---
title: 'Sr. AI Engineer - R01572484 at Brillio'
canonical: 'https://feeny.ai/job/sr-ai-engineer-r01572484-brillio-davie-5rj5e5z0dr2p'
type: 'job'
last_seen: '2026-10-18'
---

# Sr. AI Engineer - R01572484 at Brillio

- **Company:** Brillio
- **Location:** Davie, FL
- **Compensation:** $150k–$155k
- **Work type:** onsite
- **Posted:** 2026-10-14
- **Last confirmed live:** 2026-10-18
- **Apply:** https://jobs.lever.co/brillio-2/c098ffb4-7e45-4274-8b8d-af245f66afaf

## 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.

Sr. AI Engineer

Primary Skills

- Problem Formulation (Business problem to Data Science Problem), OKR Validation against statistical measures, Data Wrangling, Data Storytelling & Insight Generation, Problem Solving, Excel VBA, Data Curiosity, Technical Decision Making (How many iterations to go for vs when to stop iterating), Communication & Articulation: Vocal & Written, Business Acumen (Consume new domains quickly to learn through data), Design Thinking, Data Literacy

Job requirements Experience Range: With at least 7 years of experience in data science and AI, including significant leadership in designing and operationalizing enterprise-scale AI platforms

Key Responsibilities:

1. Lead the design and architecture of end-to-end enterprise AI platforms, ensuring scalability, reliability, and operational readiness
2. Define and implement frameworks for model lifecycle management, MLOps/LLMOps, AI observability, and operationalization
3. Establish Responsible AI principles, governance frameworks, and technical guardrails to ensure compliance and ethical AI deployment
4. Drive platform-level technical decision-making to enable consistent and scalable enterprise AI adoption
5. Provide architectural leadership across business, data, technology, and platform teams to translate AI strategy into production-ready solutions
6. Evaluate emerging AI technologies and assess their applicability to enterprise AI platforms
7. Guide teams in selecting appropriate models, platforms, frameworks, and architectural patterns based on business and technical requirements
8. Collaborate with senior stakeholders to define the enterprise AI roadmap and platform strategy

Required Skills:

1. Expertise in enterprise AI platform architecture and operationalization
2. Advanced proficiency in MLOps/LLMOps frameworks and tools
3. Deep understanding of Responsible AI principles, governance, and compliance
4. Hands-on experience with cloud-based AI platforms (AWS, Azure, GCP)
5. Technical leadership in model lifecycle management and AI observability
6. Strong knowledge of GenAI architectures, LLMs, and AI orchestration
7. Experience with scalable, secure, and production-ready AI solutions
8. Proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)

Preferred Skills:

1. Experience establishing enterprise AI Centers of Excellence or platform teams
2. Knowledge of vector databases, RAG, and AI agents
3. Experience developing reusable AI architecture patterns and accelerators
4. Familiarity with business intelligence and reporting automation
5. Experience mentoring or leading cross-functional AI teams

Desired Qualifications:

1. Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
2. Certification in Data Science or Advanced Analytics from a recognized institution (e.g., Microsoft Certified: Azure Data Scientist Associate, IBM Data Science Professional Certificate)
3. Certification in cloud architecture or AI platform engineering (e.g., AWS Certified Solutions Architect, Google Professional Machine Learning Engineer)

Know more about DAE: https://www.brillio.com/services-data-analytics/

Know what it’s like to work and grow at Brillio: https://www.brillio.com/join-us/

## Equal Employment Opportunity Declaration

Brillio is an equal opportunity employer to all, regardless of age, ancestry, colour, disability (mental and physical), exercising the right to family care and medical leave, gender, gender expression, gender identity, genetic information, marital status, medical condition, military or veteran status, national origin, political affiliation, race, religious creed, sex (includes pregnancy, childbirth, breastfeeding, and related medical conditions), and sexual orientation.

## #LI-AY1

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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