AI Engineer

skilled and innovative AI Engineer

Key Responsibilities:

LLM Deployment & Fine-Tuning

• Deploy and fine-tune self-hosted LLMs such as

  LLaMA, Mistral, MPT

  for use cases including personalized recommendations and age-aware product tagging.

AI Assistants & Search Tools

• Build internal AI assistants and intelligent search tools to improve user experience and operational efficiency.
  

RAG Pipelines & Vector Search

• Design and implement

  Retrieval-Augmented Generation (RAG)

  pipelines using tools like

  LangChain

  ,

  LlamaIndex

  , and vector databases such as

  FAISS, Pinecone

  , or

  Weaviate

  .

Moderation & Compliance

• Develop scalable moderation systems to detect and manage unsafe or non-compliant products.
  

Cloud-Based Backend Engineering

• Architect and manage scalable backend services on

  AWS

  , leveraging tools such as

  Lambda, ECS/Fargate, API Gateway, S3

  , and

  CloudWatch

  for reliable AI service delivery.

Model Deployment Automation

• Build

  CI/CD pipelines

  for automated model deployment, monitoring, and updates to ensure smooth AI operations.

AI API Integration

• Integrate and evaluate third-party AI APIs (e.g.,

  OpenAI, Anthropic, Perplexity

  ) while balancing trade-offs between local and hosted models.

Personalization & Operational Intelligence

• Develop intelligent personalization systems that adapt to contextual cues such as child’s age, gender, urgency signals (e.g., diaper restocking), and usage behavior.
  

Real-Time Ops Modeling

• Support real-time logistics and operations through models for

  demand forecasting, ETA prediction

  , and

  route optimization

  .

Required Skills & Qualifications:

• 1+ years

  of hands-on experience in AI/ML engineering focused on production-grade systems.
• Proven expertise in deploying and fine-tuning

  self-hosted LLMs

  (e.g., LLaMA, Mistral, MPT).
• Strong programming skills in

  Python

  , with experience using frameworks like

  FastAPI

  ,

  PyTorch

  , and

  HuggingFace Transformers

  .
• Experience with containerization and automation:

  Docker

  ,

  CI/CD

  .
• Solid grasp of

  cloud infrastructure

  (especially

  AWS

  ): Lambda, ECS/Fargate, S3, CloudWatch, DynamoDB.
• Hands-on experience with

  AI tooling

  such as

  LangChain

  ,

  LlamaIndex

  , and vector databases (

  FAISS, Pinecone, Weaviate

  ).
• Experience integrating and managing

  third-party AI APIs

  (OpenAI, Claude, Gemini, etc.).
• Excellent collaboration, communication, and documentation skills.
  

Nice to Have:

• Prior experience in

  e-commerce

  ,

  quick-commerce (Q-commerce)

  , or

  logistics

  domains.
• Familiarity with

  MLOps tools

  like

  MLflow, Airflow

  .
• Experience with

  GPU optimization

  for inference at scale.

What We Offer:

• A fast-paced, entrepreneurial environment.
  
• High ownership and autonomy in building next-gen AI products.
  
• Opportunities to work on cutting-edge AI applications with real-world impact.
  
• A collaborative, mission-driven team culture focused on innovation and scalability.
  

Let me know if you'd like this adapted for a specific platform or formatted for PDF/print.