AI Engineer

Design, build, and deploy AI agents and end-to-end agentic AI solutions that solve complex problems across multiple technical and manufacturing domainsWork directly with domain PhDs and subject-matter experts to understand, document, and translate complex scientific and manufacturing processes into practical AI workflowsTranslate domain expertise and process knowledge into structured workflows, agent architectures, tools, models, and production-ready agentic systemsDevelop agentic AI solutions using frameworks such as LangGraph, LangChain, Semantic Kernel, or other agent orchestration frameworksBuild multi-agent workflows, RAG pipelines, tool-calling agents, memory-enabled agents, and autonomous/semiautonomous workflows grounded in real-world domain knowledgeIntegrate agents with enterprise systems, APIs, databases, and specialized tools to enable real-world task execution and decision-makingDeploy, monitor, troubleshoot, and continuously optimize agentic AI solutions in production, with appropriate security, governance, reliability, and scalabilityRequirementsBachelor's degree in Computer Science, Engineering, or a related fieldStrong programming skills in Python with hands-on experience developing production-grade AI applicationsProven hands-on experience building and deploying Agentic AI systems in real-world production environmentsStrong experience with agent frameworks such as LangGraph, LangChain, Semantic Kernel, or equivalent frameworks, with a deep understanding of agent orchestration and workflow designDirect experience developing multi-agent systems, tool-calling agents, autonomous/semiautonomous workflows, RAG-based agents, agent memory, and agent-to-agent interactionsExperience designing and implementing real-world agent workflows involving tool integration, API calls, decision-making, planning, state management, human-in-the-loop processes, and workflow orchestrationExperience building LLM-based applications and integrating LLMs with enterprise data, APIs, databases, and external toolsAbility to work closely with technical domain experts and translate specialized scientific/process knowledge into effective agentic systemsStrong analytical, problem-solving, and process-mapping skills, with the ability to understand and work across unfamiliar technical domainsExperience deploying, monitoring, evaluating, and optimizing production agentic AI systems, including observability, reliability, security, governance, and MLOps practices