Senior AI Data Scientist

Requirements

• Experience embedding AI into SaaS or enterprise products , especially user-facing, decision-support systems.
• Hands-on experience designing or implementing MCP servers to expose tools, data, or workflows for agentic systems.
• Experience using AI to interrogate data, generate insights, and support analytical reasoning via natural language interfaces.
• Familiarity with vector databases and semantic search technologies (e.g., Pinecone, Weaviate, Chroma).
• Experience supporting AI-driven insights with analytics pipelines or data visualization .
• Working knowledge of cloud platforms (AWS, GCP, Azure) and containerized deployment (Docker, Kubernetes), without a focus on heavy infrastructure ownership.
• Interest or background in HR T

Additional Information

Senior AI Data Scientist Your Mission as a Senior AI Data Scientist Energage is seeking a Senior AI Data Scientist to join our AI and Product Innovation team. This role is designed for an AI-native, product-minded data scientist - someone who works fluently in Python, thinks in terms of models, agents, and reasoning systems, and enjoys turning ambiguity into intelligent product capabilities. You will help shape the future of Employee Experience and Talent Management by building AI-driven Advisors, Assistants, and Analysts that help leaders understand their organizations, ask better questions, and take better action. You will drive the design and delivery of production-grade AI systems built on large language models, agentic workflows, retrieval-augmented generation (RAG), and knowledge graphs. This is not a pure AI engineering or infrastructure role - it is a hands-on, applied AI and data science role focused on reasoning, analytics, and decision support, with strong ownership from concept through production. Accountability and Impact: In this role, you'll... Design and deliver AI-powered advisors, assistants, and analytic agents that reason over organizational data, context, and knowledge to support real workplace decisions. Build and maintain high-quality, production-ready Python services that power AI applications and backend services that integrate into Energage's platform. Apply, adapt, and fine-tune foundation models (OpenAI, Gemini, Claude, etc.) to deliver reliable, context-aware, and explainable AI experiences. Architect agentic AI systems that coordinate reasoning, planning, and tool use using frameworks such as CrewAI, LangChain, Autogen, or similar. Design and evolve RAG pipelines and knowledge-based approaches , enabling AI systems to ground responses in organizational data and domain expertise. Develop and systematically test prompting strategies, agent behaviors, and interaction patterns to optimize accuracy, robustness, and user trust. Enable conversational analytics , allowing users to explore data, generate insights, and answer complex questions through natural language. Partner closely with product managers, engineers, and researchers to move AI Capabilities from prototype to scalable, production-ready features . Stay current with emerging trends in Generative AI and Agentic AI, translating emerging techniques into practical product innovation. Clearly communicate AI concepts, tradeoffs, and insights to both technical and non-technical stakeholders. What Success Could Look Like (First 6-12 Months) One or more AI advisors or analytic agents you've designed are in production and actively used by customers. AI outputs are demonstrably grounded in data and trusted by users. Prompting, evaluation, and agent patterns you've established become reusable standards across the team. Product and engineering partners rely on you as a thought partner for AI-driven decision support. You help raise the overall bar for applied AI quality, safety, and clarity at Energage. What You Will Bring to the Role Required Qualifications 5+ years of experience in applied AI, data science, or machine learning , with meaningful hands-on work in generative AI. Strong Python expertise , with experience building data-centric or AI-driven services used in production environments. Practical experience working with LLM APIs (OpenAI, Anthropic Claude, Gemini, etc.). Deep skill in prompt engineering , including structured prompt design, evaluation, and iteration for complex, multi-step reasoning tasks. Solid understanding of agentic AI concepts , such as multi-agent coordination, planning, tool invocation, and memory. Experience designing and implementing RAG architectures , including vector search and knowledge-grounded reasoning. Familiarity with AI agent frameworks such as CrewAI, LangChain, Autogen, or similar tools. Track record of delivering production-quality AI solutions , including testing, monitoring, and iterative improvement. Strong communication skills and the ability to explain AI behavior, limitations, and outcomes clearly. Comfort operating in ambiguous, early-stage problem spaces , with curiosity and a strong sense of ownership.

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at energage? Share your experience