---
title: 'Data Architect - R01570398 at Brillio'
canonical: 'https://feeny.ai/job/data-architect-r01570398-brillio-bengaluru-jm3txcvr2tj6'
type: 'job'
last_seen: '2026-09-07'
---

# Data Architect - R01570398 at Brillio

- **Company:** Brillio
- **Location:** Bengaluru, India
- **Work type:** hybrid
- **Posted:** 2026-08-26
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.lever.co/brillio-2/db235fac-6c7b-41a6-a6c2-7cfd6f5f7041

## Job description

Data Architect

Job requirements Experience Range: With at least 7 to 10 years of experience in data architecture, data science, advanced statistical modeling, and AI architecture Key Responsibilities:

- Design and architect robust data pipelines and frameworks to support advanced analytics, machine learning, and AI workloads
- Develop and implement statistical and AI models, including regression (linear and logistic), classification algorithms, forecasting techniques (ARIMA, exponential smoothing), and deep learning architectures
- Lead the integration of probabilistic graph models, advanced statistical tests (hypothesis testing, T-Test, Z-Test), and AI-driven solutions into production systems
- Collaborate with data scientists and engineering teams to optimize data workflows and AI model deployment using tools such as KubeFlow and BentoML
- Ensure data quality and integrity by implementing validation frameworks like Great Expectations and Evidently AI
- Manage and optimize large-scale data processing and AI environments using Python, PySpark, R, and SAS/SPSS
- Evaluate and select appropriate machine learning and AI frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet) for scalable model deployment
- Provide technical leadership in the adoption of emerging technologies and best practices in data architecture, advanced analytics, and AI solutions

Required Skills:

- Advanced proficiency in Python and PySpark
- Expertise in statistical analysis and computing
- Hands-on experience with SAS and SPSS
- Strong knowledge of hypothesis testing, T-Test, and Z-Test
- Experience with regression techniques (linear and logistic)
- Proficiency in probabilistic graph models
- Familiarity with Great Expectations and Evidently AI for data validation
- Forecasting expertise using ARIMA, ARIMAX, and exponential smoothing
- Working knowledge of KubeFlow and BentoML
- Experience with classification algorithms (Decision Trees, SVM)
- Experience architecting AI solutions and deploying deep learning models

Preferred Skills:

- Advanced experience with ML and AI frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
- Expertise in distance metrics (Hamming, Euclidean, Manhattan)
- Proficiency in R and R Studio
- Experience with scalable AI model deployment in cloud environments
- Knowledge of automated model monitoring, drift detection, and AI lifecycle management

Desired Qualifications:

- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
- Certification in Data Architecture, Data Science, or AI (e.g., Certified Data Professional, Microsoft Certified: Azure Data Scientist Associate, AI Architect certification)
- Certification in Machine Learning frameworks or platforms (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty)

## 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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