Job Description

Principal Data Scientist - R01554881

=========================================

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

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.