We are seeking a Senior AI Engineer / AI Architect to lead the design, build, and production deployment of high-impact AI systems with emphasis on Agentic AI, RAG / GraphRAG, Multimodal LLMs, and Knowledge Graph-driven intelligence.
You will own end-to-end solution architecture, mentor engineers, drive AI/ML infrastructure strategy, and partner closely with cross-functional stakeholders to deliver scalable AI products.
Responsibilities
- Design & deploy scalable end-to-end AI systems from POC to production
- Lead architecture for LLMs, RAG / GraphRAG, multimodal chat, agentic AI
- Design scalable model serving pipelines (GPU inference, low-latency optimizations)
- Build, operate, and optimize ML infrastructure on Azure / On-Prem / OpenShift / Kubernetes
- Implement automated evaluation frameworks (Evals), monitoring, explainability guardrails
- Champion modern dev workflows using PRD-based delivery, PR review, automated testing
- Mentor engineers & drive engineering excellence best practices
- Implement Knowledge Graph-based intelligence using TigerGraph / Neo4j
- Apply RL on top of clinical or complex decision workflows
- Collaborate with product, clinical & business teams to align models to requirements (FHIR/HL7)
Requirements
- Bachelor's or Master's in CS, Data Science, AI or related field
- 6+ years experience in AI/ML Engineering (must include production deployment)
- Strong Python & deep learning frameworks (PyTorch / TensorFlow)
- Hands-on production experience with Kubernetes, GPU inferencing
- Experience with LangChain / agentic frameworks / Multimodal pipeline orchestration
- Experience with Cloud (Azure preferred)
- Experience with CI/CD + testing for ML (pytest / unittest / pydantic)
- Knowledge Graph experience (TigerGraph / Neo4j) strongly preferred
- Reinforcement Learning exposure is a plus
- Healthcare data standards (FHIR/HL7) is a strong advantage
- Excellent communicator & mentor
ONLY CANDIDATES WITH THE REQUIRED SKILLS AND EXPERIENCE SHOULD APPLY TO THIS JOB!
