Design & build GenAI/LLM systems (LLM, RAG, agent-based apps).Architect and optimize distributed, cloud-based AI solutions .
Manage vector search (OpenSearch, vector DBs, PostgreSQL, Kafka) and ingestion pipelines.
Implement fine-tuning (LoRA/QLoRA, instruction tuning) and advanced prompting .
Develop reusable frameworks, evaluation methods, and production-quality pipelines.
Troubleshoot across ML lifecycle (data prep, training, fine-tuning, serving).
Mentor engineers and ensure engineering best practices (testing, security, reliability).

Required Skills & Qualifications - BS/MS in CS or related field; 4 + years in distributed/cloud software .
Hands-on with LLMs, RAG architectures, and GenAI techniques .
Robust in Python, shell scripting , and ML frameworks ( LangChain, LlamaIndex, MLflow, Kubeflow, KServe,



Triton ).
Expertise in vector databases, retrieval systems, and orchestration tools .
Experience in model optimization, inference scaling, and serving .
Familiarity with cloud platforms (AWS/Azure/GCP) and up-to-date MLOps practices.
Solid communication skills; ability to work with product, research, and customer teams.

Preferred Skills - Advanced degree (MS/PhD).
Depth in RAG architecture & vector search solutions .
Experience with multimodal models , DeepSpeed , FasterTransformer , PyTorch/JAX/TensorFlow.
Track record of publications or speaking engagements .

📌 Software Engineer Generative Ai Bengaluru
🏢 HealthAsyst
📍 Bengaluru