Enterprise AI & LLM Systems Engineer

Remote
Remote
Full-Time
Posted Oct 18, 2026

Job details

Category: AI
Sector: Technology
Experience level: Senior-Level
Salary range: $145k - $180k
Application deadline: Rolling Admissions

Job description & requirements

Job description

Engineer enterprise GenAI agents, vector search pipelines, and private inference deployments.

Key requirements

Required skills: Python, PyTorch, RAG Pipelines, Vector Databases (Milvus/Pinecone), LLMOps, FastAPI.

Role details

What you will work on

Design enterprise Retrieval-Augmented Generation (RAG) pipelines over multi-terabyte internal knowledge bases.
Deploy fine-tuned open-source LLMs on private Kubernetes GPU clusters with TensorRT-LLM and vLLM.
Enforce strict hallucination guardrails, PII data masking, and role-based vector retrieval.

Required skills

Python
PyTorch
RAG Pipelines
Vector Databases (Milvus/Pinecone)
LLMOps
FastAPI

Responsibilities

Own the evaluation and rollout of LLM-backed features from prototype to production.
Monitor inference cost, latency, and quality metrics and tune deployments accordingly.
Partner with security to review data handling and access controls for every pipeline.

Direct Application

Apply for Enterprise AI & LLM Systems Engineer

Submit your candidate credentials below. Our hiring partners review submissions within 48 business hours.

Interested in this role?

Review the details, then send your CV and a short note with the application form.

About the company

Technology

Enterprise platforms, cloud infrastructure and applied AI.

View company profile

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Neurasal

Enterprise AI & LLM Systems Engineer

Remote
Remote
Full-Time
Posted Oct 18, 2026

Job details

Category: AI
Sector: Technology
Experience level: Senior-Level
Salary range: $145k - $180k
Application deadline: Rolling Admissions

Job description & requirements

Job description

Engineer enterprise GenAI agents, vector search pipelines, and private inference deployments.

Key requirements

Required skills: Python, PyTorch, RAG Pipelines, Vector Databases (Milvus/Pinecone), LLMOps, FastAPI.

Role details

What you will work on

Design enterprise Retrieval-Augmented Generation (RAG) pipelines over multi-terabyte internal knowledge bases.
Deploy fine-tuned open-source LLMs on private Kubernetes GPU clusters with TensorRT-LLM and vLLM.
Enforce strict hallucination guardrails, PII data masking, and role-based vector retrieval.

Required skills

Python
PyTorch
RAG Pipelines
Vector Databases (Milvus/Pinecone)
LLMOps
FastAPI

Responsibilities

Own the evaluation and rollout of LLM-backed features from prototype to production.
Monitor inference cost, latency, and quality metrics and tune deployments accordingly.
Partner with security to review data handling and access controls for every pipeline.

Direct Application

Apply for Enterprise AI & LLM Systems Engineer

Submit your candidate credentials below. Our hiring partners review submissions within 48 business hours.

Interested in this role?

Review the details, then send your CV and a short note with the application form.

About the company

Technology

Enterprise platforms, cloud infrastructure and applied AI.

View company profile

Other Open Roles

Enterprise Security & Compliance Analyst

Remote · Full-Time

Core Platform Backend Engineer

Remote · Full-Time

Cloud Infrastructure & SRE Engineer

Remote · Full-Time

Enterprise Solutions Architect

Hybrid · Full-Time