Senior Data Science Lead

Salary Range: 80 to 95 (Currency: USD) (Pay period: per-hour-wage)

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

• Brillio LLC is a fast growing, pure play Digital Transformation Solutions and Services firm backed by Bain Capital private equity. Founded in 2014 and headquartered in Silicon Valley, Brillio is focused on delivering design led solutions for our customers. We are not an IT Services company trying to pivot and support the “next big thing.” As a digitally native company, everything we have done and will continue to do, will have this laser focus.
• Our culture is driven by Brillio’s Core Values and it is the foundation of who we are as an organization. We equip and empower our employees to push boundaries with an ‘Founder’s Mindset’ spirit as they craft ‘Customer Success’ stories. With our customer-centric approach, we deliver ‘Excellence and Innovation’ at every level of our collaboration and this is what fuels Brillio’s growth story. While we are proud of our journey so far, ‘ Care and Compassion’ about our customers, employees and the community where we thrive in. We strive to stay committed to lighting up 100,000 young minds through our CSR efforts.
 
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)