structured output → CMS publish + CRM tag
- Design a tiered scraper system for hundreds of sources: rate-limited, resumable, structured JSON output, editorial board extraction
- Build a contributor submission portal: web form → automated pre-screening → routing to review queue → acknowledgement emails — all automated with defined SLA
- Build an AI content generation pipeline:



source material → LLM draft → QA agent checks accuracy and flags issues → human review queue — never auto-publishes without approval
- Design automated newsletter generation and distribution: periodic digest compiled from content pipeline → formatted via template → Zoho Campaigns dispatch to segmented audience lists • Build a social content generator: structured content → WhatsApp carousels, LinkedIn posts, Instagram slides → auto-sized, auto-captioned, queued for scheduling
- Build contributor profile pages: submission accepted → citable URL generated → author profile on CMS with article archive — automated on acceptance trigger
- Build poll and interactive content automation: topic-specific polls → WhatsApp dispatch → response aggregation → results published on platform and social channels

WHAT WE LOOK FOR

- You can design a pipeline where one LLM generates content and another validates it before a human sees it
- You understand why domain content accuracy matters and design QA layers accordingly
- You are comfortable with async processing and queue-based architectures
- A background in life sciences, medicine, or biology is a genuine advantage

IDEAL BACKGROUND

- NLP pipelines: text extraction, summarisation, structured LLM output, named entity recognition
- PubMed API, CrossRef, Semantic Scholar, or equivalent research database integrations
- Whisper or equivalent ASR: speaker diarisation, timestamping, structured transcript export
- WordPress REST API or equivalent CMS integrations for automated publishing
- Email marketing automation: Zoho Campaigns or equivalent — list segmentation, template dispatch THIS IS NOT
- A writing or journalism role — you build the pipeline that writes
- The output is a 24/7 autonomous content engine, not articles you personally authored.

📌 AI Editorial & Content Pipeline Engineer (19/08/2026) (India)
🏢 TheRightDoctors
📍 India