Please note: We only accept applications submitted through our official Enverus Careers Page or via LinkedIn. Applications received through other channels will not be considered.

Why YOU want this position

At Enverus, we’re committed to empowering the global quality of life by helping our customers make energy affordable and accessible to the world.  

We are the most trusted energy-dedicated SaaS company, with a platform built to maximize value from generative AI, and our innovative solutions are reshaping the way energy is consumed and managed. By offering anytime, anywhere access to analytics and insights, we’re helping our customers make better decisions that help provide communities around the world with clean, affordable energy. 

The energy industry is changing fast. But we’ve continued to lead the way in energy technology, creating intelligent connections across the entire energy ecosystem, from renewables, power and utilities, to oil and gas and financial institutions. Our solutions create more efficient production and distribution, capital allocation, renewable energy development, investment and sourcing, and help reduce costs by automating crucial business operations. Of course, this wouldn’t be possible without our people, which is why we have built a team of individuals from a diverse range of backgrounds. 

We are currently seeking a Technical Product Intern – AI & GenAI, you will work at the intersection of product, artificial intelligence, and analytics to help shape AI-powered products. You will collaborate with product managers, engineers, and AI teams to evaluate model performance, analyze product insights, prototype AI solutions, and support the development of new product capabilities. 

This role is ideal for someone who enjoys solving problems with data, experimenting with the latest AI technologies, and rapidly building proof-of-concepts while gaining exposure to AI product development. This is a 6-month internship that requires working from our Bangalore office.

Performance Objectives 

• Analyze product usage, AI performance, and customer feedback to identify trends and opportunities.
• Support the creation of Ground Truth datasets and evaluation (Evals) for AI models, prompts, and agent workflows.
• Build lightweight AI prototypes, such as chatbots, AI agents, and workflow automations, to validate product ideas and demonstrate new capabilities.
• Experiment with LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), and agentic workflows to explore innovative solutions.
• Build dashboards and reports to monitor product adoption, AI performance, and evaluation metrics.
• Assist Product Managers in defining product requirements, documenting user stories, and validating new features.
• Research emerging AI technologies and evaluate their applicability to product development.
• Present insights, prototype demonstrations, and recommendations to technical and business stakeholders. 

Competitive Candidate Profile

• Strong analytical and problem-solving skills.
• Hands-on programming experience in Python (mandatory).
• Knowledge of SQL and data analysis.
• Working knowledge of JIRA/confluence.
• Understanding of Generative AI, Large Language Models (LLMs), and modern AI applications.
• Familiarity with prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and agentic workflows.
• Familiarity with APIs and integrating AI models into lightweight applications.
• Experience with data visualization tools such as Power BI, Tableau, or similar.
• Strong communication and presentation skills.
• Strong product mindset with the ability to think from a user and customer perspective.  

Preferred Qualifications 

• Academic or personal projects involving AI applications, product analytics, or automation.
• Experience building chatbots, AI assistants, or agent-based applications.
• Exposure to AI evaluation frameworks and benchmarking LLM performance.
• Familiarity with vector databases, embeddings, and semantic search.
• Basic understanding of Agile product development, user stories, and product lifecycle concepts