Agentic AI and Data Engineer

Agentic AI and Data Engineer The Opportunity: As an experienced engineer, you know how to design, develop, and deliver production-grade agentic AI systems that demonstrate the practical value of generative AI, large language models (LLMs), and autonomous workflows. This role combines deep technical expertise with strong product skills to design AI applications that leverage prompting, retrieval-augmented generation (RAG), agentic orchestration, evaluation pipelines, and human-in-the-loop systems to deliver measurable impact. You will architect modular, reusable AI application patterns, integrate multiple model providers such as cloud-hosted, local, and hybrid, and apply modern GenAI stack capabilities, including structured prompting, tool use, workflow orchestration, and multi-modal reasoning. You will design solutions deployable across various contexts, from cloud-hosted platforms to portable, self-contained builds, optimizing for latency, cost efficiency, observability, and safety. You will rapidly prototype and iterate using AI-assisted development tools, validating hypotheses through eval-driven development and continuous experimentation. In this role, you’ll define the direction of mission-critical agentic systems by selecting and combining prompting strategies, RAG architectures, agentic workflows, and fine-tuned or foundation models as appropriate. You’ll be part of a [... source excerpt omitted ...] ment, and evaluation to enable rapid development of new AI capabilities. Integrate LLMs, embeddings, RAG pipelines, structured outputs, and long-context or memory mechanisms into production-ready systems. Apply advanced prompting techniques such as few-shot, chain-of-thought, tool-calling, and function-calling, orchestration frameworks such as LangChain or equivalent, and agentic architectures such as MCP, A2A, or similar patterns, to enable goal-directed autonomy with guardrails, observability, and human oversight, including planning, tool use, delegation, and recovery from failure. Design and implement evaluation frameworks, both offline and online, to measure correctness, rob [... source excerpt omitted ...] ble application artifacts. Use AI assistance tools to accelerate development, debugging, and system design while maintaining engineering rigor and code quality. Collaborate with clients to identify high-value AI opportunities and define solution requirements. Present AI capabilities and technical solutions to both technical and non-technical stakeholders. Lead workshops and prototyping sessions to accelerate adoption. Provide guidance on responsible AI practices, ethics, and compliance. Join us. The world can’t wait. You Have: 2+ years of experience with software engineering 2+ years of experience in AI or ML-focused roles in a professional work environment Experience