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Associate Ai Agent Developer Jobs in New York (NOW HIRING)

OneStream

Associate AI Engineer

Manhattan, NY

Associate AI Engineer Location :  Hybrid, United States Employment Type : Full-Time Benefits Offered : Vision, Medical, Life, Dental, 401K Gross Annual Base Salary : USD 87,000 - 116,000 ...

eClercx

Senior AI Developer

Manhattan, NY · On-site

$125K - $140K/yr

Senior AI Developer Location: New York, United States Type: Full-time Department: Technology Job ... Build and orchestrate multi-agent pipelines -including supervisor agents, collaborative agent ...

eClerx

Senior AI Developer

Manhattan, NY · On-site

$125K - $140K/yr

Senior AI Developer Location: New York, United States Type: Full-time Department: Technology Job ... Build and orchestrate multi-agent pipelines -including supervisor agents, collaborative agent ...

SS&C

Director, AI Platform Engineering

New York, NY · On-site

Champion developer experience: APIs, SDKs, documentation, self-service tooling * Ensure AI agent platform security, compliance, and audit requirements What You Will Bring: * 10+ years in software ...

eClerx LLC

Senior AI Developer

Manhattan, NY · On-site

$125 - $140/hr

We are seeking a Senior AI Developer to support one of our premier clients--a leading global ... The ideal candidate will have hands‑on experience developing scalable multi-agent AI systems ...

Hello Patient

AI Agent Product Manager

New York, NY · On-site

$160K - $200K/yr

Do hands-on prompt engineering using AI tools to build the components that make agents work ... Continuously improve agent performance using structured evals, live call review, and direct ...

SysMind Tech

Azure DevOps Engineer - AI Foundry

Manhattan, NY · On-site

$58 - $79.50/hr

Monitor, debug, and optimize AI agent performance, reliability, and cost * Ensure security ... Experience with Azure DevOps (Repos, Pipelines, Boards, CI/CD) * Intermediate experience in Python ...

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All JobsAssociate Ai Agent Developer JobsAssociate Ai Agent Developer Jobs in New York

Associate Ai Agent Developer information

What is the difference between Associate Ai Agent Developer vs Machine Learning Engineer?

AspectAssociate Ai Agent DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related field; some certificationsBachelor's or Master's in CS, Data Science, or related; advanced certifications
Work EnvironmentTech companies, AI startups, R&D labsTech firms, AI companies, research institutions
Employer & Industry UsageDevelops AI agents, chatbots, virtual assistantsDesigns ML models, algorithms, data pipelines
Common Search & ComparisonOften compared for entry-level AI rolesMore advanced, research-focused roles

The Associate Ai Agent Developer typically focuses on building and maintaining AI agents like chatbots and virtual assistants, often at an entry to mid-level. In contrast, a Machine Learning Engineer develops complex ML models and algorithms, usually requiring more advanced skills and experience. Both roles are vital in AI development but differ in scope, complexity, and specialization.

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The most popular types of Ai Agent Developer jobs in New York are:

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Forward Deployed Engineer (Generative AI)

Tiger Analytics Inc.

New York, NY • Remote

Full-time

Re-posted 9 days ago

Job description

Tiger Analytics is looking for experienced Forward Deployed Engineer (Generative AI) with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Role Overview

The Forward Deployed Engineer (FDE) drives the on-site deployment, integration, and scaling of our enterprise Generative AI solutions. This role embeds directly within customer engineering teams to operationalize Large Language Models (LLMs) and retrieval systems across multi-cloud environments (AWS, Azure, GCP). You will bridge the gap between AI research and production-grade cloud infrastructure.

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

Agentic Design & Implementation
● Develop intelligent agents using Vertex AI Agent Builder to automate complex
business workflows.
● Leverage the Agent Developer Kit (ADK) to build and manage multi-agent systems
that collaborate to solve end-to-end business challenges.
● Implement tools like MCP (Model Context Protocol) Toolbox to securely connect
agents to enterprise databases like BigQuery and Spanner.


AI on Data Strategy
● Utilize Vertex AI for model training, tuning, and deployment, ensuring seamless
integration with BigQuery for feature engineering.
● Build and optimize streaming data pipelines (e.g., via Dataflow) to execute
real-time inference using RunInference API or Vertex AI endpoints.
● Ground AI models in live business context using vector engines within BigQuery or
AlloyDB to eliminate "AI amnesia".


Operational Excellence (Soft Skills)
● Active Participation: Show up promptly for all internal and client-facing meetings.
● Transparent Communication: Provide regular, structured status updates to team
members and stakeholders regarding project milestones and technical blockers.
● Proactive Collaboration: Demonstrate the ability to ask for help when facing
technical hurdles and contribute to a collaborative troubleshooting environment.
● Consultative Approach: Navigate corporate environments to translate high-level
business goals into robust technical architectures.
Technical Qualifications
● Vertex AI Mastery: Proven experience with Model Garden, Vertex AI Pipelines, and
model evaluation.
● Data Proficiency: Advanced knowledge of SQL for BigQuery, Python for ML
engineering, and data preprocessing techniques (scaling, encoding, imputation).
● Cloud Infrastructure: Hands-on experience with Google Cloud Storage and Vertex
AI endpoints.
● Emerging Tech: Familiarity with stateful real-time processing and the latest
innovations in agentic architectures.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.