Hyderabad, India
Senior Data ScientistJob requirementsExperience Range 5 - 8 years of experience, including at least 5 years of hands-on work in data science, analytics, or related fields, with recent exposure to age....
Bangalore, India
Lead EngineerJob requirementsExperience Range With at least 4 to 6 years of full-stack development experience, including hands-on expertise architecting and reviewing AI-generated code for cloud-nati....
Bangalore, India
Data ScientistJob requirementsExperience Range With 4 to 6 years of experience in advanced data science roles, including hands-on involvement in machine learning and statistical modeling projects Key....
Bangalore, India
Data ScientistJob requirementsExperience Range With 4 to 6 years of experience in advanced data science roles, including hands-on involvement in machine learning and statistical modeling projects Key....
Bangalore, India
Quality EngineerJob requirementsExperience Range With 1 to 3 years of hands-on experience in Salesforce CPQ quality assurance, including direct involvement in testing and validating CPQ modules. Key ....
Bangalore, India
Software Development LeadJob requirementsExperience Range With at least 4 to 6 years of software development experience, including substantial hands-on work with Salesforce CPQ solutions Key Responsi....
A self-service AI model garden that sows the seeds of innovation
A self-service LLM Model Garden and GenAI platform for building, testing, and deploying over a hundred GenAI use cases at scale.
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We nurture an inclusive workplace environment that promotes collaboration, creativity, and innovation. Discrimination, harassment, or any form of unfair treatment will not be tolerated at Brillio. We have established clear policies and procedures to address such issues promptly. We believe that our commitment to creating an inclusive and diverse workplace not only makes us a better company but also contributes to a more just and fair society. Transparency in Coverage Rule – Machine-Readable Files (Applicable only in the U.S.)
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12 questions
Brillio is The Enterprise AI Accelerator, helping Fortune 1000 companies move from AI ambition to scaled impact. It delivers transformation powered by its AI Accelerator Platform, ADAM. Brillio delivers across five core workstreams: business-led transformation, customer experience transformation, AI and data engineering, digital engineering, and infrastructure engineering, combining industry expertise, modern engineering, and accelerators to deliver measurable outcomes.
Brillio invests in continuous learning through Brillio Academy, alongside mentoring, hackathons, and a personalized career development framework.
Engineers ship enterprise AI into production for real clients, not sandbox demos. Most work end to end: designing, building, evaluating, and running agentic and GenAI systems that reach live users.
No. Hiring is based on demonstrated ability. Strong software fundamentals, hands-on projects with LLMs, RAG, or agents, and clear reasoning about trade-offs matter more than a specific credential.
Engineers work on current agentic and GenAI problems, not legacy backlogs, with exposure to platforms like ADAM. Learning programs, hackathons, and certifications keep skills close to what's actually changing.
Both. Some engagements are net-new agentic builds; others modernize existing estates. The mix is transparent, so engineers can choose problems that match how they want to grow.
Common tracks run from engineer to AI architect, platform lead, and technical leadership. Growth follows demonstrated impact, not tenure, and staying deeply technical is a valid long-term path.
Interviews cover fundamentals plus applied depth: LLMs, RAG, agents, evaluation, and a design or debugging exercise. Candidates should be ready to walk through a real system they built and shipped.
Engineers get meaningful ownership within clear guardrails, making architecture and trade-off calls on their workstreams. Mentorship is available rather than rigid, top-down prescriptions on how to solve problems.
AI engineers build intelligent applications, predictive models, enterprise search solutions, RAG systems, AI copilots, autonomous agents, and multi-agent workflows. The focus is increasingly on moving AI from prototypes into scalable production systems. At Brillio, engineers solve business challenges across product engineering, application modernization, data, operations, and agentic AI using platforms such as ADAM.
Build strong software and machine learning fundamentals, then create hands-on projects using LLMs, RAG, agents, orchestration frameworks, APIs, and cloud platforms. Add evaluation, monitoring, security, and human oversight to understand production requirements. At Brillio, professionals gain practical exposure through enterprise AI projects, learning programs, hackathons, and opportunities to build agentic solutions using ADAM.
Future-ready AI engineers will need expertise in LLMs, agentic systems, orchestration, data engineering, cloud infrastructure, MLOps, LLMOps, evaluation, observability, security, governance, and responsible AI. Strong software engineering and problem-solving will remain essential. Engineers must also understand how to build reliable systems around probabilistic models and integrate them safely into enterprise applications and workflows.