Brillio

5 months ago

Data Science Lead

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 14 hours agoStatus: Live

Job Summary

Lead the architectural design and technical execution of an AI-enabled application, building agentic multi-agent systems and integration blocks to connect Generative AI agents with third-party apps. Drive live data ingestion, speech-to-text and NLU workflows, governance, and multi-LLM pipelines while guiding data scientists on RAG enhancements and enterprise data grounding. Lead scalable, low-latency, high-concurrency architectures for proactive incident triage and automated investigations.

Location: Bengaluru

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Drive Agentic AI Strategy: Lead the architectural design of autonomous agents capable of L1/L2 incident triage, automated investigation, and proactive threat hunting.
•Cross-App Integration: Develop reusable integration patterns (Event-Driven, WebSockets, REST) to ensure the app is the 'single pane of glass' for all connected applications.
•Conversational AI & STT: Design high-fidelity chatbot interfaces and real-time transcription services that allow operators to 'talk to the data' and receive voice-activated summaries of active incidents.
•Data Science Leadership: Partner with Data Scientists to fine-tune LLMs, optimize Retrieval-Augmented Generation (RAG) pipelines, and ensure model outputs are grounded in enterprise-specific data.
•Scalability & Resilience: Ensure the architecture supports high-concurrency, low-latency operations.

Key Requirements

•Experience leading AI/DS architecture and solution design for enterprise applications.
•Proficiency with multi-agent frameworks and integration patterns (Event-Driven, WebSockets, REST).
•Strong background in LLMs, Retrieval-Augmented Generation (RAG), and governance (guardrails, audit logs, human-in-the-loop).
•Hands-on knowledge of GenAI workflows: STT, NLU, data ingestion, and real-time reasoning pipelines.
•Familiarity with tools and frameworks such as AutoGen, LangChain, Semantic Kernel, TensorFlow, PyTorch, Keras, Scikit-Learn, CNTK, MXNet, Kubeflow, BentoML, GreatExpectations, Evidently AI.

Experience:AIData ScienceData Analytics

Skills:CommunicationLeadershipProblem-solving

Tech Stack:AutoGenLangChainSemantic KernelTensorFlowPyTorchKerasSci-Kit LearnCNTKMXNetKubeflowBentoMLGreat ExpectationsEvidently AISpeech-to-TextNLURAGAPIsWebhooks

Company Brief

Brillio

Provides digital transformation and IT consulting services, including cloud migration, analytics, digital engineering, and managed services to accelerate business outcomes for enterprises across industries.

Industry: Consulting

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Funding: Private Equity Backed

Headquarters: Santa Clara, United States

Founded: 2014

Website LinkedIn

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Brillio

5 months ago

Data Science Lead

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 14 hours agoStatus: Live

Job Summary

Location: Bengaluru

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Drive Agentic AI Strategy: Lead the architectural design of autonomous agents capable of L1/L2 incident triage, automated investigation, and proactive threat hunting.
•Cross-App Integration: Develop reusable integration patterns (Event-Driven, WebSockets, REST) to ensure the app is the 'single pane of glass' for all connected applications.
•Conversational AI & STT: Design high-fidelity chatbot interfaces and real-time transcription services that allow operators to 'talk to the data' and receive voice-activated summaries of active incidents.
•Data Science Leadership: Partner with Data Scientists to fine-tune LLMs, optimize Retrieval-Augmented Generation (RAG) pipelines, and ensure model outputs are grounded in enterprise-specific data.
•Scalability & Resilience: Ensure the architecture supports high-concurrency, low-latency operations.

Key Requirements

•Experience leading AI/DS architecture and solution design for enterprise applications.
•Proficiency with multi-agent frameworks and integration patterns (Event-Driven, WebSockets, REST).
•Strong background in LLMs, Retrieval-Augmented Generation (RAG), and governance (guardrails, audit logs, human-in-the-loop).
•Hands-on knowledge of GenAI workflows: STT, NLU, data ingestion, and real-time reasoning pipelines.
•Familiarity with tools and frameworks such as AutoGen, LangChain, Semantic Kernel, TensorFlow, PyTorch, Keras, Scikit-Learn, CNTK, MXNet, Kubeflow, BentoML, GreatExpectations, Evidently AI.

Experience:AIData ScienceData Analytics

Skills:CommunicationLeadershipProblem-solving

Tech Stack:AutoGenLangChainSemantic KernelTensorFlowPyTorchKerasSci-Kit LearnCNTKMXNetKubeflowBentoMLGreat ExpectationsEvidently AISpeech-to-TextNLURAGAPIsWebhooks

Company Brief

Brillio

Industry: Consulting

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Funding: Private Equity Backed

Headquarters: Santa Clara, United States

Founded: 2014

Website LinkedIn