Artificial Intelligence Engineer

Job Description

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