Data Science Lead - R01570347

Brillio 2; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Brillio 2 is seeking a Data Science Lead with 8+ years of AI/ML experience to design and deploy advanced ML solutions, including LLM-based apps and agentic AI. You will lead production deployments across Azure, AWS, or GCP and mentor engineers in a fast-growing enterprise.

You will drive MLOps/LLMOps, RAG architectures, and robust AI security while collaborating with cross‑functional teams to deliver scalable AI platforms.

Qualifications

• 8+ years in AI/ML engineering, data science or related fields.
• Strong Python and SQL with large-scale data experience.
• Hands-on ML and AI fundamentals with production deployments.
• Experience building and deploying LLM-based apps.
• Expertise in agent orchestration and autonomous workflows.
• Extensive Databricks AI Agents experience and Databricks ecosystem knowledge.
• Experience with MLOps/LLMOps, CI/CD and model lifecycle management.

Responsibilities

• Design and implement advanced ML/AI solutions incl. LLM apps and agentic AI.
• Lead production AI/ML deployments across Azure/AWS/GCP.
• Build and optimize AI agents, memories, and multi-agent workflows.
• Drive Databricks AI workloads with Model Serving and Unity Catalog.
• Establish MLOps and LLMOps, including CI/CD and monitoring.
• Develop RAG architectures, embeddings and vector databases.
• Ensure security, privacy and guardrails for GenAI.
• Mentor engineers and provide technical leadership.

Skills

Python programming

SQL

ML fundamentals

LLM-based apps

agentic AI

Databricks AI Agents

MLOps/LLMOps

Azure/AWS/GCP deployment

RAG architectures

Prompt engineering

LangChain/SDKs

Kubernetes

Docker

Education

Bachelor's degree in Computer Science or related field

TensorFlow Developer Certificate

Databricks Certified Professional Data Scientist

AWS Certified ML Specialist

Azure AI Engineer Associate

Tools

Databricks

Kubernetes

Docker

REST APIs

LangChain/LangGraph

Pinecone/Vector DBs

Job description

Data Science Lead

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