GenAI Solutions Lead: Strategy, Architecture & Pipelines

Good co India; United States; Remote; USD 180,000 - 260,000; Full time

Job summary

Good co India in the United States seeks a Senior GenAI Lead to define and execute the Generative AI strategy and technical roadmap. You will architect GenAI solutions, lead end-to-end development, and drive AI-enabled business outcomes across teams.

Responsibilities include leading prompt engineering, model evaluation, and building scalable architectures with vector databases, cloud platforms, and MLOps practices. Strong collaboration and cloud experience are essential.

Qualifications

• Hands-on Generative AI implementation experience.
• Experience with LLMs and foundation models.
• Knowledge of RAG, embeddings, vector databases.
• Experience deploying production AI apps on cloud platforms.
• Ability to lead technical teams across cross-functional partners.

Responsibilities

• Define and implement Generative AI strategy, roadmap, and architecture.
• Lead design, development, testing, deployment of GenAI solutions with LLMs.
• Build and optimise RAG pipelines, AI agents, chatbots, automation.
• Evaluate and integrate LLMs for business use cases.
• Lead prompt engineering, model evaluation, benchmarking, performance tuning.
• Design scalable AI architectures using vector databases, APIs, cloud platforms.
• Establish MLOps/LLMOps for deployment, monitoring, versioning.

Skills

Python

Analytical thinking

Problem solving

Communication

Stakeholder management

Education

Bachelor's degree in Computer Science/IT/AI/Data Science

Master's degree in AI/ML/CS/Data Science (preferred)

Tools

PyTorch

TensorFlow

LangChain

LangGraph

AWS

Azure

Google Cloud Platform

Docker

Kubernetes

CI/CD

Job description

Good co India in the United States seeks a Senior GenAI Lead to define and execute the Generative AI strategy and technical roadmap. You will architect GenAI solutions, lead end-to-end development, and drive AI-enabled business outcomes across teams.

Responsibilities include leading prompt engineering, model evaluation, and building scalable architectures with vector databases, cloud platforms, and MLOps practices. Strong collaboration and cloud experience are essential.