Key Responsibilities:

- Solution Delivery Consulting
- Partner with client stakeholders to understand business goals translate them into AI ML and Generative AI use cases and define success metrics
- Contribute to solution design effort estimation and delivery planning for AI initiatives in a consulting environment
- Communicate findings trade offs and recommendations through explicit documentation and presentations
- Generative AI Development
- Build Python based prototypes and production ready components for Generative AI workflows prompting evaluation and iteration
- Develop and refine prompts templates and guardrails to improve response quality safety and consistency
- Implement evaluation approaches to measure output quality accuracy relevance hallucination checks and drive continuous improvement
- AI ML Engineering
- Develop and maintain ML pipelines in Python for data preparation training inference and monitoring
- Perform model experimentation feature engineering and performance tuning aligned to business requirements
- Collaborate with cross functional teams to integrate AI services into applications and workflows
- Minimum Qualifications
- 3 5 years of professional experience delivering Python based solutions including AI ML or Generative AI components




- Hands on experience with Generative AI concepts and implementation prompt engineering evaluation and iterative improvement
- Working knowledge of AI ML fundamentals supervised unsupervised learning model validation metrics
- Strong Python programming skills with clean coding practices testing and debugging
- Bachelor s degree in engineering or computers or AI

Technical Requirements:

- Technology AI ML Python Gen AI Databricks

Additional Responsibilities:

- Preferred Qualifications
- Experience delivering end to end AI ML solutions in a client facing or consulting setup including requirement discovery and stakeholder management
- Exposure to LLM application patterns such as RAG embeddings vector search and tool function calling
- Familiarity with MLOps practices such as experiment tracking model versioning CI CD for ML and production monitoring
- Experience with scalable data ML platforms and workflows e
- g
- Databricks style notebook to production practices
- Proven ability to balance rapid prototyping with production readiness including performance security and reliability considerations
- Good to have skills
- RAG Embeddings Vector Databases Prompt Engineering MLOps

Preferred Skills:

Technology->AI-AI Engineering->AI/ML Solution Architecture and Design->traditional ai ml,Technology->AI-Generative AI->Prompt Engineering

📌 Generative AI (Bengaluru)
🏢 Infosys
📍 Bengaluru