Experience Range: With at least 4 to 6 years of experience in ML engineering, including hands-on work with cloud-native architectures, agentic AI frameworks, and scalable full-stack systems Key Responsibilities:
Design and build end-to-end full-stack intelligent applications, integrating frontend, backend, and APIs using modern frameworks
Develop and deploy cloud-native solutions leveraging platforms such as Azure, AWS, and GCP
Build and implement agentic AI applications, including multi-agent systems and autonomous workflows
Develop scalable backend systems using microservices and event-driven architectures, optimizing for performance, security, and scalability
Work with LLM-based frameworks and agent orchestration tools to create intelligent, adaptive workflows
Ensure best practices in code quality, testing, debugging, observability, and performance optimization
Collaborate with cross-functional teams to translate business requirements into robust technical solutions and participate in architectural decisions
Required Skills:
Advanced proficiency in Python and JavaScript/TypeScript
Experience with frontend frameworks such as React, Angular, or Vue
Backend expertise with Node.js, Java Spring Boot, or Python (FastAPI, Django)
Hands-on experience with cloud platforms (Azure, AWS, GCP)
Proficiency in containers (Docker) and basic understanding of Kubernetes
RESTful API and microservices design
Experience with agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or CrewAI
Understanding of prompt engineering and Retrieval-Augmented Generation (RAG)
Familiarity with CI/CD pipelines
Preferred Skills:
Experience with autonomous systems or multi-agent architectures
Knowledge of conversational AI or AI-driven automation workflows
Familiarity with vector databases (FAISS, Pinecone, etc.)
Expertise in event streaming systems like Kafka or Pub/Sub
Contributions to open-source projects or hackathons in AI/ML or full stack domains
Desired Qualifications:
Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related discipline
Certification in cloud platforms (e.g., AWS Certified Machine Learning Specialty, Azure AI Engineer Associate, Google Professional Machine Learning Engineer)
Relevant certification in agentic AI frameworks or full-stack development (e.g., TensorFlow Developer Certificate, React Professional Certification)
This role builds full-stack intelligent applications, including agentic AI systems and LLM-powered workflows. It combines cloud-native application development, scalable backend architecture, and collaboration on technical design.
Role at a glance
AI engineeringFull-stack application developmentAgentic AI systemsCloud-native solutionsScalable backend systemsCross-functional collaboration
Skills mentioned
PythonJavaScript or TypeScriptReactAngularor VueNode.jsJava Spring Bootor Python backend frameworksAzureAWS
What you will likely work on
Build end-to-end applications spanning frontend, backend, and APIs.
Develop and deploy cloud-native applications on Azure, AWS, or GCP.
Implement agentic AI applications, multi-agent systems, and autonomous workflows.
Design scalable backend services using microservices and event-driven patterns.
Use LLM frameworks and orchestration tools to create adaptive workflows.
Apply code quality, testing, debugging, observability, security, and performance practices.
Translate business needs into technical solutions with cross-functional teams and contribute to architecture decisions.
Good fit signals
You bring 4–6 years of hands-on ML engineering experience, including cloud-native architectures, agentic AI frameworks, and scalable full-stack systems.
You have advanced proficiency in Python and JavaScript or TypeScript, with experience across frontend and backend development.
You have hands-on cloud platform experience and can work with containers, APIs, and microservices.
Experience with multi-agent systems, conversational AI, vector databases, or event streaming is helpful.
A relevant bachelor's degree and cloud or AI/full-stack certifications align with the stated desired qualifications.
Meet Brillio
Brillio is a technology consulting and services company that helps enterprises build and modernize software, data platforms and digital operations. Its services span AI and data engineering, application development, customer experience transformation, cloud infrastructure and security. It serves businesses in banking and financial services, insurance, healthcare and life sciences, retail, consumer goods, telecommunications and media. Its ADAM platform, short for Agentic Data and Application Management, provides tools to build, orchestrate and govern AI agents and supporting data workflows. Brillio combines consulting, engineering and implementation services to address legacy systems, fragmented data and the challenges of moving AI applications into production. Founded in 2014, the company is headquartered in Dallas and operates delivery locations across North America, Europe and Asia.
Founded
2014
Company size
5,001-10,000 employees
Company stage
Not known
Headquarters
Dallas, USA
Why work here
Brillio offers work on enterprise AI, cloud migration, application modernization and data platforms for large companies. Current engineering roles use React, Python, AWS, Azure, Databricks and Snowflake. Development programs include Brillio Academy, graduate training and Winspire for women leaders. Its role-specific AI training combines hands-on practice with assessment and earned two Gold Brandon Hall HCM Excellence Awards in 2026. Brillio's October 2026 U.S. Great Place to Work profile reports that 81% of respondents consider it a great workplace. Work arrangements depend on the project; some roles require client-office attendance or shifts.
RMRaj MamodiaChairman, Founder and Chief Executive OfficerView bioHide bio
Founded Brillio in 2014 and leads the company as chairman and CEO. Previously held technology and management roles at Larsen & Toubro, IBM and Cognizant. He holds a bachelor's degree in mechanical engineering from Motilal Nehru National Institute of Technology and an MBA from Northwestern University's Kellogg School of Management.
CDChander DamodaranChief Technology OfficerView bioHide bio
Leads Brillio's technology innovation and advises clients on digital and AI initiatives. He brings more than 25 years of experience in architecture, engineering, innovation and product development. His responsibilities include strengthening engineering capabilities and translating business needs into technology solutions.
SKSridhar KrishnamurthyChief Human Resources OfficerView bioHide bio
Leads Brillio's people strategy and culture. As a member of its founding leadership team, he has helped develop the workforce throughout the company's global expansion. His remit includes employee capability development and preparing technical, delivery, sales and leadership teams to apply AI in their work.
JKJitendra KukdayGlobal Head of the Growth OfficeView bioHide bio
Leads Brillio's Growth Office and brings more than 28 years of experience in IT services and business process outsourcing. His industry commentary focuses on modernizing legacy systems and data foundations so insurers can deploy AI in production.
JMJeff McMillanIndependent DirectorView bioHide bio
Joined Brillio's board in 2026, bringing experience deploying AI in financial services. Founder of McMillanAI, he previously led firmwide AI and wealth management analytics at Morgan Stanley and held senior roles at Merrill Lynch. He is a West Point graduate and teaches AI in financial services at Columbia University.
Brillio recognized as an ISG Leader for AI-driven application development
Brillio·
ISG named Brillio a Leader in the Application Development Projects category of its 2026 U.S. study, highlighting the ADAM platform, industry-focused delivery teams and application modernization capabilities.
Brillio joined Salesforce's invitation-only engineering partner network to support Agentforce deployments and enterprise AI adoption through closer collaboration with Salesforce product and engineering teams.
The partnership combines Brillio's ADAM accelerator and industry solutions with the Databricks Data Intelligence Platform to support data modernization, governance and production AI deployments.