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Agent Based Modeling Jobs in New York (NOW HIRING)

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Build and maintain APIs and microservices for AI and agent-based applications. * Integrate AI ... Handle edge cases, failures, hallucinations, and unintended model outputs. * Implement appropriate ...

New

Showing results 41-60

Agent Based Modeling information

What is an agent based modeling?

An Agent-Based Modeling (ABM) job involves developing and implementing simulations that model the interactions of autonomous agents within a system. These roles are common in fields like economics, epidemiology, traffic modeling, and artificial intelligence. Professionals in this role use programming and mathematical models to analyze complex systems and predict emergent behaviors. Key skills typically include coding (Python, NetLogo, or AnyLogic), data analysis, and knowledge of computational modeling techniques.

What are some typical challenges faced in an agent based modeling position?

A common challenge in Agent Based Modeling is accurately representing complex, real-world systems with diverse and dynamic agents while balancing computational resources and model simplicity. Professionals in this role often need to validate and calibrate their models with limited or imperfect data, requiring both technical skill and creativity. Additionally, effectively communicating modeling results to non-technical stakeholders and integrating feedback into iterations is a key part of the job. Overcoming these challenges provides rewarding opportunities to contribute to innovative solutions across areas like finance, healthcare, logistics, or social sciences.

What are the key skills and qualifications needed to thrive in the agent based modeling position, and why are they important?

To thrive in an Agent Based Modeling role, a strong background in computational modeling, mathematics, and systems analysis is typically required, often supported by a degree in computer science, engineering, or a related field. Proficiency with simulation tools such as NetLogo, AnyLogic, or Repast, as well as programming languages like Python or Java, is highly valuable. Effective communication, critical thinking, and strong collaboration skills help professionals explain complex models to stakeholders and work within multidisciplinary teams. These qualities are crucial for accurately simulating real-world systems, delivering actionable insights, and driving informed decision-making in various industries.

What are the most commonly searched types of Agent Based Modeling jobs in New York?

The most popular types of Agent Based Modeling jobs in New York are:

What are popular job titles related to Agent Based Modeling jobs in New York?

For Agent Based Modeling jobs in New York, the most frequently searched job titles are:

What cities in New York are hiring for Agent Based Modeling jobs?

Cities in New York with the most Agent Based Modeling job openings:

Infographic showing various Agent Based Modeling job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 16% Part Time, and 6% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

AI/LLM Engineer

2T Consulting

Staten Island, NY • On-site

Full-time

Posted 2 days ago

New


Job description

We are seeking a highly skilled AI/LLM Engineer to design, develop, and deploy intelligent agent-based systems capable of reasoning, planning, and executing tasks autonomously. The ideal candidate will have strong Python engineering skills, hands-on experience with modern AI agent frameworks, and experience integrating LLM solutions with enterprise data platforms.

Roles and Responsibilities

Agent & AI System Development

  • Design and develop AI agent systems using LangChain, LangGraph, or similar frameworks.
  • Build intelligent components capable of reasoning, planning, and autonomous task execution.
  • Implement agentic patterns such as ReAct (Reasoning + Acting).
  • Develop multi-step LLM workflows and agent orchestration.

LLM Capabilities & Enhancements

  • Implement memory, tool usage, context management, and MCP capabilities.
  • Develop solutions using tool calling, chaining, and workflow orchestration.
  • Work with prompt engineering teams to improve LLM response quality and performance.
  • Optimize LLM applications for scalability, reliability, and cost.

Software Engineering

  • Develop high-quality, scalable, and maintainable Python applications, including asynchronous programming.
  • Build and maintain APIs and microservices for AI and agent-based applications.
  • Integrate AI services with enterprise applications and backend systems.
  • Develop production-ready solutions with appropriate testing, monitoring, and error handling.

Guardrails & Responsible AI

  • Design and implement guardrails and safety mechanisms for LLM-powered applications.
  • Handle edge cases, failures, hallucinations, and unintended model outputs.
  • Implement appropriate validation, security, and access controls for AI systems.

Data & Platform Integration

  • Integrate AI solutions with modern data platforms, including Snowflake and Databricks.
  • Work with Lakehouse architectures and enterprise data pipelines.
  • Enable LLM applications to securely access and leverage enterprise data.
  • Collaborate with Data Engineering, ML Engineering, and Cloud teams on scalable AI architectures.
Required Technical Skills
  • 5+ years of experience in software engineering, AI/ML engineering, or a related field.
  • Strong hands-on experience with Python and asynchronous programming.
  • Experience building LLM and generative AI applications.
  • Strong experience with LangChain, LangGraph, or similar agent frameworks.
  • Understanding of AI agents, ReAct, tool calling, memory, context management, and MCP.
  • Experience developing REST APIs and microservices.
  • Experience integrating AI applications with Snowflake, Databricks, or Lakehouse platforms.
  • Strong understanding of scalable, production-ready software architectures.
  • Knowledge of LLM guardrails, responsible AI, security, and failure handling.
  • Strong problem-solving, communication, and collaboration skills.
Preferred Skills
  • Experience with multi-agent systems and agent orchestration.
  • Knowledge of vector databases and RAG architectures.
  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Familiarity with LLM observability, evaluation, and performance optimization.
  • Experience deploying AI applications in enterprise production environments.