Data Science Lead – R01570347

Brillio; Bengaluru; On-site; INR 3,200,000 - 5,200,000; Full time

Job summary

Brillio is seeking an experienced AI/ML engineer to design and implement advanced ML/AI solutions, including LLM-based apps, across major cloud platforms. You will lead production AI/ML deployments, build autonomous AI agents, and drive MLOps practices to ensure security and reliability.

The role requires 8+ years in AI/ML, strong Databricks expertise, and hands-on experience with LLMs, vectors, and orchestration. Join a cross-functional team to deliver scalable enterprise-grade AI.

Qualifications

• Advanced hands-on programming in Python.
• Strong SQL skills with large structured/unstructured datasets.
• Solid ML/AI fundamentals with production experience.
• Hands-on experience building and deploying LLM-based apps.
• Expertise in agent orchestration, autonomous workflows, and memory management.
• Extensive use of Databricks AI Agents and Databricks ecosystem.
• MLOps/LLMOps including CI/CD, model lifecycle, experiments, deployment.
• Experience deploying AI models in Azure/AWS/GCP.
• Familiarity with LangChain or equivalent tooling.

Responsibilities

• Design and implement advanced ML/AI solutions including LLM-based apps.
• Lead deployment/operation of production AI/ML models across major clouds.
• Build and optimize AI agents, autonomous workflows, and memory management.
• Drive enterprise ML workloads within Databricks, leveraging key tools.
• Establish MLOps and LLMOps practices for lifecycle, tracking, monitoring.
• Develop RAG architectures, embeddings, and prompt engineering strategies.
• Ensure AI security, privacy, and guardrails; mitigate hallucinations.
• Mentor engineers and collaborate with cross-functional teams on scalable AI.

Skills

Python

SQL

ML fundamentals

LLM-based apps

Agent orchestration

Databricks ecosystem

MLOps/LLMOps

Cloud deployment

LangChain/semantic kernel

Vector embeddings

Education

Bachelor's degree in CS/AI/IT

TensorFlow Developer Certificate

Databricks Certified Professional Data Scientist

AWS Certified Machine Learning Specialist

Azure AI Engineer Associate

Tools

Databricks AI Agents

Model Serving

Unity Catalog

Vector Search

MLflow

Kubernetes

Docker

REST APIs

LangChain

Job description

Experience Range: With at least 8 years of experience in AI/ML engineering, machine learning, data science, software engineering, or related fields Key Responsibilities:

• Design and implement advanced machine learning and AI solutions, including LLM-based applications and agentic AI systems, to address complex business challenges and deliver measurable business outcomes
• Lead the development, deployment, and operation of production AI/ML and GenAI models across major cloud platforms such as Azure, AWS, or GCP, ensuring high availability and scalability
• Build, orchestrate, and optimize AI agents and autonomous workflows, focusing on robust memory, context management, and multi-agent architectures
• Drive enterprise AI/ML workloads within the Databricks ecosystem, leveraging Databricks AI Agents, Model Serving, Vector Search, MLflow, and Unity Catalog to enhance operational efficiency
• Establish and maintain MLOps and LLMOps practices, including CI/CD pipelines, model lifecycle management, experiment tracking, evaluation, and monitoring for continuous improvement
• Develop and apply RAG architectures, embeddings, vector databases, prompt engineering, and LLM evaluation frameworks to improve model performance and reliability
• Ensure AI security, responsible AI practices, data privacy, and effective mitigation of hallucination, prompt injection, and GenAI guardrails
• Mentor engineers and provide technical leadership, collaborating with cross-functional teams to deliver scalable, enterprise-grade AI solutions

Required Skills:

• Advanced hands-on programming experience in Python
• Proficiency in SQL and experience with large-scale structured and unstructured datasets
• Strong practical understanding of machine learning and AI fundamentals
• Hands-on experience building and deploying LLM-based applications
• Expertise in agentic AI including agent orchestration, autonomous workflows, tool/function calling, planning, task decomposition, memory, and context management
• Extensive hands-on experience with Databricks AI Agents and the Databricks ecosystem
• Experience with MLOps and LLMOps, including CI/CD, model lifecycle management, experiment tracking, and production deployment
• Proven experience deploying and operating AI/ML or GenAI models/applications in Azure, AWS, or GCP
• Expertise in RAG architectures, embeddings, vector databases/vector search, prompt engineering, and LLM evaluation
• Proficiency with LLM and GenAI frameworks/orchestration tools such as LangChain, LangGraph, Semantic Kernel, or similar technologies

Preferred Skills:

• Experience building enterprise-grade agentic AI platforms or multi-agent systems
• Expertise with Databricks Model Serving, Vector Search, MLflow, Unity Catalog, and related Databricks AI/ML capabilities
• Experience with Kubernetes, Docker, REST APIs, microservices, and CI/CD pipelines
• Experience with managed GenAI platforms such as Azure OpenAI, AWS Bedrock, or Google Vertex AI
• Experience with vector databases like Pinecone, Azure AI Search, Weaviate, or Databricks Vector Search
• Experience optimizing LLM applications for latency, throughput, scalability, token consumption, and cost

Desired Qualifications:

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Information Technology, or a closely related discipline
• Certification in machine learning, AI engineering, or data science from a recognized institution such as TensorFlow Developer Certificate or Databricks Certified Professional Data Scientist
• Certification in cloud platforms or MLOps, for example AWS Certified Machine Learning Specialist or Azure AI Engineer Associate