Sr. Lead AI Engineer (AI)

TL;DR

Sr. Lead AI Engineer (AI): Technical leadership for Service and Marketing AI capabilities, including architecture and execution for distributed backend systems and AI serving for LLMs, tools, evaluators, and retrieval. Focus on building low-latency, production-grade agentic systems with strong evaluation/quality, observability, and safety/guardrails while mentoring engineers and unblocking cross-team dependencies.

Company

hirify.global builds AI-native experiences powered by first-party data for ecommerce and beyond.

What you will do

• Define and improve engineering architecture for Service and Marketing AI, designing scalable, low-latency backend systems and APIs.
• Build and harden AI serving systems that host and orchestrate LLMs, tools, evaluators, and retrieval systems with clear contracts, SLOs, and observability.
• Evolve agentic architecture by driving the technical roadmap for AI agents, improving tool use, autonomy, and reliability.
• Set engineering standards for AI services, including evaluation, safety/guardrails, prompt/model versioning, testing, and incident response.
• Lead cross-team technical work as the primary interface between AI services and other product/platform teams.
• Mentor engineers and help shape local engineering rituals for the Palo Alto hub; measure availability, latency, cost-to-serve, agent success rates, eval scores, and adoption.

Requirements

• 8+ years of professional software engineering with a strong focus on backend and distributed systems; led complex projects end-to-end as a technical owner.
• Hands-on experience shipping generative or agentic AI applications in production, including prompt design, few-shot approaches, fine-tuning, and evaluation.
• Deep experience architecting and operating large-scale distributed systems, async pipelines, and distributed task queues (e.g., Celery, Kafka, SQS, RabbitMQ, Redis).
• Strong Python and backend framework fluency (e.g., FastAPI, Django) plus data tooling experience (e.g., Spark/Hadoop, SQLAlchemy/Alembic).
• Production-grade cloud experience with AWS and Kubernetes, including CI/CD, observability, and operational best practices.
• Designed human and automated evals for AI systems and can balance latency, cost, and response quality in real usage.

Culture & Benefits

• Hybrid role based in the Boston, MA hub (3x week).
• Responsible AI expectations (privacy, security, bias awareness, and human-in-the-loop) with accommodations as needed.
• Compensation includes base salary plus potential bonus/equity/sign-on and a comprehensive health/welfare/wellbeing benefits package based on eligibility.
• May require up to 10% travel for onboarding, partner/client work, team meetings, and industry events (coordinated in advance).