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This is a remote position.
Job Summary:
We are looking for highly skilled AI Engineers with expertise in Large Language Models (LLMs) and hands-on experience with advanced AI platforms such as Gemini 2.5, GitHub Copilot, Glean, and other generative AI tools.
The ideal candidate will be able to design, develop, and deploy AI-powered solutions that enhance productivity, accelerate workflows, and drive innovation.
Healthcare industry experience is a strong plus .
Key Responsibilities:
Design and implement AI-driven solutions leveraging Gemini 2.5, Copilot, Glean , and other LLM-based platforms.
Integrate generative AI tools into enterprise workflows to improve knowledge management, search, and automation.
Collaborate with product, engineering, and data science teams to build scalable AI applications.
Fine-tune and optimize AI/LLM models for specific business and healthcare use cases.
Conduct experiments, perform benchmarking, and ensure high-quality AI deliverables.
Ensure compliance, security, and ethical usage of AI in production.
Stay up to date with the latest advancements in AI/LLMs, RAG, knowledge graphs, and healthcare AI trends .
Required Skills & Experience:
Proven hands-on experience with Gemini 2.5, GitHub Copilot, Glean , or similar LLM-based tools.
Solid understanding of LLM architectures, embeddings, and retrieval-augmented generation (RAG) .
Proficiency in Python, JavaScript/TypeScript, or similar programming languages .
Experience with cloud platforms (AWS, Azure, GCP) and AI/ML deployments.
Familiarity with Vector Databases (Pinecone, Weaviate, FAISS, Milvus, etc.) .
Knowledge of ML pipelines, APIs, and prompt engineering .
Excellent problem-solving, communication, and collaboration skills.
Preferred Qualifications:
Healthcare industry background or prior work on AI/ML healthcare projects (strong plus).
Experience with enterprise search systems and AI-driven knowledge management tools .
Exposure to LangChain, LlamaIndex, Hugging Face, OpenAI API , or similar frameworks.
Hands-on with AI copilots for development, clinical data processing, or decision support .
Strong understanding of data privacy and compliance (HIPAA, PHI handling, etc.) in healthcare.
