11 وظيفة Data Engineer Infrastructure في New York

About the company:

We build AI hiring agents. They deploy inside the enterprise systems a company already runs, or on the Qureos platform itself for teams who would rather have the whole hiring stack in one place. Either way the agents do the work recruiting teams have always done by hand, from sourcing and screening to interviewing and shortlisting, with speed and consistency no agency or traditional ATS can match. We are a Seed-stage startup backed by Prosus Ventures and COTU Ventures, having raised $5M to accelerate the future of AI-powered hiring. Trusted by more than 1,000 enterprise and public sector organizations, we're scaling rapidly as we build the next generation of AI hiring agents. Operating in a market where every unfilled role and every slow hiring loop costs real money, we are building the future of AI-powered hiring. Our agents let companies run high-volume hiring end to end without ripping out the systems their teams already live in.

About the Role

As a Forward Deployed Engineer, you will sit at the intersection of engineering, AI, and customer impact. You will work directly with customers to understand how they hire, find the parts of that process worth handing to an agent, and then design, build, and deploy those agents either into the customer's existing enterprise stack or onto the Qureos platform, depending on how they want to run.

• You will partner closely with customers and Qureos's product and engineering teams to customise agent workflows, improve agent performance, and bring what you learn in live deployments back into the core platform.
• This role is ideal for an engineer who enjoys building production systems, working inside someone else's environment, solving ambiguous problems, and shaping how AI actually gets used in hiring.

What You'll Do

• Embed directly with customers to understand their hiring processes, the systems those processes run on, and where an agent can take over.
• Design, build, and deploy AI hiring agents that source, screen, interview, and move candidates through the funnel.
• Ship those agents into the customer's existing enterprise environment, or onto the Qureos platform for customers who want the all-in-one setup.
• Develop and maintain the infrastructure behind the agents, including APIs, integrations with enterprise ATS and HRIS systems, monitoring, and feedback loops.
• Translate customer requirements into scalable technical solutions and production-ready deployments.
• Collaborate with product and engineering teams to influence roadmap decisions based on what you see in the field.
• Identify patterns across customer deployments and turn one-off integration work into something the platform supports natively.
• Work across engineering, product, and customer teams to ensure successful adoption and long-term impact.
• Operate independently in fast-moving environments where ownership and initiative are highly valued.

What You'll Bring

• 3+ years of software engineering experience, preferably with backend, infrastructure, or systems-focused development.
• Strong programming experience in Python (experience with TypeScript/JavaScript is a plus).
• Experience working with cloud platforms such as AWS, GCP, or Azure.
• Ability to design and build reliable production systems, including inside environments you do not control.
• Strong communication skills with the ability to work with both technical and non-technical stakeholders.
• Experience working directly with customers, partners, or cross-functional teams is a plus.

Bonus: experience with AI agents, large language models (LLMs), vector databases, prompt engineering, retrieval-augmented generation (RAG), voice agents, or integrating with enterprise ATS and HRIS platforms.

Comfortable working in dynamic environments with changing priorities and high ownership.

Why Join Us

You'll be part of a team building a category-defining AI company in a market that has barely started to change. We move fast, we ship, and we work close to the customer.

If you are excited about building AI agents that do real work, deploying them into the systems enterprises actually run, and shaping how hiring gets done, we'd love to hear from you.