AI Engineer with machine learning expertise
Eliassen Group
Location
πΊπΈ United States
Type
full_time
Salary
Undisclosed
Posted
3w ago
Job Description
Requirements
Must have: - Proven experience in developing agentic AI solutions, specifically LLM tool integration and function execution in multi-step workflows. β’ Strong background in data handling across structured and unstructured formats, including data modeling and collaboration with analytics teams. β’ Demonstrated proficiency in implementing retrieval-augmented generation (RAG) in production or nearly production scenarios, covering all aspects from ingestion to grounding. β’ Solid foundation in backend engineering principles, including API development, service design, and reliability mechanisms. β’ Proficient in Python or another backend programming language such as Java, Go, or TypeScript, with strong software engineering practices like testing and continuous integration/deployment.
Responsibilities
: - Develop AI agents that can plan and carry out business workflows involving multiple actions, including understanding inquiries, retrieving relevant context, executing tasks, confirming results, and documenting outcomes. β’ Convert vague business challenges into consistent agent workflows utilizing tool functions, orchestration logic, and structured outputs. β’ Design and implement RAG pipelines that effectively manage both structured and unstructured data, prioritizing quality retrieval and regulatory adherence. β’ Establish database lookup strategies using AI that comprise semantic searches, metadata filters, and corporate rules. β’ Connect agents to backend services through APIs and microservices, ensuring secure and reliable endpoints with auditing features. β’ Collaborate closely with data and platform teams to facilitate scalable and regulated access to data, considering aspects like caching, access controls, and performance logging. β’ Evaluate and suggest agent and RAG toolsets, executing implementations in production-grade architectures. β’ Set up observability measures that encompass tracing, evaluation frameworks, and drift monitoring for enhancing quality and performance. β’ Implement safety measures against prompt injection, output validation, and handling of personal identifiable information in line with responsible AI standards. β’ Define quality thresholds and fallback mechanisms to ensure agents operate safely and reliably. Company: We are looking for a talented AI-focused engineer to join our remote team, dedicated to building advanced backend services and AI agents that streamline end-to-end business workflows. Our organization offers an attractive