Educational Requirements

- Bachelor of Engineering, BTech, BCA, BSc, MTech, MSc, MCA

Service Line

- Data Analytics Unit

Responsibilities

- Key ResponsibilitiesDevelop and deploy Generative AI applications using LLMs (GPT, Llama, etc.)

- Build and maintain LLM pipelines, including prompt engineering and fine-tuning

- Design and implement end-to-end AI/ML workflows (data model deployment)

- Work with vector databases for semantic search and retrieval (RAG architecture)

- Implement LLMOps practices for monitoring, evaluation, and versioning

- Integrate LLMs into applications via APIs and microservices

- Optimize model performance, cost, and latency

- Collaborate with data engineers, product teams, and stakeholders

- Conduct testing, validation, and debugging of AI models

- Ensure security, compliance, and responsible AI practices

Additional Responsibilities

- Experience with fine-tuning LLMs / parameter-efficient tuning (LoRA, PEFT)

- Knowledge of multimodal AI (text,



image, audio)

- Exposure to cloud platforms (AWS, Azure, GCP)

- Experience with Kubernetes and scalable deployments

- Knowledge of data engineering tools (Spark, Kafka)

- Familiarity with vector search optimization and embeddings

- Understanding of AI governance, ethics, and compliance

- Experience with chatbots, copilots, or conversational AI systems

Technical and Skilled Requirements

- Primary skills:Technology- >Data Science- >Machine Learning, Technology- >Geographical Information System- >Spatial Databases- >SQL Server, Technology- >Machine Learning- >Python

Preferred Skills

- Technology- >AI-Data science- >PYTHON

- Technology- >AI-Data science- >Machine Learning

- Technology- >AI-Generative AI- >Generative AI - Basic- >retrieval augmented generation (rag)

📌 Python Professional -GenAI-LLMOps (Bengaluru)
🏢 Infosys
📍 Bengaluru