Generative AI Expert

Overview:

As a Generative AI Expert & Solutions Developer, you will be at the forefront of AI innovation, driving research, development, and implementation of cutting-edge GenAI solutions across multiple business verticals. This role demands deep technical expertise in AI/ML with specialized focus on Generative AI applications. You'll spend 90% of your time researching emerging AI technologies, architecting GenAI solutions, developing prototypes and production-ready code, and creating comprehensive business case studies that demonstrate AI's transformative potential. The remaining 10% involves technical content review and validation to ensure accuracy and relevance of AI/ML educational materials.

This is a high-impact technical role for AI practitioners who thrive on solving complex problems, building innovative solutions, and translating cutting-edge research into practical business applications.

Roles and Responsibilities:

Primary Focus (90% of role):

• Research & Innovation: Conduct in-depth research on emerging GenAI technologies, frameworks, and models (LLMs, diffusion models, multimodal AI, agentic systems, RAG architectures, etc.) and evaluate their applicability to business challenges.
• Solution Development & Prototyping: Design, develop, and deploy GenAI solutions and proof-of-concepts for various use cases across different product teams and business units using state-of-the-art tools and frameworks.
• Code Development: Write production-quality Python code for GenAI applications, including prompt engineering pipelines, fine-tuning workflows, API integrations, vector database implementations, and AI agent systems.
• Experimentation & Benchmarking: Design and execute experiments to evaluate model performance, conduct A/B testing of GenAI approaches, and establish best practices for implementation.
• Technical Documentation: Develop detailed technical documentation, architectural diagrams, implementation guides, and knowledge repositories for GenAI solutions.
• Stay Current: Continuously monitor the rapidly evolving GenAI landscape, experiment with new models and techniques, and bring insights from research papers and industry developments into practical applications.

Secondary Focus (10% of role):

• Content Review & Validation: Review and validate technical accuracy of AI/ML/GenAI educational content, ensuring alignment with current best practices and industry standards.
• Technical Quality Assurance: Collaborate with SMEs and instructional designers to ensure code examples, technical explanations, and AI concepts are presented accurately and reflect real-world implementation patterns.

Required Qualifications:

Education:

• Bachelor's or Master's degree in Computer Science, Engineering (B.E./B.Tech), Data Science, AI/ML, or related technical field
• Consistent academic record with minimum 65% throughout

Experience:

• Minimum 4 years of hands-on experience in Artificial Intelligence, Machine Learning, or Data Science
• Minimum 2 years of specialized experience working with Generative AI technologies (LLMs, prompt engineering, RAG systems, fine-tuning, GenAI frameworks)
• Proven track record of building and deploying AI/ML solutions in production environments

Technical Skills (Mandatory):

• Strong expertise in Generative AI concepts and applications: LLMs (GPT, Claude, Llama, Gemini), prompt engineering, fine-tuning, RAG architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings
• Advanced proficiency in Python with experience in AI/ML frameworks: LangChain, LlamaIndex, Hugging Face Transformers, OpenAI API, Anthropic API
• Solid foundation in traditional Machine Learning and Deep Learning: neural networks, model training, evaluation metrics, MLOps practices
• Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services
• Familiarity with MLOps tools and practices: model versioning, deployment pipelines, monitoring
• Strong understanding of data structures, algorithms, and software engineering principles

Technical Skills (Desirable):

• Experience with AI agents and autonomous systems frameworks (AutoGPT, LangGraph, CrewAI)
• Knowledge of model fine-tuning techniques (LoRA, QLoRA, PEFT)
• Familiarity with multimodal AI and computer vision applications
• Experience with evaluation frameworks and benchmarking methodologies
• Contributions to open-source AI projects or published research

Professional Competencies:

• Exceptional problem-solving abilities with a research-oriented mindset
• Strong coding skills with ability to write clean, maintainable, and well-documented code
• Excellent written and verbal communication skills ability to explain complex technical concepts to both technical and non-technical audiences
• Self-driven and proactive approach to learning and staying current with rapidly evolving AI technologies
• Ability to work independently on ambiguous problems while managing multiple concurrent projects
• Strong collaboration skills to work effectively with cross-functional teams including product, engineering, and business stakeholders
• Experience presenting technical findings and recommendations to leadership and decision-makers
• Adaptability and comfort with fast-paced, innovation-driven environments

What Sets This Role Apart:

This is a technical practitioner role, not a content creation role. You'll be hands-on with code, architecture, and implementation while contributing to the broader AI knowledge ecosystem through case studies and technical documentation. If you're passionate about pushing the boundaries of what's possible with GenAI and want to work on diverse, challenging problems across multiple domains, this role offers exceptional opportunities for impact and growth.