Identify and deliver high-impact, low-effort AI use cases that demonstrate measurable business value.
Build AI solutions from concept to prototype, validate their effectiveness, and industrialize successful solutions.
Develop and deploy production-ready AI solutions using LLMs, RAG, embeddings, and agent-based technologies.
Partner with business and technology teams to identify opportunities where AI can improve efficiency, quality, decision-making, and user experience.
Continuously evaluate emerging AI tools, models, and frameworks and recommend their adoption where they provide clear business value.
Improve and scale successful AI solutions in collaboration with domain teams.
Establish reusable AI frameworks, patterns, and best practices to accelerate AI adoption across the organization.
Support teams in determining when to use AI, traditional automation, or rule-based solutions, and when to build versus buy.
Promote responsible AI adoption by addressing governance, compliance, hallucinations, edge cases, and AI output quality.
Build and maintain AI solutions using technologies such as Azure OpenAI, APIs, RAG, prompt engineering, and backend integrations.
Evaluate AI outputs and implement appropriate validation and compliance mechanisms.
Build internal AI capability through knowledge sharing, workshops, training, and a Community of Practice.
Enable teams to understand AI capabilities, limitations, available tools, and practical business applications.




Collaborate with international teams and other communities of practice to share use cases, learnings, and best practices.
Master's degree in Computer Science or equivalent practical experience.

- 4+ years of experience in AI, machine learning, AI platforms, or related technology roles.
- Proven experience building, prototyping, or deploying real-world AI solutions.
- Strong understanding of LLMs and applied AI.
- Strong understanding of AI/ML architectures, including LLMs, RAG, embeddings, and agent-based systems.
- Hands-on experience with the Azure AI ecosystem, including Azure OpenAI, API Management, monitoring, and identity and access management.
- Robust programming skills in Python; Node.js experience is an advantage.
- Experience working with OpenAI and Microsoft ecosystem APIs.
- Experience integrating AI solutions with APIs and backend systems.
- Understanding of data handling and AI output evaluation.
- Ability to identify and address hallucinations, edge cases, and reliability challenges in AI solutions.
- Good understanding of AI governance, compliance, security, and enterprise architecture.
- Ability to rapidly prototype, experiment, validate, and iterate on AI solutions.
- Experience working in Agile product teams using Scrum, Kanban, or similar methodologies.

Basic functional analysis skills, including use cases and UML.
Experience with embeddings, vector search, or Knowledge Graph technologies.
Plenty of opportunities to grow and develop.
Support for maintaining a healthy work-life balance, including vacation, personal, and sick time.

📌 AI / ML Specialist (Pune)
🏢 Edwards Vacuum
📍 Pune