---
title: 'Data Scientist at Hyderabad at Brillio'
canonical: 'https://feeny.ai/job/data-scientist-at-hyderabad-brillio-hyderabad-andhra-pradesh-kms81z704tvv'
type: 'job'
last_seen: '2026-09-13'
---

# Data Scientist at Hyderabad at Brillio

- **Company:** Brillio
- **Location:** Hyderabad Andhra Pradesh, India
- **Work type:** hybrid
- **Posted:** 2025-09-30
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.lever.co/brillio-2/588d190c-d0b0-4718-8ea1-c380d5b17e4a

## Job description

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.

Know what it’s like to work and grow at Brillio: Click here

## About Brillio

## Company Overview
- **One-liner**: Brillio is a digital transformation consulting and technology services company that helps Fortune 1000 enterprises accelerate AI adoption and scale impact through its AI accelerator platform, ADAM.
- **Entity Type**: Private (backed by Bain Capital Private Equity)
- **Headquarters**: Dallas, Texas, United States
- **Founded**: 2014
- **Founders**: Not publicly disclosed (CEO: Raj Mamodia)

## Core Business
- **Primary industries**: IT Services and IT Consulting; Digital Transformation; AI and Data Engineering; Customer Experience Transformation; Digital Engineering; Infrastructure Engineering
- **Target customers**: Fortune 1000 enterprises (B2B, Enterprise)
- **Mission / purpose statement**: “The Enterprise AI Accelerator” – helping companies move from AI ambition to scaled impact, faster.

## Products & Services
- **ADAM (Agentic Data and Application Management)**: A self-service LLM model garden and GenAI platform for building, testing, and deploying over a hundred GenAI use cases at scale. Core accelerator for Brillio’s delivery.
- **Business-led transformation**: Strategy consulting and business process modernization.
- **Customer experience transformation**: Design, digital product engineering, and omnichannel experience.
- **AI and data engineering**: Predictive models, enterprise search, RAG systems, AI copilots, autonomous agents, multi-agent workflows.
- **Digital engineering**: Application modernization, platform engineering, cloud-native development.
- **Infrastructure engineering**: Cloud infrastructure, security, MLOps/LLMOps, and observability.

## Market Standing
- **Valuation / Market Cap**: Not disclosed (privately held)
- **Key Metric**: Annual revenue reported at **$1B** (latest available); total employees ~3,941 (+6.7% YoY) per LinkedIn, though company claims “over 6,000 customer-obsessed professionals” on its website.
- **Notable Investors / Partners**: Bain Capital Private Equity (parent company); Great Place to Work® certified in the USA.
- **Growth Signals**: +352 employees YoY; 14 delivery locations across North America, Europe, and Asia; expanding AI engineering roles; 616,797 LinkedIn followers (+24.4% yearly growth).

## Competitive Advantages
- **Enterprise AI focus**: Industrializing AI across every layer of the business – not just building demos but shipping production systems.
- **ADAM platform**: Proprietary accelerator that enables rapid deployment of GenAI use cases, shortening time-to-value for clients.
- **End-to-end ownership**: Engineers design, build, evaluate, and run agentic and GenAI systems that reach live users.
- **Scale and reach**: Global delivery footprint (USA, India, UK, Europe, Mexico, Canada, Romania) with deep Fortune 1000 client relationships.

## Strategic Focus
- **AI engineering at scale**: Moving AI from pilots to production with a focus on agentic systems, LLMOps, evaluation, security, and governance.
- **Continuous learning**: Brillio Academy, hackathons, mentoring, and certifications to keep skills current.
- **Talent development**: Hiring based on demonstrated ability (not just degrees); clear career paths from engineer to AI architect or technical leadership.
- **Diversity & inclusion**: Committed to a diverse, inclusive workplace; no discrimination based on protected characteristics.

## Why Work Here
- **Culture**: Rated 4.0/5.0 on Glassdoor (2,264 reviews) and 4.0/5.0 on LinkedIn; 80% would recommend to a friend; Great Place to Work® certified in the USA.
- **Work environment**: Engineers get meaningful ownership within clear guardrails – autonomy to make architecture and trade-off calls on their workstreams.
- **Learning & growth**: Brillio Academy, hackathons, personalized career development framework; exposure to cutting-edge GenAI and agentic AI projects.
- **Remote / hybrid / office**: Not explicitly stated, but global delivery locations suggest a mix of on-site and remote (roles posted across multiple countries).
- **Benefits**: “BYou” wellness program built on four pillars of wellness – personal and professional well-being and development.
- **Interview process**: Focus on software fundamentals, LLMs, RAG, agents, evaluation, and a design or debugging exercise; candidates should be ready to walk through a real system they shipped.

## Sources
1. [careers.brillio.com](https://careers.brillio.com/)
2. [brillio.com/about-us/who-we-are](https://www.brillio.com/about-us/who-we-are/)
3. [linkedin.com/company/brillio](https://linkedin.com/company/brillio)
4. [glassdoor.com/Reviews/Brillio-Reviews-E821879](https://www.glassdoor.com/Reviews/Brillio-Reviews-E821879.htm)
5. [wikipedia.org/wiki/Brillio](https://en.wikipedia.org/wiki/Brillio)

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