- 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 .
- Strong 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 modern 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