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Applied AI Engineer

Zensark IncNew York, NY🇺🇸United StatesPosted 2 Sept 2026

Why This Role Stands Out

This hybrid role at Zensark Inc. offers an exciting opportunity to innovate with cutting-edge Generative AI and Agentic AI technologies, significantly impacting product development. You'll thrive here if you have extensive Python experience and a proven track record with LLM APIs, contributing to a dynamic tech environment. Apply now to leverage your expertise and grow your career in applied AI!

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
New York, NY, United States
Posted
5 days ago
Generative AILLMPostgreSQLPython

Job Description

Position: Applied AI Engineer
Location: New York, NY – 1633 Broadway (Locals only from NY&NJ) 
Work Model: Hybrid – 3 days onsite/week
Duration: 12+ Months
Candidate Requirement: Local NYC candidates only
Experience: 7+ Years
Interview: Zoom + 90-minute onsite interview

Key Requirements

  • Strong hands-on Python development.
  • Strong Generative AI and Agentic AI experience.
  • Production experience with OpenAI, Claude SDK, or comparable LLM APIs.
  • Strong understanding of prompt engineering, grounding, context management, prompt testing, and output validation.
  • Strong hands-on RAG experience.
  • Experience with vector databases and/or PostgreSQL.
  • Experience building complex AI applications integrating APIs, databases, cloud services, and enterprise data.
  • Experience with AI coding tools such as Claude Code, Amp, Codex, or similar.
  • Strong understanding of embeddings and retrieval architectures.
  • Experience building and operating production-grade GenAI systems at scale.
  • AI/LLM evaluation experience is highly desirable.
  • Financial Services / Fixed Income experience is a strong plus.
  • Excellent written and verbal communication skills.

Important

Please do not submit profiles based only on GenAI/RAG keywords. Candidates must have genuine hands-on production experience and should be able to explain their architecture, RAG implementation, scale, evaluation approach, challenges, and individual contribution during the interview.

 

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