Senior Artificial Intelligence Solutions Architect

23 hours ago

Mumbai, Maharashtra, India beBeeArchitect Full time ₹ 14,08,000 - ₹ 37,12,000
Job Opportunity:

A leading life sciences organization seeks an AI Architect to spearhead the design and deployment of cutting-edge Generative AI solutions. This high-impact role is ideal for experienced architects passionate about applying LLM technology to solve complex problems in healthcare, research, and regulated environments.

This position requires a strong architectural mindset, deep understanding of AI governance in regulated environments, and ability to work closely with scientific and business stakeholders to translate domain needs into effective AI systems.

Required Skills & Qualifications:
  • 7+ years of experience in AI/ML solution architecture, including 2+ years working directly with LLMs and Generative AI
  • Proven success deploying production LLM applications, including prompt engineering, fine-tuning, and retrieval-augmented generation
  • Hands-on experience with enterprise-grade LLM APIs and orchestration frameworks
  • Proficient in Python for building orchestration pipelines, APIs, and experimentation frameworks
  • Strong expertise with Databricks ecosystem—Unity Catalog, Delta Lake, MLflow, and cluster orchestration
  • Deep knowledge of data governance, metadata management, and data lineage in large-scale, regulated environments
  • Experience integrating vector databases and implementing feedback systems
  • Ability to map domain problems to AI workflows in a modular, scalable, and secure way
  • Familiarity with deploying models in cloud or hybrid environments (AWS, Azure, or GCP)
Benefits:
  • Competitive compensation package
  • Opportunity to work with cutting-edge LLM technology
  • Collaborative and dynamic work environment
Others:

The architect will collaborate with data engineering, platform, and compliance teams to build end-to-end LLM workflows—integrating RAG pipelines, vector stores, prompt orchestration, and real-time inference.

They will use Databricks Unity Catalog to ensure robust governance of training and inference datasets, metadata, lineage, and access controls.

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