Back
High due to Tier-1 brand, Bengaluru metro, popular mid-level ML title, and broad GenAI skillset requirements.
Medium — ML and GenAI skills transfer broadly, but enterprise integrations and energy-specific context add some domain specificity.
High due to explicit years plus mandatory GenAI/LLM frameworks, cloud, Python, and vector DB requirements.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop, test, and deploy AI applications using Large Language Models (LLMs) like GPT, Claude, and Llama.
Design and implement Retrieval-Augmented Generation (RAG) solutions, AI agents, prompts, and workflows for automating business processes and improving decision-making.
Integrate AI applications with APIs, databases, enterprise systems and collaborate with cross-functional teams to translate business requirements into AI solutions.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
2-4 years of experience in Software Development, AI/ML, Data Science, or related areas.
Strong programming skills in Python and familiarity with LLMs and Generative AI concepts.
Experience with GenAI frameworks (e.g., LangChain, Semantic Kernel), vector databases (e.g., FAISS, Pinecone), and cloud platforms (Azure, AWS, or Google Cloud).
Experienced in building AI copilots, chatbots, virtual assistants, and multi-agent AI workflows involving retrieval-augmented generation and semantic search.
Familiar with agentic AI frameworks like LangChain Agents, AutoGen, or Semantic Kernel and cloud-based AI services such as Azure OpenAI.
Comfortable working in a collaborative engineering environment supporting global business needs and deploying solutions aligned with responsible AI and governance practices.