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About Brillio:
Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.
Data Scientist
Primary Skills
- Required Skills:
- • 4+ years of experience in Data Science, Machine Learning, or AI.
- • Strong Python programming skills and familiarity with AI/ML frameworks (TensorFlow, PyTorch, HuggingFace).
- • Hands-on experience with LLMs, prompt engineering, RAG, and vector databases (e.g., FAISS, Pinecone, Weaviate).
- • Practical knowledge of agentic AI frameworks (Langraph, CrewAI, AutoGPT, etc.). • Familiarity with orchestration tools like Airflow, FastAPI, or similar.
- • Good understanding of RESTful APIs, microservices, and cloud platforms (AWS/GCP/Azure).
- • Should have worked in the Healthcare insurance space from the payer side
Nice to Have:
- • Exposure to LangGraph, Semantic Kernel, or agent evaluation frameworks
- • Experience working in domain-specific AI applications (e.g., healthcare, insurance, customer service).
- • Demonstrated ability to iterate quickly on prototypes and scale them into production-grade components.
Specialization
- Data Science Advanced: Data Scientist
Job requirements
- Data Scientist
- About the Role:
- We are looking for a highly motivated Data Scientist with a strong foundation in building intelligent, autonomous, and goal-driven Agentic AI systems. The ideal candidate will have hands-on experience in designing, training, and deploying AI agents that leverage LLMs, RAG, and autonomous task orchestration to solve complex business problems.
- Key Responsibilities:
- • Design and develop agentic AI systems capable of planning, reasoning, and executing tasks with minimal human input.
- • Implement LLM-based agents using frameworks such as LangGraph, AutoGPT, CrewAI, AgentOps, or similar.
- • Build and integrate Retrieval-Augmented Generation (RAG) pipelines to enable contextual grounding for agents.
- • Fine-tune and prompt-engineer foundation models (OpenAI, LLaMA, Mistral, etc.) for domain-specific use cases.
- • Collaborate with cross-functional teams to identify use cases and implement scalable AI solutions.
- • Monitor agent performance, identify bottlenecks, and improve reliability and efficiency.
- Required Skills:
- • 5+ years of experience in Data Science, Machine Learning, or AI.
- • Strong Python programming skills and familiarity with AI/ML frameworks (TensorFlow, PyTorch, HuggingFace).
- • Hands-on experience with LLMs, prompt engineering, RAG, and vector databases (e.g., FAISS, Pinecone, Weaviate).
- • Practical knowledge of agentic AI frameworks (Langraph, CrewAI, AutoGPT, etc.).
- • Familiarity with orchestration tools like Airflow, FastAPI, or similar.
- • Good understanding of RESTful APIs, microservices, and cloud platforms (AWS/GCP/Azure).
- • Should have worked in the Healthcare insurance space from the payer side
- • Nice to Have: • Exposure to LangGraph, Semantic Kernel, or agent evaluation frameworks
- • Experience working in domain-specific AI applications (e.g., healthcare, insurance, customer service).
- • Demonstrated ability to iterate quickly on prototypes and scale them into production-grade components.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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