Data Scientist Economist responsible for creating new economic indicators and analyzing macro/micro trends. Focused on the insurance sector with emphasis on client advisory services.
About the role
- Principal Data Scientist leading design and deployment of multi-agent AI systems at Brillio. Driving innovation at the intersection of data science, AI research, and engineering leadership.
Responsibilities
- Lead the architecture, experimentation, and fine-tuning of LLMs (e.g., GPT, Claude, Mistral, LLaMA, Falcon) for business-specific applications.
- Drive Agentic AI POCs and production implementations using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or Semantic Kernel.
- Design and implement multi-agent systems with human-in-the-loop decision-making, contextual reasoning, and memory management.
- Collaborate with cross-functional AI engineering, data platform, and product teams to operationalize LLM-based solutions.
- Develop fine-tuning and RAG pipelines using open-source and proprietary foundation models.
- Lead research and evaluation of emerging AI/LLM technologies for internal innovation and client solutions.
- Mentor data scientists and ML engineers on prompt engineering, model alignment (RLHF/RLAIF), and scalable AI system design.
- Partner with business stakeholders to translate complex business problems into data-driven, AI-enabled strategies.
- Publish internal whitepapers and drive AI Center of Excellence (CoE) initiatives within the organization.
Requirements
- 14–22 years of overall experience with at least 4+ years in advanced AI/LLM/GenAI research or engineering.
- Deep expertise in Agentic AI and building multi-agent workflows using LangGraph, LangChain, AutoGen, CrewAI, or Haystack.
- Strong hands-on programming skills in Python, with working proficiency in R or Scala.
- Proven experience with LLM fine-tuning, adapter methods (LoRA, QLoRA, PEFT), RAG pipelines, and vector databases (e.g., Pinecone, FAISS, Weaviate, Milvus).
- Strong understanding of transformer architectures, tokenization, prompt optimization, and model evaluation metrics.
- Experience integrating LLMs with enterprise data systems, APIs, and orchestration pipelines (Databricks, AWS, Azure ML, Vertex AI).
- Demonstrated success leading POCs and production-grade implementations in Agentic AI use cases (knowledge assistants, automation, data analysis, etc.).
- Familiarity with data engineering, MLOps/LLMOps, and cloud-native AI deployment.
- Excellent analytical, communication, and leadership skills with a track record of mentoring teams and driving innovation.
Benefits
- Brillio was awarded ‘Great Place To Work’ in 2021 and 2022.
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