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LLM AI Engineer at Gainwell Technologies. Location Information: Bangalore, KA, IN, 560100. . Summary . Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and . pipelines. for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps, and. . Role Description . Core LLM Ops Responsibilities:. • Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.).. • Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines.. • Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines.. • Manage vector databases, embedding stores, and document stores used in conjunction with LLMs.. • Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments.. • Continuously monitor models for its performance and ensure alert system in place.. • Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows.. Core ML Ops Responsibilities:. • Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring.. • Implement version control, model registry, and reproducibility strategies for ML models.. • Automate data ingestion, feature engineering, and model retraining workflows.. • Monitor model performance, drift, and ensure proper alerting systems are in place.. • Implement security, compliance, and governance protocols for model deployment.. • Collaborate with Data Scientists to streamline model development and experimentation.. . What We’re Looking For . • Bachelor's or Master's degree or higher in Computer Science, Data Sciences-Machine Learning, Engineering, or related fields. . • Strong experience with ML Ops tools (Kubeflow, ML flow, TFX, Sage Maker, etc.). . • Experience with LLM-specific tools and frameworks ( LangChain, Lang Graph, LlamaIndex, Hugging Face, OpenAI APIs, Vector DBs like Pinecone, FAISS, Weavite, Chroma DB etc.). . • Solid experience in deploying models in cloud (AWS, Azure, GCP) and on-prem environments. . • Proficient in containerization (Docker, Kubernetes) and CI/CD practices. . • Familiarity with monitoring tools like Prometheus, Grafana, and ML observability platforms. . • Strong coding skills in Python, Bash, and familiarity with infrastructure-as-code tools (Terraform, Helm, etc.).Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. . • Strong skills in Giskard, Deepeval etc.. Qualifications. • Bachelor or Masters or Higher in Computer Sciences, Data Sciences, or any related field. • 3+ years to 7 Years of experience in deploying ML/DL and LLM based solutions in large scale deployment environment or related experience. • Experience with fine-tuning LLMs and serving them in production at scale. . • Knowledge of model compression techniques for LLMs (LoRA, QLoRA, quantization-aware training). . • Experience with distributed systems and high-performance computing for large-scale model serving. . Awareness of AI fairness, explainability, and governance frameworks.. . What You Should Expect in This Role . • Fully Remote Opportunity – Work from anywhere in the U.S. / India. • Minimal Travel Required – Occasional travel opportunities (0-10%). . • Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. . . .