The Core Engineering-L2-New York-Vice President-Software Engineering (AI)

Location: New York, NY, United States

Salary: USD 130,000–260,000 per year

Company

hirify.global' Core Engineering organization builds and operates platforms, applications, data solutions, models, and analytics supporting risk, financial reporting, compliance, treasury, human capital management, and other critical functions.

What you will do

• Design, build, deploy, and operate cloud-native AI applications using modern software engineering practices, CI/CD, and automated testing.
• Partner with business and engineering stakeholders to identify high-impact AI opportunities and translate requirements into scalable architectures, data models, and technical specifications.
• Embed with internal business teams to map workflows, prototype agentic automation, define approval and control boundaries, and measure adoption.
• Integrate LLM APIs, retrieval-augmented generation, embeddings, vector search, structured outputs, response validation, and evaluation frameworks into production applications.
• Apply cloud, DevOps, MLOps, observability, security, lifecycle management, and resilience practices.
• Document solutions, mentor receiving teams, and transfer code, integrations, data models, and operational practices into long-term ownership.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
• 9+ years of hands-on software engineering experience building, deploying, and supporting production applications.
• Strong proficiency in Python, Java, or Go, with sound testing, data modeling, and system design skills.
• Experience translating complex business requirements into cloud-optimized architectures and scalable production solutions.
• Experience with AWS, Azure, or GCP, including serverless services, containers, managed services, automated deployment, monitoring, and cloud security.
• Experience integrating AI/ML capabilities into production applications, including RAG pipelines, embeddings, vector databases or search indexes, prompt management, evaluation datasets, and model monitoring.

Nice to have

• Experience building agentic AI systems with multi-step planning, tool and API calls, state management, permission checks, failure handling, and auditable action trails.
• Experience implementing agent observability, prompt and tool-call logging, hallucination and policy checks, human approvals, and incident handoff.
• Experience optimizing production AI systems for latency, cost, retrieval quality, caching, batching, streaming, and regression testing.

Culture & Benefits

• Work within a centralized engineering organization supporting six Core business units.
• Collaborate directly with internal business and engineering partners in a forward-deployed AI engineering model.
• Deliver measurable business impact through pilots, feedback loops, production adoption, and knowledge transfer.