GenAI Architect & Data Scientist

GenAI Architect & Data Scientist

Hours/Week: 40
Work Location: USA – Remote (Work from Home)

Position Overview

We are seeking a GenAI Architect & Data Scientist to design and build intelligent, scalable AI systems with a strong focus on Natural Language Processing (NLP) and Generative AI–driven conversational experiences.

The ideal candidate will combine deep data science expertise with architectural vision to deliver intent-driven, context-aware, and production-ready AI solutions across cloud platforms.

This role involves:

• Understanding user intent
• Designing conversational dialogue flows
• Applying generative AI techniques
• Operationalizing models using MLOps best practices
• Automating complex language interactions across multiple channels

Experience Required: 12+ years of hands-on and architectural experience in large-scale enterprise environments.

Key Responsibilities

 GenAI & NLP Solution Design

• Architect Generative AI solutions leveraging Large Language Models (LLMs)
• Build and optimize NLP pipelines for:
• Intent detection
• Entity extraction
• Sentiment analysis
• Summarization
• Conversational understanding
• Apply generative AI techniques to automate complex language-based interactions
• Design scalable architectures supporting multi-channel conversational platforms (web, chat, voice, APIs)

 Intent Design & Conversational AI

• Define clear intent hierarchies based on user behavior and business requirements
• Design accurate dialogue flows and fallback strategies
• Implement contextual conversation handling
• Improve accuracy using:
• Prompt engineering
• Fine-tuning
• Retrieval-Augmented Generation (RAG)
• Ensure conversational systems are natural, explainable, and aligned with business objectives

 Data Science & Model Development

• Develop, train, evaluate, and optimize ML and deep learning models for NLP use cases
• Work with structured and unstructured datasets
• Perform:
• Feature engineering
• Model experimentation
• Validation and performance optimization

 MLOps & Production Readiness

• Implement CI/CD pipelines for ML (MLOps)
• Enable model versioning, deployment, monitoring, and retraining
• Ensure production-grade readiness with:
• Observability
• Performance tracking
• Governance controls
• Partner with DevOps and platform teams for enterprise integration

 Cloud AI & Architecture

• Design and deploy AI solutions on cloud platforms:
• AWS
• Azure
• Google Cloud Platform
• Leverage managed AI/ML services for training and inference
• Ensure:
• Scalability
• Security
• Cost optimization
• Compliance

 Collaboration & Leadership

• Collaborate with product managers, engineers, UX designers, and business stakeholders
• Provide technical leadership for GenAI initiatives
• Mentor data scientists and engineers on NLP, GenAI, and MLOps best practices

Required Skills

Core Technical Skills

• Strong expertise in Natural Language Processing (NLP)
• Hands-on experience with Generative AI & Large Language Models (LLMs)
• Proven experience in Intent Design & Conversational AI
• Strong background in Data Science & Machine Learning
• Experience implementing MLOps pipelines
• Proficiency in Python for AI/ML development

Cloud & Platform Expertise

• Hands-on experience with AWS, Azure, or Google Cloud Platform AI platforms
• Experience deploying AI models at scale in cloud environments

Conversational AI Capabilities

Experience building intelligent conversational systems including:

• Intent classification
• Dialogue flow design
• Context management
• Prompt engineering
• RAG-based architectures

Preferred / Good to Have

• Experience with vector databases and semantic search
• Knowledge of AI ethics and bias mitigation practices