I
AI Engineer
Incedo Inc.
3 hours ago
Full-time
On-site
New York City, New York, United States
Role Overview
We are looking for an AI Full-Stack / Systems Engineer to build scalable backend services and platform components that power enterprise AI applications and agent-based workflows. The role focuses on LLM integrations, AI orchestration frameworks, RAG-based knowledge systems, and production-grade AI infrastructure used by multiple engineering teams. This engineer will work closely with platform, architecture, and application teams to build secure, reliable, and governed AI systems at enterprise scale. Key Responsibilities
Build backend services supporting AI agents and multi-step AI workflows Develop LLM integration layers and model service APIs Implement RAG pipelines including document ingestion, embeddings, and vector retrieval Build orchestration frameworks connecting models, tools, and enterprise APIs Implement AI safety controls, guardrails, and policy enforcement Develop observability, monitoring, and cost tracking for AI systems Integrate AI systems with enterprise platforms and internal services Required Skills
Strong backend engineering experience (Python preferred) Experience building distributed systems / microservices Hands-on experience with LLMs, RAG architectures, or AI agent frameworks Experience integrating AI APIs such as OpenAI, Anthropic, Bedrock, etc. Experience with cloud platforms (AWS preferred) Familiarity with vector databases, embeddings, and knowledge retrieval systems Experience with REST APIs, containerization (Docker), and modern backend frameworks Preferred Skills
Experience with LangChain, LlamaIndex, or agent orchestration frameworks Experience building AI platform components or internal developer platforms Exposure to AI governance, guardrails, and evaluation frameworks Experience operating systems in enterprise or regulated environments Ideal Candidate
5-10 years backend / platform engineering experience Hands-on experience building production AI systems Strong problem solving and distributed systems background Comfortable working in AWS cloud-native environments
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We are looking for an AI Full-Stack / Systems Engineer to build scalable backend services and platform components that power enterprise AI applications and agent-based workflows. The role focuses on LLM integrations, AI orchestration frameworks, RAG-based knowledge systems, and production-grade AI infrastructure used by multiple engineering teams. This engineer will work closely with platform, architecture, and application teams to build secure, reliable, and governed AI systems at enterprise scale. Key Responsibilities
Build backend services supporting AI agents and multi-step AI workflows Develop LLM integration layers and model service APIs Implement RAG pipelines including document ingestion, embeddings, and vector retrieval Build orchestration frameworks connecting models, tools, and enterprise APIs Implement AI safety controls, guardrails, and policy enforcement Develop observability, monitoring, and cost tracking for AI systems Integrate AI systems with enterprise platforms and internal services Required Skills
Strong backend engineering experience (Python preferred) Experience building distributed systems / microservices Hands-on experience with LLMs, RAG architectures, or AI agent frameworks Experience integrating AI APIs such as OpenAI, Anthropic, Bedrock, etc. Experience with cloud platforms (AWS preferred) Familiarity with vector databases, embeddings, and knowledge retrieval systems Experience with REST APIs, containerization (Docker), and modern backend frameworks Preferred Skills
Experience with LangChain, LlamaIndex, or agent orchestration frameworks Experience building AI platform components or internal developer platforms Exposure to AI governance, guardrails, and evaluation frameworks Experience operating systems in enterprise or regulated environments Ideal Candidate
5-10 years backend / platform engineering experience Hands-on experience building production AI systems Strong problem solving and distributed systems background Comfortable working in AWS cloud-native environments
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