AI AUTOMATION ENGINEER

In-Office | 2-3 Years Experience

Not a prompt engineer. A builder. Someone who thinks in systems, builds agents, and explores what AI can do next.

ROLE OVERVIEW :

- Role : AI Automation Engineer

- Experience : 2-3 Years

- Work Mode : In-Office

- Joining : Immediate,15-20 days,1 Month

ABOUT THE ROLE :

We are building AI into the core of our operations not just as a feature, but as fundamental infrastructure. This role is for a builder who lives and breathes AI tools, understands how LLMs work under the hood, and is excited to develop intelligent agents, automate complex workflows, and push the boundaries of what is possible with every new model that ships.

We don't want someone who merely uses AI. We want someone who thinks about where AI should go, builds it there, and then asks what comes next.

WHAT YOU'LL OWN :

- Agent Development : Design and build custom AI agents for internal workflows from ideation to production.

- Model Exploration : Evaluate new AI models the day they drop benchmark, test, and decide how we use them.

- Tool Integration : Identify, test, and integrate AI tools across the org find the best fit for every use case.

- Workflow Automation : Map, reimagine, and automate manual processes using LLMs, APIs, and custom pipelines.

- Problem Solving : Take any business problem and explore how AI can solve it own research, prototype, and outcome.

- Internal Knowledge : Document AI usage, build best practices, and upskill the team on what you discover.

MUST-HAVE SKILLS :

AI & LLM Depth :

- Hands-on with LLMs OpenAI, Claude, Gemini, open-source models.

- Understands internals : context windows, tokenisation, RAG, fine-tuning.

- Advanced prompt engineering (few-shot, chain-of-thought, tool use).

- Experience building AI agents or multi-step AI workflows.

- Knows when to use which model and why.

Engineering Foundations :

- Strong coding skills Python is a must, any other language is a plus.

- Comfortable with APIs, webhooks, and third-party integrations.

- Experience with automation tools (n8n, Make, Zapier, or custom pipelines).

- Basic understanding of databases and data pipelines.

- Can take a problem from whiteboard to deployed solution.

TOOLS & ECOSYSTEM :

- LangChain / LlamaIndex, Langraph

- OpenAI API

- Claude API

- Gemini / Vertex AI

- Hugging Face

- RAG Pipelines

- Python

- FastAPI

- n8n / Make/Zapier/Autogen/ Opal google/CrewAI

- Vector Databases(Pinecone, milvus, Qdrant, ChromaDB, LanceDB, pgvector, MongoDB Atlas Vector Search)

- Cursor , Copilot ,Antigravity, Codex, Claude, Windsurf

- REST APIs

- Docker /Kubernetes

- AWS / GCP/Azure

BONUS GOOD TO HAVE :

- Experience with open-source models (Mistral, LLaMA, Qwen, DeepSeek, etc.).

- Knowledge of model fine-tuning, LoRA, or RLHF techniques.

- Built production-grade AI features in a live, scaled product.

- Familiarity with AI safety, hallucination mitigation, and output validation.

- Actively follows AI research tries new tools as they launch.

WHAT MAKES YOU A GREAT FIT :

- You read the paper, then build it : A new model drops you don't just read the blog post, you're already running tests on it.

- You think in use cases : Every meeting, every problem your brain asks 'where does AI fit here?' automatically.

- You understand the internals : Not just API calls you know what's happening inside the model and why it matters.

- You ship, not just explore : You turn experiments into real tools that real people use every day.

WHAT YOU'LL DO DAY-TO-DAY :

- Explore, benchmark, and adopt new AI models and tools as they emerge.

- Build, test, and deploy AI agents for internal business workflows.

- Design automation pipelines that connect AI capabilities to real processes.

- Audit existing workflows and propose AI-driven improvements.

- Research and document AI use cases specific to fashion and quick-commerce.

- Collaborate with product and engineering teams to ship AI-powered features.

- Run internal demos and knowledge sessions on what you discover.

WHY JOIN US :

- Direct Impact : Every agent you build touches real users and real revenue no abstract research.

- Innovation Time : Dedicated weekly time to explore and experiment with new AI tools fully supported.

- Fast Growth : Performance-based trajectory what you ship decides how fast you grow.

- Full AI Access : Fully equipped and supported environment to utilize top-tier AI capabilities.