AI Engineer (Agentic Systems, Full-Stack)
AI Engineer (Agentic Systems, Full-Stack) Overview: We are seeking a skilled AI engineer to join our team. In this role, you will be responsible for designing and developing agentic systems that leverage large language models and data to create intelligent, automated workflows. You will work across the full stack, integrating data sources, building backend services, and enabling user-facing applications powered by AI. You will use APIs, databases, and other data sources to support AI-driven applications, and collaborate with analytics and engineering teams to ensure solutions are scalable, accurate, and aligned with business needs. Responsibilities: Design and develop agentic systems, including multi-agent workflows and orchestration pipelines Build and integrate LLM-powered applications using APIs and modern AI frameworks Develop backend services (APIs, microservices) to support AI-driven workflows Work with data from various sources (APIs, databases, files) to support AI use cases Transform and prepare data for use in AI models and applications Collaborate with analytics and visualization engineers to ensure outputs meet business requirements Assist in building and maintaining lightweight data pipelines as needed Evaluate and improve prompting strategies, embeddings, and retrieval techniques Monitor and optimize system performance, including latency, cost, and accuracy Stay up-to-date with new AI engineering techniques and technologies and apply them as needed Requirements: Bachelor's degree in a relevant field such as Computer Science, Data Science, or a related field 1–2 years of professional experience building or supporting software or AI-driven systems in a work environment (internships and co-ops included) Hands-on experience working with LLM-based applications or agentic workflows in a professional or production setting Strong programming skills, including experience with: Python (preferred), Java (optional), Scala (optional) Experience working with APIs and backend development frameworks (e.g., Flask, FastAPI) in a job setting Familiarity with LLM frameworks or platforms (e.g., LangChain, LangGraph, OpenAI, Gemini) Basic SQL skills and experience working with structured and unstructured data Experience contributing to applications or pipelines deployed in cloud environments such as GCP, AWS, or Azure Understanding of data pipelines, APIs, and system integrations Excellent communication and collaboration skills in a team-based environment Ability to work independently and manage multiple tasks and priorities