Agentic AI Engineer

Sharp Decisions; Jersey City (NJ); Hybrid; USD 180,000 - 210,000; Full time

Job summary

Sharp Decisions is recruiting for a senior, hands-on AI engineer to join the technology organization of a major global bank. This is a forward-looking role focused on agentic AI: designing, coding, and deploying autonomous agents built on large language models.

What sets this role apart is the problem space. The team is looking for someone who understands not just how to build an agent, but how agents behave once they interact with each other, with data, and with the institution around them.

Qualifications

• Deep understanding of AI agents: how they work, how they reason and act, and how they fail.
• Strong working knowledge of LLMs and building agents on top of them.
• Solid coding ability in Python, with PySpark and SQL for working with data at scale.
• Experience with Microsoft Azure.
• PhD in computational social science or similar interdisciplinary programs is a meaningful plus.

Responsibilities

• Design and build LLM-powered agents and multi-agent systems, from prototype through production.
• Write the code yourself: agent logic, tool use, orchestration, and the data pipelines that feed them.
• Model how agents interact within larger systems and identify where emergent behavior can create risk.
• Bring a complex-systems lens to how interconnected processes, models, and data flows affect one another.
• Work with engineering and business stakeholders to shape how agentic AI is applied responsibly across the bank.

Skills

AI agents

LLMs

Python

PySpark

SQL

Azure

Tools

Databricks

Job description

Location: Jersey City, NJ or Charlotte, NC
Contract to hire
W2 only
Hybrid on site

About the Role

Location: Jersey City, NJ or Charlotte, NC
Contract to hire
W2 only
Hybrid on site

About the Role

Sharp Decisions is recruiting for a senior, hands-on AI engineer to join the technology organization of a major global bank. This is a forward-looking role focused on agentic AI: designing, coding, and deploying autonomous agents built on large language models.

What sets this role apart is the problem space. The team is looking for someone who understands not just how to build an agent, but how agents behave once they interact with each other, with data, and with the institution around them. That means thinking about emergent risk, complex systems, and the interconnectivity of things.

What You'll Do

• Design and build LLM-powered agents and multi-agent systems, from prototype through production.
• Write the code yourself: agent logic, tool use, orchestration, and the data pipelines that feed them.
• Model how agents interact within larger systems and identify where emergent behavior can create risk.
• Bring a complex-systems lens to how interconnected processes, models, and data flows affect one another.
• Work with engineering and business stakeholders to shape how agentic AI is applied responsibly across the bank.

What You Bring

• A deep understanding of AI agents: how they work, how they reason and act, and how they fail.
• Strong working knowledge of LLMs and practical experience building agents on top of them.
• Solid coding ability in Python, with PySpark and SQL experience for working with data at scale.
• Experience with Microsoft Azure.
• A genuine grasp of complex systems, emergent behavior, and systemic or emergent risk.

Backgrounds we'd love to see: Strong candidates often come out of computational social science or similar interdisciplinary programs, where modeling agents, networks, and emergent behavior is core to the work. A PhD in one of these fields is a meaningful plus.

Technology Environment

Azure, Python, PySpark, SQL, LLMs and agent frameworks. Databricks is part of the environment but not required.

Location

Jersey City, NJ or Charlotte, NC. The team is flexible on which office and will base the role wherever the right person is.

Sharp Decisions has connected technology talent with leading financial institutions for more than 36 years.