Description

You will design and implement scalable, secure AI solutions leveraging Generative AI, LLMs, and Agentic AI systems, establishing mature MLOps and LLMOps practices.

Responsibilities

• Architect and implement end-to-end AI workflows, covering data ingestion, model orchestration, prompt engineering, and enterprise integration.
• Develop and code frameworks to evaluate AI models, defining metrics and processes for accuracy, fairness, safety, and reliability.
• Lead the CI/CD for AI models by automating monitoring, versioning, and building scalable deployment pipelines.
• Guide data scientists and ML engineers to ensure adherence to architectural principles and AI best practices.
• Convert complex business challenges into actionable AI strategies, prototyping solutions to demonstrate feasibility.

Required Skills

• 7+ years of experience in software architecture, with 2+ years specializing in AI/ML.
• Expert proficiency in Python and hands-on experience with Azure AI/ML services.
• Demonstrated ability to build and deploy Generative AI solutions, including LLMs and diffusion models.
• Familiarity with and ability to develop agentic AI frameworks (e.g., LangChain, AutoGen).
• Expert knowledge of MLOps/LLMOps pipelines, including MLflow, Kubeflow, or Azure ML.
• Proven ability working with prompt engineering techniques, large model attunement, and vector databases.
• Solid understanding of data privacy regulations (HIPAA, GDPR, CCPA).
• Experience in medical insurance or healthcare preferred.
• Strong influence and leadership skills for technical discussions with cross-functional teams.

Key Skills

Education

Any Graduate