Senior Professional LLM AI Engineer

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.
•    Leadership Skills – Should be able to work as a team lead, interface with team leads of other functions/departments, understand business requirements, cost sensitivity and translate the same to an appropriate solution that is feasible to develop and deploy.

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.
•    Understanding of business use cases, cost sensitivity, strong interpersonal skills, architecting skills and abilities to convince multiple stakeholders.
Qualifications
•    Bachelor or Masters or Higher in Computer Sciences, Data Sciences, or any related field
•    7+ years to 10-11 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.