Brillio 2

<div>Senior Lead AI/ML Engineer</div>
<h2>Primary Skills</h2><ul><li>Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio </li></ul>
<h2>Job requirements</h2><ul><li>Experience Range: 6 to 8 years of experience developing modern software applications, including at least 5 years building and optimizing machine learning pipelines with Java, Python, or Scala, and 4 years working with distributed computing frameworks such as Spark, DASK, or Ray. Key Responsibilities: 1. Design, develop, and maintain scalable machine learning pipelines using Java, Python, or Scala to support advanced data science solutions. 2. Implement, optimize, and deploy distributed computing solutions leveraging frameworks such as Spark, DASK, or Ray to handle large-scale data processing and model training. 3. Lead the end-to-end delivery of low-latency inferencing solutions, ensuring robust performance and reliability in production environments. 4. Build and enhance deep learning pipelines for forecasting and personalization using frameworks such as PyTorch and TensorFlow. 5. Collaborate with cross-functional agile teams to design and implement RESTful web services and integrate machine learning components into broader service-oriented architectures. 6. Utilize real-time streaming technologies like Kafka or Storm to enable real-time data ingestion and processing for machine learning applications. 7. Drive experimentation, model evaluation, and statistical analysis using advanced techniques such as hypothesis testing, regression, and probabilistic graphical models. 8. Ensure quality and reproducibility of machine learning workflows by leveraging tools such as Git, JIRA, and containerization platforms like Docker or PCF. Required Skills: 1. Advanced proficiency in Java, Python, or Scala for software and ML pipeline development 2. Hands-on experience with distributed computing frameworks such as Apache Spark, DASK, or Ray 3. Deep understanding of machine learning frameworks including TensorFlow, PyTorch, Sci-Kit Learn, Keras, and MXNet 4. Expertise in statistical analysis and computing, including hypothesis testing, T-Test, Z-Test, and regression methods 5. Experience with real-time data streaming tools such as Kafka or Storm 6. Knowledge of building and deploying deep learning models for forecasting and personalization 7. Proficiency in RESTful web services and service-oriented architecture design 8. Experience with containerization technologies such as Docker or PCF 9. Familiarity with ML workflow orchestration tools like KubeFlow or BentoML 10. Proficiency with Git for version control Preferred Skills: 1. Experience with Great Expectations or Evidently AI for model monitoring and validation 2. Hands-on expertise in SAS, SPSS, or R/R Studio for advanced statistical modeling 3. Knowledge of advanced forecasting techniques including Exponential Smoothing, ARIMA, and ARIMAX 4. Familiarity with classification algorithms such as Decision Trees and SVM 5. Understanding of distance metrics like Hamming, Euclidean, and Manhattan Distance 6. Experience in container orchestration and deployment within cloud or hybrid environments 7. Experience using agile project management tools such as JIRA Desired Qualifications: 1. Bachelor's degree in Computer Science, Information Systems, Data Science, or a closely related field 2. Relevant certification in machine learning, data engineering, or distributed computing (such as TensorFlow Developer Certificate or Databricks Certified Associate Developer for Apache Spark) Additional Information: This role requires working from the office at Manyata Tech Park, Bangalore, for at least 4 days per week. </li></ul>

Senior Lead AI/ML Engineer

<div>About Brillio: </div><div> </div><div>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. </div><div>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.</div><div> </div><div>Sr. AI Engineer</div>
<h2>Primary Skills</h2><ul><li>Problem Formulation (Business problem to Data Science Problem), OKR Validation against statistical measures, Data Wrangling, Data Storytelling &amp; Insight Generation, Problem Solving, Excel VBA, Data Curiosity, Technical Decision Making (How many iterations to go for vs when to stop iterating), Communication &amp; Articulation: Vocal &amp; Written, Business Acumen (Consume new domains quickly to learn through data), Design Thinking, Data Literacy</li></ul>
<h2>Job requirements</h2>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: <a href="https://www.brillio.com/services-data-analytics/" rel="noopener noreferrer ugc" target="_blank">https://www.brillio.com/services-data-analytics/</a>
Know what it’s like to work and grow at Brillio: <a href="https://www.brillio.com/join-us/" rel="noopener noreferrer ugc" target="_blank">https://www.brillio.com/join-us/</a>
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

Senior AI Engineer

<div>
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 Orogen Group, and growing rapidly 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 5500 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 consistently. Learn more <a href="https://www.brillio.com/" rel="noopener noreferrer ugc" target="_blank">www.Brillio.com</a>.
 
Role Title: Full Stack AI Engineer Location: Coppell, TX Experience: 0–2 Years
Type: On-site 
 
The Role
Brillio is seeking motivated and technically skilled Full Stack AI Engineers to join our growing engineering team. This role focuses on building cloud-native, full-stack applications and integrating artificial intelligence capabilities through hands-on development, rapid prototyping, and modern software engineering practices.
 
The ideal candidate will have a strong foundation in programming and application development, with knowledge of Java, Python, React, and Node.js, along with experience developing agentic AI applications.
 
This is an exciting opportunity for early-career engineers to work with emerging AI technologies, contribute to innovative application development, and gain practical experience delivering modern digital solutions.
 
Key Responsibilities
<ul>
<li>Design, develop, and maintain Java-based microservices and modern web applications.</li>
<li>Build responsive, scalable frontend applications using React and backend services using Node.js.</li>
<li>Develop and integrate AI services, intelligent agents, and AI-powered development accelerators into applications.</li>
<li>Contribute to the development of agentic AI applications and intelligent automation workflows.</li>
<li>Build prototypes and proof-of-concept solutions to evaluate new technologies and business use cases.</li>
<li>Collaborate with engineering teams to develop, test, troubleshoot, and deliver software solutions.</li>
<li>Support cloud-native application development using AWS or Microsoft Azure.</li>
<li>Leverage AI-assisted development tools such as GitHub Copilot, Claude, Codex, or similar platforms to accelerate development.</li>
<li>Participate in application testing, debugging, performance optimization, and production delivery.</li>
<li>Stay current with emerging AI technologies, software engineering practices, and development tools.</li>
</ul>
 
What We Are Looking For?
<ul>
<li>0–2 years of software engineering or application development experience, including relevant internships or hands-on project experience.</li>
<li>Strong computer science fundamentals, programming knowledge, and problem-solving capabilities.</li>
<li>Knowledge of Java/J2EE, Python, Node.js, and React.</li>
<li>Understanding of Java microservices and modern full-stack application development.</li>
<li>Experience developing agentic AI applications or integrating AI agents into software solutions.</li>
<li>Familiarity with GitHub Copilot, Claude, Codex, or similar AI-assisted development tools.</li>
<li>Exposure to AWS or Microsoft Azure cloud development environments.</li>
<li>Ability to build, test, debug, and enhance software applications.</li>
<li>Strong learning agility and enthusiasm for emerging technologies, particularly generative AI and intelligent automation.</li>
<li>Excellent communication, collaboration, and analytical skills.</li>
<li>Ability to work effectively in a collaborative, fast-paced engineering environment.</li>
</ul>
 
Candidates should demonstrate the below listed critical leadership qualities:
Customer Advocacy – Lead with the client's business priorities and build relationships grounded in relevance, trust and measurable value.
Owner's Mindset – Take accountability for the territory, pipeline and results; approach every target account with a clear ambition to build a meaningful Brillio franchise.
Innovation Ethos – Bring new ideas and perspectives that challenge conventional thinking and create reasons for clients to engage.
Execution with Pace – Maintain urgency, discipline and momentum from initial access through contract closure.
Big Picture Thinking – Connect individual opportunities to broader client transformation agendas and Brillio's long term growth strategy.
Winning Through Teams – Mobilize the best of Brillio and its ecosystem to create differentiated propositions and win together.
 
Why Join Brillio?
Be a Founding Engineer. Build the Future of AI-Native Applications.
This is more than an entry-level engineering opportunity. It's a chance to join as a Founding Engineer, helping build the next generation of AI-native applications from the ground up.
You'll work at the forefront of emerging AI technologies, developing intelligent applications, integrating AI agents, and transforming innovative ideas into real-world solutions.
You'll have the opportunity to make a meaningful impact from day one, contribute to foundational technical decisions, and help shape how AI-native applications are designed, developed, and delivered.
 
If you're passionate about coding, excited by artificial intelligence, and eager to build technology that defines the future, we want to hear from you.
 
</div>

AI Engineer

<div>Lead Engineer</div>
<h2>Job requirements</h2><div>5–6+ years of recent, hands-on Python development, including ownership of production services, reusable libraries and automation—not only scripts, notebooks or data analysis. Practical FastAPI and Pydantic experience covering API creation, schema design, complex validation, serialization, async processing, error handling and testing. Strong conceptual, logical, physical and metadata modelling, including canonical models, data contracts, source-to-target mapping, schema versioning, lineage and data quality. Experience processing large JSON, YAML and SQL datasets, with practical knowledge of batching, retries, idempotency, caching and performance optimisation. Strong production engineering practices: PyTest, Git, code reviews, CI/CD, deployment, monitoring and production support. A hands-on go-getter who can contribute from day one, work independently and deliver production-ready solutions quickly. Financial-services or regulated-domain experience is preferred 5–6+ years of recent, hands-on Python development, including ownership of production services, reusable libraries and automation—not only scripts, notebooks or data analysis. Practical FastAPI and Pydantic experience covering API creation, schema design, complex validation, serialization, async processing, error handling and testing. Strong conceptual, logical, physical and metadata modelling, including canonical models, data contracts, source-to-target mapping, schema versioning, lineage and data quality. Experience processing large JSON, YAML and SQL datasets, with practical knowledge of batching, retries, idempotency, caching and performance optimisation. Strong production engineering practices: PyTest, Git, code reviews, CI/CD, deployment, monitoring and production support. A hands-on go-getter who can contribute from day one, work independently and deliver production-ready solutions quickly. Financial-services or regulated-domain experience is preferred</div>

Lead Engineer

<div>Software Development Engineer</div>
<h2>Job requirements</h2><ul><li>Proven experience building and shipping full-stack applications in a professional product-based environment.</li><li>Ability to independently own and deliver features or systems across sprint/release cycles.</li><div>Mandatory Skills &amp; Responsibilities</div><li>Strong hands-on experience with at least one modern backend stack, such as Java, Python, or Node.js/NestJS, with solid understanding of performance tuning, memory management, and concurrency.</li><li>Strong experience with modern frontend development using React and SSR-based frameworks where applicable, including routing, state management, and performance optimization.</li><li>Working knowledge of a major cloud platform such as GCP or Azure, including production deployments, containers, serverless services, messaging, IAM, and cost-aware operations.</li><li>Strong SQL fundamentals, including query optimization, indexing, schema design, and data modeling, with working knowledge of at least one NoSQL database.</li><li>Proven ability to design scalable and resilient systems using caching, load balancing, and event-driven architecture.</li><li>Comfortable working in an Agile/Scrum environment, with a track record of independently delivering features across sprints and releases.</li><li>Strong Git practices, including sensible branching strategies and clean release management.</li><li>Experience designing REST and/or GraphQL APIs, including versioning and backward compatibility.</li><li>Strong testing mindset, with experience in unit, integration, and contract testing.</li><li>Hands-on experience with Docker and container orchestration platforms such as Kubernetes.</li><div>AI Skills:</div><li>Comfortable using AI tools in day-to-day engineering work to move faster, work smarter, and stay cost-aware while doing it</li><li>Familiarity with Retrieval Augmented Generation (RAG) architectures — semantic layers for data retrieval and grounding LLM responses in real, trustworthy data</li><li>Practical experience with at least one LLM application framework (LangChain, LangGraph, Google GenAI tools, or similar) for prototyping and integrating AI-driven features</li><li>Exposure to agentic or multi-agent AI systems — agent roles, tool use, memory, and workflow orchestration.</li></ul>

Software Development Engineer

<div>Data Scientist</div>
<h2>Primary Skills</h2><ul><li>Classification (Decision Trees, SVM), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Great Expectation, Evidently AI, Hypothesis Testing, ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Probabilistic Graph Models, Python/PySpark, R/ R Studio, Regression (Linear, Logistic), SAS/SPSS, Statistical analysis and computing, Tools(KubeFlow, BentoML), T-Test, Z-Test </li></ul>
<h2>Job requirements</h2><ul><li>Langraph, agentic ai </li></ul>

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