Principal Data Scientist - R01556906

Brillio; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Benefits offered by this job

Great Place To Work recognition

Job summary

A leading digital technology service provider is seeking a Principal Data Scientist to lead the design and deployment of autonomous AI systems. This hands-on role requires deep expertise in Agentic AI and Large Language Models, with a proven track record in engineering leadership. Candidates should have over 14 years of experience, strong programming skills in Python, and a solid understanding of AI technologies. The position offers opportunities for significant innovation and mentoring within cross-functional teams.

Qualifications

• 14–22 years of overall experience in AI/LLM/GenAI research or engineering.
• Experience leading POCs and production-grade implementations in Agentic AI.
• Excellent analytical, communication, and leadership skills.

Responsibilities

• Lead the architecture and fine-tuning of LLMs for business applications.
• Collaborate with cross-functional teams to operationalize LLM-based solutions.
• Mentor teams on prompt engineering and scalable AI system design.

Skills

Agentic AI

Large Language Models (LLMs)

Python

R

Scala

multi-agent workflows

LLM fine-tuning

data engineering

Education

Ph.D./M.Tech/M.S. in Computer Science, AI, Machine Learning, or related field

Tools

LangGraph

LangChain

AutoGen

CrewAI

Databricks

AWS

Azure ML

Vertex AI

Job description

Principal Data Scientist

Primary Skills

• Agentic AI, Large Language Models (LLMs), and enterprise‑grade AI/ML systems. The ideal candidate will lead the design, experimentation, and deployment of autonomous, multi‑agent AI systems leveraging LLMs, knowledge graphs, and reasoning frameworks.

Specialization

• Agentic AI and LLM with framework

Job Requirements

Brillio is the partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Backed by Bain Capital private equity, and growing at nearly 60% YoY since its inception, Brillio is one of the fastest growing digital technology service providers. We help clients harness the transformative potential of the four superpowers of technology – cloud computing, internet of things (IoT), artificial intelligence (AI), and mobility. Born digital in 2014, we apply Customer Experience Solutions, Data Analytics and AI, Digital Infrastructure and Security, and Platform and Product Engineering expertise to help clients quickly innovate for growth, create digital products, build service platforms, and drive smarter, data‑driven performance.

With delivery locations across the United States, Romania, Canada, Mexico, and India, our growing global workforce of over 6,000 Brillians blends the latest technology and design thinking with digital fluency to solve complex business problems and drive competitive differentiation for our clients. Brillio was awarded ‘Great Place To Work’ in 2021 and 2022. Learn more www.Brillio.com

We are seeking a highly accomplished Principal Data Scientist with extensive experience in Agentic AI, Large Language Models (LLMs), and enterprise‑grade AI/ML systems. The ideal candidate will lead the design, experimentation, and deployment of autonomous, multi‑agent AI systems leveraging LLMs, knowledge graphs, and reasoning frameworks. This is a strategic and hands‑on role at the intersection of data science, AI research, and engineering leadership.

Key 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.

Required Skills & Experience

• 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.

Preferred Qualifications

• Advanced degree (Ph.D./M.Tech/M.S.) in Computer Science, AI, Machine Learning, Data Science, or a related field.
• Publications, patents, or conference presentations in AI, NLP, or LLM domains.
• Experience in Generative AI governance, ethics, or AI system reliability.
• Hands‑on experience with open‑source LLM frameworks and custom dataset curation for fine‑tuning.