Gen AI Lead

Good co India; India; Remote; INR 600,000 - 1,200,000; Full time

Job summary

Good co India seeks a senior GenAI leader to define and execute the Generative AI strategy, aligning roadmaps with business aims. You will oversee the design, development, testing, and deployment of GenAI solutions using LLMs, create RAG pipelines, AI agents, and chatbots, and drive scalable architectures with modern cloud and vector technologies.

The role requires hands-on experience with LLMs, prompt engineering, model evaluation, and performance optimization, plus strong leadership to mentor

Qualifications

• Bachelor's degree in computer science, information tech, AI, data science or related field.
• 5-10 years in software eng, ML, AI, or data science with hands-on GenAI experience.
• Strong programming skills in Python and frameworks like PyTorch, TensorFlow.
• Experience deploying production AI apps on cloud platforms (AWS/Azure/GCP).
• Knowledge of MLOps/LLMOps, CI/CD, monitoring and scalable architectures.

Responsibilities

• Define and implement Generative AI strategy and technical roadmap.
• Lead design, development, testing, and deployment of GenAI solutions using LLMs and foundation models.
• Build and optimize RAG pipelines, AI agents, chatbots, and intelligent automation.
• Evaluate, select, fine-tune, and integrate LLMs for business use cases.
• Lead prompt engineering, model evaluation, benchmarking, and performance optimization.
• Design scalable AI architectures using vector databases, APIs, cloud and distributed systems.
• Establish MLOps/LLMOps practices for deployment and monitoring.
• Ensure data privacy, security, reliability, responsible AI, and regulatory compliance.
• Collaborate with product, engineering, data science, and business teams to deliver high-impact AI use cases.
• Manage technical project delivery, resources, and stakeholder expectations.
• Mentor AI/ML engineers and establish GenAI best practices.
• Track emerging AI tech and drive innovation and cost optimization.

Skills

Python programming

LLM & GenAI implementations

Cross-functional collaboration

Problem-solving

Stakeholder management

Architectural design

Prompt engineering

Education

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

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

Tools

PyTorch

TensorFlow

LangChain

LangGraph

Docker

Kubernetes

AWS/Azure/Google Cloud

Vector databases

Job description

Role & responsibilities

• Define and implement the Generative AI strategy, technical roadmap, and architecture aligned with business objectives.
• Lead the design, development, testing, and deployment of GenAI solutions using LLMs and foundation models.
• Build and optimise RAG pipelines, AI agents, chatbots, and intelligent automation systems.
• Evaluate, select, fine-tune, and integrate LLMs for specific business use cases.
• Lead prompt engineering, model evaluation, benchmarking, and performance optimisation.
• Design scalable AI architectures using vector databases, APIs, cloud platforms, and distributed systems.
• Establish MLOps/LLMOps practices for model deployment, monitoring, versioning, and continuous improvement.
• Ensure AI solutions meet requirements for data privacy, security, reliability, responsible AI, and regulatory compliance.
• Collaborate with product, engineering, data science, and business teams to identify and deliver high-impact AI use cases.
• Manage technical project delivery, resource allocation, and stakeholder expectations.
• Mentor AI/ML engineers and establish best practices for GenAI development.
• Track emerging AI technologies and drive innovation, cost optimisation, and measurable business outcomes.

Preferred candidate profile

• Bachelor's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
• Master's degree in AI/ML, Computer Science, or Data Science preferred but not mandatory.
• 5 to 10 years of experience in software engineering, machine learning, AI, or data science, with hands-on Generative AI implementation experience.
• Strong programming skills in Python and experience with frameworks such as PyTorch, TensorFlow, LangChain, or LangGraph.
• Practical expertise in LLMs, RAG, embeddings, vector databases, prompt engineering, fine-tuning, and AI agents.
• Experience deploying production-grade AI applications using AWS, Azure, or Google Cloud Platform.
• Knowledge of Docker, Kubernetes, CI/CD, MLOps/LLMOps, model monitoring, and scalable system architecture.
• Strong understanding of AI evaluation, hallucination mitigation, guardrails, data security, and responsible AI practices.
• Proven ability to lead technical teams, manage projects, and collaborate across cross-functional teams.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.
• Ability to translate business requirements into secure, reliable, cost-effective, and scalable GenAI solutions.