Senior AI/ML & Generative AI Engineer
- Compensation
- Not disclosed
- Location
- Hyderabad; Bangalore
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Full time
- Experience
- 6+ years
- Category
- Ml / AI
- Posted
Skills
Full description
Job Title : Senior AI/ML & Generative AI Engineer (GitHub Copilot, Gemini, LLMs & Cloud Integration)
Experience : 6 - 8.5 Years
Location : Hyderabad, Bangalore
Employment Type : Full-Time
Job Summary :
We are seeking an experienced Senior AI/ML & Generative AI Engineer with 6 to 8.5 years of hands-on experience in designing, developing, and deploying AI-powered solutions. The ideal candidate should possess strong expertise in Machine Learning, Generative AI, Large Language Models (LLMs), AI agents/assistants, GitHub Copilot, Gemini, LangChain, cloud integration, and Python/R-based analytical workflows. The candidate will play a key role in building enterprise-grade AI applications, integrating GenAI capabilities into business processes, and enabling intelligent automation through modern AI frameworks and cloud-native architectures.
Key Responsibilities :
- Design, develop, and deploy scalable AI/ML and Generative AI solutions to address complex business challenges.
- Build and optimize applications powered by Large Language Models (LLMs) for enterprise use cases.
- Develop intelligent AI agents and assistants using frameworks such as LangChain and related orchestration tools.
- Leverage GitHub Copilot, Gemini, and other AI-assisted development tools to accelerate software delivery and improve developer productivity.
- Integrate GenAI capabilities with enterprise applications through APIs, vector databases, and cloud services.
- Develop end-to-end Retrieval-Augmented Generation (RAG) pipelines for knowledge management and conversational AI use cases.
- Fine-tune, evaluate, and monitor LLM performance to ensure accuracy, scalability, and reliability.
- Collaborate with cross-functional stakeholders to translate business requirements into AI-driven solutions.
- Design and implement data preprocessing, feature engineering, model training, validation, and deployment workflows.
- Build robust Python and/or R-based analytical pipelines for machine learning experimentation and production workloads.
- Integrate AI solutions with major cloud platforms and services while adhering to security and governance standards.
- Conduct code reviews, establish best practices, and mentor junior team members.
- Stay updated with emerging trends and advancements in AI, GenAI, agentic frameworks, and cloud technologies.