Principal Software Engineer, Full-Stack AI

Location: NYC, NY; on-site

Salary: $200,000–$250,000 USD per year

Company

hirify.global is a seed-stage, AI-native startup building an enterprise platform for IT Service and Configuration Management using AI, graph-based architecture, and product-focused design.

What you will do

• Own the technical vision for the platform’s intelligence layer across data ingestion, embeddings, retrieval, graph reasoning, agents, and real-time inference.
• Architect and ship production LLM, predictive-model, and agent workflows, including RAG, hybrid search, automated enrichment, anomaly explanation, topology discovery, change impact analysis, and natural-language querying.
• Build scalable backend and data systems for high-throughput inference, embedding generation, vector search, graph traversal, and event-driven workloads.
• Collaborate across the stack on APIs and user-facing AI experiences that provide explanations, confidence signals, provenance, and feedback loops.
• Establish practices for model selection, evaluation, fine-tuning, prompt and schema design, guardrails, observability, and continuous monitoring.
• Mentor senior engineers, lead architecture reviews, influence engineering standards, and partner with product, leadership, infrastructure, and DevOps teams.

Requirements

• 10+ years of professional software engineering experience, including technical leadership in complex, high-scale systems.
• Proven experience architecting and shipping distributed systems with AI, automation, or intelligent decision-making components.
• Hands-on experience with LLMs, embeddings, vector databases, RAG pipelines, agent frameworks, or model integration patterns.
• Strong system design skills across APIs, data modeling, event-driven architectures, caching, storage, and performance optimization.
• Proficiency in at least one of Go, Rust, Python, Java, or C++ and comfort working across backend and user-facing or API-layer design.
• Experience mentoring senior engineers and applying modern AI-assisted development and DevOps practices.

Nice to have

• Experience operationalizing ML or LLM workloads in production at scale.
• Background in microservices, event-driven systems, real-time data pipelines, or high-throughput and low-latency systems.
• Exposure to frontend frameworks or strong product intuition around AI user experience.
• Open-source contributions or technical leadership in distributed systems or AI tooling.

Culture & Benefits

• Opportunity to architect foundational systems for an AI-first enterprise platform.
• Ownership of critical systems intended to scale to millions of users.
• Culture focused on craftsmanship, autonomy, technical excellence, and ownership.
• Competitive compensation, equity, and a comprehensive benefits package.