Senior AI Engineer
Remote Engineer · Bengaluru · onsite · Posted 52d ago
About a minute. You'll make an account on the way through.
About this role
Location: Bengaluru
Work mode: Remote
Type: Full Time
Experience: 3–6 years
Key Skills: GenAI & LLM Development, RAG Pipeline Development, Vector Databases, LLM Evaluation & Evals, Python & FastAPI, MCP & Agentic AI, Hugging Face, Docker & Kubernetes/MLOps
What you'll be working on
VisioGen is building the future of AI-powered healthcare by developing human-verified clinical communication solutions for ophthalmology practices. We combine cutting-edge Generative AI with clinical expertise to build scalable, production-ready applications that enhance patient engagement and improve healthcare delivery.
We're looking for a Senior AI Engineer to help design, build, and scale the GenAI systems powering the platform, from retrieval and reasoning to evaluation and real-time data pipelines.
What you'll do
- Design, build, and maintain GenAI and LLM-based features across the VisioGen platform
- Develop and optimize RAG (Retrieval-Augmented Generation) pipelines, including data ingestion, chunking, retrieval, and real-time data updates
- Build, tune, and maintain vector database infrastructure to support semantic search and retrieval workflows
- Design and run evaluation frameworks (evals) to continuously monitor and improve model accuracy, quality, and safety
- Develop and maintain backend services using Python and FastAPI
- Build and extend agentic tooling using Model Context Protocol (MCP)
- Fine-tune, evaluate, and deploy models using the Hugging Face ecosystem
- Containerize and deploy services with Docker, and orchestrate with Kubernetes (K8s)
- Own MLOps practices across the model lifecycle: CI/CD, monitoring, versioning, and retraining pipelines
- Partner closely with product, clinical, and engineering stakeholders to translate requirements into robust, scalable AI systems
- Support a smooth knowledge transition as the team grows, and contribute to the broader AI roadmap
What we're looking for
- 3–6 years of experience in AI/ML engineering
- Hands-on experience building GenAI and LLM-powered applications
- Proven experience designing and shipping RAG systems in production
- Experience building evaluation frameworks (evals) for LLM/GenAI systems
- Working knowledge of vector databases
- Experience with data ingestion pipelines and real-time data update mechanisms
- Strong proficiency in Python and FastAPI
- Familiarity with Model Context Protocol (MCP)
- Experience with Hugging Face libraries and models
- Hands-on experience with Docker and Kubernetes
- Experience with MLOps practices and tooling (CI/CD for ML, model monitoring, and versioning)
- Strong problem-solving and analytical skills, with the ability to work through ambiguous technical challenges
- Experience in healthcare, medtech, or another regulated industry
- Exposure to LLM observability/tracing tools (e.g., Langfuse)
- Experience with multilingual or multi-channel conversational AI systems
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