Senior AI Production Engineer (Remote)

TalentAlly; New York (NY); Remote; USD 150,000 - 210,000; Full time

Job summary

TalentAlly is seeking a mid‑to‑senior full‑stack AI engineer to design, train, and deploy production AI systems end‑to‑end. You will work across the full AI stack—machine learning, deep learning, and generative AI—building observable, safe, and scalable solutions.

You’ll deploy on Azure with Git-based workflows, CI/CD, and containerized services. Strong Python, ML libraries, and experience with LLMs and RAG are required for this remote role.

Qualifications

• Bachelor’s or Master’s degree or equivalent practical experience.
• 4+ years in software engineering with ML/AI production work.
• Strong Python and ML library proficiency.

Responsibilities

• Design, train, evaluate, and ship ML/DL models.
• Build LLM-powered applications with major providers.
• Develop RAG systems, embeddings, vectors, and re-ranking.
• Create agentic workflows with tooling orchestration.
• Apply prompt engineering and evaluation methods.
• Build data/feature pipelines on Azure, ensure quality and reproducibility.
• Operationalize models with MLOps: versioning, retraining, drift detection.
• Maintain CI/CD pipelines for AI services.
• Deploy services on Azure with containers (Docker) and Kubernetes.
• Ensure observability, safety, and compliance in production.

Skills

Python

PyTorch

TensorFlow

scikit-learn

pandas

NumPy

Git

CI/CD

Azure

Docker

Kubernetes

LLM-based apps

Prompt engineering

Education

Bachelor’s or Master’s in CS/ML

Tools

Claude Code

Cursor

Azure OpenAI

GitHub Actions

Azure DevOps

Docker

Terraform/Bicep

pgvector

Job description

TalentAlly is seeking a mid‑to‑senior full‑stack AI engineer to design, train, and deploy production AI systems end‑to‑end. You will work across the full AI stack—machine learning, deep learning, and generative AI—building observable, safe, and scalable solutions.

You’ll deploy on Azure with Git-based workflows, CI/CD, and containerized services. Strong Python, ML libraries, and experience with LLMs and RAG are required for this remote role.