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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Data Scientist - **Company:** Energage, LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $175,000.0 - $195,000.0 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Software as a Service, Encodings, Data Visualization, Decision Support Systems, Python (Programming Language), Machine Learning, Search Technologies, Google Cloud, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Kubernetes, Data Analytics, Virtual Agents, Docker - **Published:** May 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=ae3ab842378e4081 ## About the Role Do you have experience in Python?, * 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., * 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 Tech, people science, employee experience, or organizational analytics. ## Description * 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., * 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. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [A Brief History of Data Storage](https://www.wearedevelopers.com/videos/974-a-brief-history-of-data-storage) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Got AI ideas but no money? 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