[Remote] AI Engineer

Note: The job is a remote job and is open to candidates in USA. Eliassen Group is seeking an AI-focused engineer to build backend services and AI agents that execute end-to-end business workflows. The role involves designing and deploying retrieval-augmented generation systems for AI-driven lookups across enterprise data and integrating agents with secure, scalable services.

Responsibilities

• Build AI agents that plan and execute business workflows with multi-step actions, including understanding requests, retrieving context, taking actions, verifying results, and logging outcomes
• Translate ambiguous business problems into repeatable agent workflows with tool and function calling, orchestration logic, and structured outputs
• Design and implement RAG pipelines across structured and unstructured sources, optimizing retrieval quality and grounding
• Implement retrieval strategies that support AI-driven database lookups using semantic search, metadata filters, and business rules
• Integrate agents into backend services via APIs and microservices, delivering reliable endpoints and orchestration layers with auditability and operational controls
• Partner with data and platform teams to ensure scalable and governed data access patterns, including caching, latency constraints, access controls, and logging
• Assess and recommend agent and RAG frameworks and deploy solutions in production-ready architectures
• Implement observability with tracing, evaluation harnesses, and drift monitoring to improve solution quality and cost and performance
• Add guardrails for prompt injection defenses, output validation, and PII handling to align with responsible AI expectations
• Establish quality gates and fallback behaviors so agents fail safely and predictably

Skills

• Hands-on experience building agentic AI solutions, including LLM tool and function calling, multi-step workflows, and orchestration patterns
• Strong data experience across structured and unstructured sources, including data modeling intuition and data readiness assessment, and collaboration with analytics and data engineering teams
• Proven experience implementing RAG in production or near-production environments, including ingestion, chunking or indexing, retrieval, reranking, and grounding
• Backend engineering fundamentals including APIs, service design, reliability patterns, and integration with enterprise systems
• Proficiency in Python and or another backend language such as Java, Go, or TypeScript, with strong software engineering practices including testing, code review, and CI or CD

Benefits

• Medical, Dental, and Vision benefits
• 401k with company matching
• Life insurance

Company Overview

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