AI Automations Engineer

Job Description — AI Automations Engineer (Junior–Mid) Role: AI Automations Engineer (Junior–Mid) Location: Kalyan, Mumbai (on-site; field visits across Mumbai/Thane & Bengaluru) Company: Solastaa Hair and Skin Private Limited Office: Mohan Tribeca, Office No. 906–907, 9th Floor, Next to Mohan Altezza, Gandhare, Near K.M. Agrawal College, Kalyan (West) – 421301 Google Maps: https://g.co/kgs/289vsvz Timings: 11:00 AM – 8:00 PM (Mon–Sat) Contact: Shruti — +91 74004 38040 About Solastaa Solastaa is a fast-growing premium beauty & grooming brand with multi-city stores and a strong membership base. We use premium products and technology (CRM: Zenoti) to deliver consistent, luxury experiences. Why this role exists We are investing in AI to scale growth and efficiency across Solastaa (and support the preschool when relevant). We need an owner who can scout AI tools, build quick automations, deploy voice/chat agents, integrate with Zenoti/WhatsApp, and track ROI quickly. Key responsibilities Scout new AI tools weekly (agents, voice, chat, RPA, analytics), run short pilots, and recommend what to adopt. Build and maintain voice agents for missed calls: greet, capture intent, book callbacks, push leads to Zenoti/Sheets. Build WhatsApp chatbots for FAQs, offers, membership renewals, service guidance, and rebooking nudges; design smooth handoff to human. Create workflows with Zapier/Make/n8n; write small Python scripts for APIs/webhooks/JSON when needed. Connect Zenoti, Google Sheets, WhatsApp Cloud API/Twilio, email, and calendars; keep data clean and tagged. Build simple dashboards (Looker Studio/Sheets) for leads, calls, bookings, and reviews. Maintain a single source of truth for services, prices, offers, policies, and FAQs; enable RAG-style answers. Run A/B tests on prompts and flows; improve using real chat/call transcripts. Publish a weekly performance report with insights and next experiments. Train front desk teams; create “How-To” guides and Loom videos. Follow security best practices for API keys, access, logging, and PII. Outcomes and KPIs Missed-call response time under 5 minutes via voice/WhatsApp agent. Lead-to-booking conversion up by 15–25% in 90 days. 40–60 automation hours saved per store per month. 30–50% WhatsApp self-serve resolution rate. Lower cost per contact; higher incremental bookings and review velocity. Data hygiene: duplicates under 2%; over 95% records with correct store/service tags. Day-to-day work Ship and maintain voice agents, chatbots, and automations (Zapier/Make/n8n + Python). Integrate with Zenoti (APIs/exports), Google Sheets, WhatsApp Cloud API/Twilio. Build and update the FAQ/knowledge base from our menus, offers, and policies. Run small experiments, measure results, and iterate fast. Collaborate with marketing and front desk for scripts, offers, and review workflows. Must-have skills Python basics (requests, JSON, small scripts), APIs/Webhooks, GitHub. Hands-on with Zapier/Make/n8n (or similar). WhatsApp Business Platform (Cloud API) or Twilio experience, or strong willingness to learn. LLM fundamentals (prompts, system messages, guardrails, basic retrieval/RAG). Google Sheets/Looker Studio, GA4 basics, and UTM tagging. Clear written English; basic Hindi/Marathi for prompts and replies. Nice-to-have skills Zenoti experience; Dialogflow/Voiceflow; LangChain/LlamaIndex; SQL; Docker basics. Gradio/Streamlit for quick internal tools. Experience in retail/beauty/wellness or education service flows. Ideal profile Early-career engineer/developer (0–3 years) who ships fast and documents well. Degree: B.E./B.Tech/B.Sc (CS/IT) or equivalent skills with strong portfolio. Passion for automations; can demo side projects. Comfortable being on-site and running field tests with store teams. Growth and culture Direct visibility to founders, ownership of AI across stores and adjacent school ops. Test–learn–scale mindset: ship fast, measure, and improve. Tooling stack No/Low-code: Zapier or Make or n8n Messaging/Voice: WhatsApp Cloud API, Twilio LLM/Agents: OpenAI/Anthropic with simple retrieval from GDrive/Sheets/Notion Dashboards: Google Sheets + Looker Studio Dev basics: Python, GitHub, Postman, JSON, webhooks Nice-to-have: Dialogflow/Voiceflow, LangChain/LlamaIndex, Streamlit/Gradio Example success metrics after 90 days 20% higher booking conversion from missed calls. 40–60 automation hours saved per store per month. 30–50% of WhatsApp queries resolved without human help. More reviews per month, rating stable or better.