Senior Data Scientist - R01550290

About Brillio:

Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.

Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.

Senior Data Scientist

Primary Skills

• Sagemaker Studio, Vertex AI, Data Robot, SageMaker, Privacy (Federated Learning, Privacy preserving Algorithms), Model Provisioning: Kubernetes, Kibana, Databricks ML, Model Monitoring, Explainability (SHAPE, LIME, SHAPLEY), Azure ML, Bias Detection/Correction in Data, Big Query ML, Azure Synapse ML, Deployment Strategies (A/B, Blue green, Canary), Model testing, Integration testing, Domino Datalabs, Model Experimentation

Job requirements

• Agentic AI Lead
• Tampa, FL (Hybrid 3 days)
• The Agentic AI Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation.
• Key Responsibilities:
• 1. Architecting & Scaling Agentic AI Solutions
• Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving.
• Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains.
• Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications.
• 2. Hands-On Development & Optimization
• Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability.
• Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning.
• Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making.
• 3. Driving AI Innovation & Research
• Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents.
• Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions.
• Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops.
• 4. AI Strategy & Business Impact
• Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings.
• Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production.
• 5. Mentorship & Capability Building
• Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures.
• Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents.
• Required Skills & Experience
• ✅ Strong hands-on experience with LangGraph and multi-agent AI development
• ✅ Proficiency in LLM orchestration (LangChain, LlamaIndex, OpenAI Function Calling)
• ✅ Expertise in reinforcement learning (RLHF, RLAIF) and self-improving AI agents
• ✅ Knowledge graph construction & RAG implementation for enhanced agent reasoning
• ✅ Experience deploying AI agents in production (GCP)

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