GenAI Engineer

Position: Generative AI Engineer

Location: Bengaluru / Remote

Employment Type: Full-time

Experience: 5+ Years

About Factspan

Factspan is a global pure-play data and analytics consultancy partnering with Fortune 500 leaders across Retail, Financial Services, and Hospitality. With 350+ experts across the USA, UK, Denmark, and India, we build scalable AI/analytics solutions that convert complex data into strategic business value.

Role Overview

We are seeking an autonomous, hands-on Generative AI Engineer (IC) to design, build, and deploy production-grade GenAI applications and services on Google Cloud Platform (GCP). In this role, you will own the end-to-end lifecyclefrom fine-tuning custom LLMs and implementing RAG pipelines to containerized deployment on Vertex AIdelivering robust, secure retail AI solutions with minimal supervision.

Key Responsibilities

• End-to-End LLM Development: Independently build, fine-tune, and optimize LLMs (Transformers, T5, BERT, GPT variants) for retail use cases (conversational agents, recommendation engines, content generation).

• RAG & Semantic Search Architecture: Design and implement production Retrieval-Augmented Generation (RAG) pipelines using vector databases (Pinecone, FAISS) and custom embedding models.

• Autonomous GCP Deployment: Deploy secure, low-latency AI applications and microservices on GCP (Vertex AI, GKE/Kubernetes, Cloud Run/Functions) within private VPC networks adhering to strict data privacy and encryption standards.

• MLOps & Pipeline Automation: Build and manage automated CI/CD and MLOps pipelines (Docker, TFX, Terraform) for model versioning, testing, real-time drift monitoring, and automated retraining.

• Collaboration & Quality: Partner directly with product, data engineering, and business stakeholders to translate domain requirements into high-performance, bias-mitigated, and compliant AI systems.

Key Requirements

• Education: Bachelors degree in Engineering (B.Tech / B.E. required; Masters is a plus).

• Core Experience: 5+ years in ML/AI, with 3+ years dedicated to developing and deploying Generative AI models and LLM-powered applications.

• Hands-On Independence: Proven track record as an Individual Contributor (IC) capable of building AI microservices and deploying to cloud infrastructure without hand-holding.

• GCP & Cloud Mastery: Advanced hands-on proficiency with Google Cloud Platform, specifically Vertex AI, GKE, BigQuery, and IAM/VPC security.

Tech Stack:

• Languages: Python (expert), SQL
• Frameworks: PyTorch, TensorFlow, Hugging Face Transformers.
• Vector Search & RAG: Pinecone, FAISS, LangChain / LlamaIndex, or native vector stores.
• MLOps & DevOps: Docker, Kubernetes, CI/CD pipelines, TFX/Kubeflow.

Preferred

Domain experience in retail or e-commerce personalization/NLP.

Active open-source contributions, technical publications, or relevant AI community projects.