I
Artificial Intelligence Engineer
iT Resource Solutions.net,inc
3 hours ago
Full-time
On-site
New York City, New York, United States
Agentic AI Engineer / Applied AI Engineer
Job Description
We are seeking a highly skilled **Agentic AI Engineer / Applied AI Engineer** to design, build, and deploy production-grade AI systems that go beyond conversational experiences and execute complex business workflows autonomously.
The ideal candidate will have strong experience in **LLM-based agents, Retrieval-Augmented Generation (RAG), multi-agent systems, AI automation, backend engineering, and full-stack AI product development**. This role requires the ability to translate complex user intent into reliable, scalable, and observable automated actions.
Key Responsibilities
* Design and architect **production-grade Agentic AI systems** capable of reasoning, planning, decision-making, and executing business workflows. * Build **LLM-powered agents and multi-agent workflows** using modern AI frameworks and orchestration patterns. * Develop scalable **RAG pipelines**, including document ingestion, embedding, vector search, retrieval, ranking, and contextual generation. * Integrate LLMs with enterprise systems through **backend APIs, tools, function calling, and event-driven architectures**. * Build AI applications using **OpenAI and other foundation models**, optimizing prompts, agent behavior, context management, and tool usage. * Develop reliable AI systems incorporating **memory, evaluation, observability, guardrails, security, and human-in-the-loop workflows**. * Architect and develop backend services using **Python and FastAPI**. * Build full-stack AI products and internal platforms using **React and TypeScript**. * Design event-driven and asynchronous workflows capable of supporting autonomous AI agents at scale. * Implement semantic and vector search solutions using technologies such as **Pinecone and FAISS**. * Develop AI/ML systems for areas including **fraud detection, risk scoring, anomaly detection, compliance automation, and intelligent business operations**. * Establish evaluation frameworks and monitoring systems to measure **agent accuracy, reliability, latency, cost, and production performance**. * Deploy and operate AI applications using **AWS, Docker, Kubernetes, and modern MLOps practices**. * Collaborate with product, engineering, data, and business teams to identify opportunities for **AI-driven automation and intelligent workflows**.
Required Technical Skills
* **Python** * **OpenAI / LLM APIs** * **LangChain** * **LangGraph** * **LangSmith** * **RAG architectures** * **Vector databases and semantic search** * **Pinecone / FAISS** * **FastAPI** * **REST APIs and backend development** * **React / TypeScript** * **PostgreSQL** * **Redis** * **AWS** * **Docker** * **Kubernetes** * **MLflow** * AI/ML evaluation and observability * Agent orchestration and tool/function calling * Event-driven architectures and workflow automation
Preferred Experience
* Experience building **Agentic AI platforms or autonomous AI workflows** in production. * Experience with **financial services, fraud detection, risk management, compliance, or enterprise automation**. * Strong understanding of **LLM reasoning, retrieval, memory, planning, tool use, and agent evaluation**. * Experience taking AI products from **prototype/MVP through production deployment and ongoing optimization**. * Experience building scalable, secure, and reliable **enterprise AI applications**.
Target Roles
This position is suited for professionals working in or transitioning toward:
* **Agentic AI Engineering** * **Applied AI Engineering** * **LLM Engineering** * **AI Automation Engineering** * **Forward Deployed AI Engineering** * **RAG Engineering** * **AI Platform Engineering** * **Full-Stack AI Product Engineering**
Ideal Candidate Profile
The ideal candidate combines **AI/ML expertise with strong software engineering and product development skills**. You should be comfortable moving from an AI architecture concept to a working production system, building the underlying APIs and infrastructure, integrating LLMs and retrieval systems, and implementing the monitoring and guardrails necessary to make autonomous AI reliable in real-world enterprise environments.
U.S citizenship or Green Card Required
Rate: $70.00
Job Description
We are seeking a highly skilled **Agentic AI Engineer / Applied AI Engineer** to design, build, and deploy production-grade AI systems that go beyond conversational experiences and execute complex business workflows autonomously.
The ideal candidate will have strong experience in **LLM-based agents, Retrieval-Augmented Generation (RAG), multi-agent systems, AI automation, backend engineering, and full-stack AI product development**. This role requires the ability to translate complex user intent into reliable, scalable, and observable automated actions.
Key Responsibilities
* Design and architect **production-grade Agentic AI systems** capable of reasoning, planning, decision-making, and executing business workflows. * Build **LLM-powered agents and multi-agent workflows** using modern AI frameworks and orchestration patterns. * Develop scalable **RAG pipelines**, including document ingestion, embedding, vector search, retrieval, ranking, and contextual generation. * Integrate LLMs with enterprise systems through **backend APIs, tools, function calling, and event-driven architectures**. * Build AI applications using **OpenAI and other foundation models**, optimizing prompts, agent behavior, context management, and tool usage. * Develop reliable AI systems incorporating **memory, evaluation, observability, guardrails, security, and human-in-the-loop workflows**. * Architect and develop backend services using **Python and FastAPI**. * Build full-stack AI products and internal platforms using **React and TypeScript**. * Design event-driven and asynchronous workflows capable of supporting autonomous AI agents at scale. * Implement semantic and vector search solutions using technologies such as **Pinecone and FAISS**. * Develop AI/ML systems for areas including **fraud detection, risk scoring, anomaly detection, compliance automation, and intelligent business operations**. * Establish evaluation frameworks and monitoring systems to measure **agent accuracy, reliability, latency, cost, and production performance**. * Deploy and operate AI applications using **AWS, Docker, Kubernetes, and modern MLOps practices**. * Collaborate with product, engineering, data, and business teams to identify opportunities for **AI-driven automation and intelligent workflows**.
Required Technical Skills
* **Python** * **OpenAI / LLM APIs** * **LangChain** * **LangGraph** * **LangSmith** * **RAG architectures** * **Vector databases and semantic search** * **Pinecone / FAISS** * **FastAPI** * **REST APIs and backend development** * **React / TypeScript** * **PostgreSQL** * **Redis** * **AWS** * **Docker** * **Kubernetes** * **MLflow** * AI/ML evaluation and observability * Agent orchestration and tool/function calling * Event-driven architectures and workflow automation
Preferred Experience
* Experience building **Agentic AI platforms or autonomous AI workflows** in production. * Experience with **financial services, fraud detection, risk management, compliance, or enterprise automation**. * Strong understanding of **LLM reasoning, retrieval, memory, planning, tool use, and agent evaluation**. * Experience taking AI products from **prototype/MVP through production deployment and ongoing optimization**. * Experience building scalable, secure, and reliable **enterprise AI applications**.
Target Roles
This position is suited for professionals working in or transitioning toward:
* **Agentic AI Engineering** * **Applied AI Engineering** * **LLM Engineering** * **AI Automation Engineering** * **Forward Deployed AI Engineering** * **RAG Engineering** * **AI Platform Engineering** * **Full-Stack AI Product Engineering**
Ideal Candidate Profile
The ideal candidate combines **AI/ML expertise with strong software engineering and product development skills**. You should be comfortable moving from an AI architecture concept to a working production system, building the underlying APIs and infrastructure, integrating LLMs and retrieval systems, and implementing the monitoring and guardrails necessary to make autonomous AI reliable in real-world enterprise environments.
U.S citizenship or Green Card Required
Rate: $70.00