Member of Technical Staff

GradBay; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

GradBay is seeking a Member of Technical Staff to tackle AI agent and software engineering challenges within a fast-evolving product environment. You’ll work in small, adaptable teams with quarterly reviews and opportunities to contribute across disciplines or deepen expertise in a chosen area.

Responsibilities span product engineering, agent engineering, agent platform, infrastructure, data, and internal AI systems, with a focus on building trusted AI tools and contexts for agents to operate

Qualifications

• Experience designing, building and maintaining software systems.
• Experience building agents or applications that use AI to perform tasks.
• Experience structuring information, knowledge or state that AI systems use.
• Experience building data pipelines and integrating external information with low latency.
• Comfortable taking responsibility, collaborating across disciplines and adapting to changing priorities.

Responsibilities

• Build intuitive products and experiences powered by AI agents.
• Develop context structures and tools that help agents understand tasks and take action.
• Build systems for running, evaluating and improving agents.
• Develop the platform and infrastructure foundations supporting products and agent workloads.
• Provide agents with accurate, up-to-date external information at low latency.
• Support recruitment, sales and engineering workflows with AI-driven knowledge systems.

Skills

Software engineering

AI agent engineering

Context engineering

Agent tools and integrations

Agent execution and evaluation

Platform and infrastructure

Data engineering

Internal AI and knowledge systems

Adaptability and ownership

Job description

Member of Technical Staff – AI Agents & Software Engineering

Help build AI agents that people can trust to tackle real work.

An AI company is seeking engineers to solve challenges across product development, agent systems, data and infrastructure. This is a varied technical role where your focus will evolve as the company grows.

One project could involve designing how an agent organises and uses context. The next could involve building the data pipelines that keep its information accurate and up to date.

About the role

You’ll work in small, adaptable teams organised around specific objectives, with priorities and team structures reviewed quarterly. There’s scope to contribute across disciplines or develop deep expertise in a particular area.

Your work could span:

• Product engineering: Build intuitive products and experiences powered by AI agents.
• Agent engineering: Develop context structures and tools that help agents understand tasks and take action.
• Agent platform: Build systems for running, evaluating and improving agents.
• Platform and infrastructure: Develop the foundations supporting products and agent workloads.
• Agent data: Provide agents with accurate, up-to-date external information at low latency.
• Internal AI systems: Build agents and knowledge systems supporting recruitment, sales and engineering.

A central challenge is making users comfortable working with AI systems whose responses and behaviour can vary. You’ll help turn complex technical capabilities into tools that earn users’ confidence.

Candidate targeting criteria

We’re interested in candidates with relevant strengths across the areas below. You do not need experience in every technical discipline; both specialists and broader engineers could suit the role.

• Software engineering: Experience designing, building and maintaining software systems.
• Product development: Experience translating user needs into practical features or applications.
• AI agent engineering: Experience building agents or applications that use AI to perform tasks.
• Context engineering: Experience structuring the information, knowledge or state that AI systems use.
• Agent tools and integrations: Experience building tools, APIs or integrations that enable agents to interact with other systems.
• Agent execution and evaluation: Experience with agent execution frameworks, evaluation systems or performance testing.
• Platform and infrastructure: Experience developing infrastructure or shared platforms supporting software and AI workloads.
• Data engineering: Experience building pipelines or integrations where accuracy, freshness and latency matter.
• Internal AI and knowledge systems: Experience applying AI to business workflows or building shared knowledge infrastructure.
• Adaptability and ownership: Comfortable taking responsibility for technical problems, collaborating across disciplines and responding to changing priorities.

Help shape how AI agents are built and used, with opportunities to contribute across the engineering stack and deepen your expertise as the organisation develops.