Principal AI Engineer

Location: Onsite in New York City three days per week

Salary: $180,000–$200,000 yearly USD

Company

hirify.global Inc. is hiring for an enterprise AI engineering role focused on production software and client solutions.

What you will do

• Design and build agentic systems with retrieval, structured reasoning, tool calling, and secure least-privilege action execution.
• Productionize LLM applications through retrieval pipelines, prompt synthesis, response validation, self-correction loops, and rigorous evaluation.
• Own the supporting full stack, including data pipelines, Python and SQL services, distributed compute, and orchestration.
• Engineer reliability and governance with validators, adversarial testing, policy checks, deterministic fallbacks, rollback strategies, and continuous evaluation.
• Optimize token efficiency, latency, cost, caching, model routing, batching, streaming, and parallel tool calls against defined SLOs.
• Deploy AI applications across AWS, Azure, or GCP and mentor engineers while collaborating with product owners, data scientists, and business stakeholders.

Requirements

• 8–14 years of software engineering experience with strong hands-on Python development and strong data structures, algorithms, APIs, microservices, and system design knowledge.
• Working depth in Go, Rust, Java, or C/C++ and experience operating data pipelines and production-grade distributed systems.
• At least 2 years of hands-on LLM engineering, including multiple agentic systems designed and taken to production.
• Experience with agent frameworks, MCP servers, tool-calling interfaces, RAG fundamentals, vector databases, guardrails, and reliability patterns.
• Hands-on AWS experience with ECS/EKS, Lambda, S3, DynamoDB, Redshift, and Step Functions, plus CI/CD and Terraform or CloudFormation.
• Ability to work onsite in New York City three days per week and communicate directly with client stakeholders in ambiguous environments.

Nice to have

• Experience with Amazon Bedrock, Vertex AI, or Azure AI while maintaining fluency in underlying AI fundamentals.
• Experience with Azure or GCP equivalents.

Culture & Benefits

• Ownership-oriented engineering culture with an emphasis on urgency, analytical problem-solving, and high-quality reusable components.
• Direct collaboration with product owners, data scientists, business subject-matter experts, and client stakeholders.
• Technical leadership and mentoring responsibilities across AI and software engineering practices.