Engineering Manager (AI & Data Infrastructure)

TL;DR

Engineering Manager (AI & Data Infrastructure): Leading the team responsible for data and inference systems powering AI agents with an accent on streaming/batch pipelines, realtime databases, and GPU model-serving platforms. Focus on driving architecture for high-throughput data systems, optimizing low-latency inference, and scaling infrastructure for enterprise environments.

Location: On-site in San Francisco or New York City

Salary: $280,000 – $430,000 + Equity

Company

hirify.global is a leading conversational AI platform empowering brands to deliver concierge customer experiences through advanced AI agents.

What you will do

• Build and lead a high-performing team of data and ML infrastructure engineers, managing hiring and performance.
• Own the technical strategy and roadmap for streaming/batch data, realtime databases, and the GPU model-serving stack.
• Remain hands-on by reviewing designs and PRs, leading architecture for complex problems, and contributing code.
• Establish reliability and cost standards, including data freshness SLOs and inference latency/availability.
• Collaborate with Research and Product teams to deliver capabilities for cloud and on-prem enterprise deployments.
• Define and implement AI-assisted engineering workflows to increase team shipping velocity and quality.

Requirements

• 2+ years of engineering management experience leading data, ML, or infrastructure teams, with a strong IC background.
• Deep technical expertise in streaming/batch processing, analytical databases, or model-serving.
• Hands-on experience operating large-scale data systems such as Kafka, ClickHouse, Snowflake, BigQuery, or Postgres.
• Proficiency with cloud platforms (AWS, GCP, or Azure), Kubernetes, and Infrastructure-as-Code.
• Track record of delivering complex, multi-quarter data or ML infrastructure initiatives.
• Must be based in San Francisco or New York City for on-site work

Nice to have

• Experience with production LLM inference infrastructure, GPU capacity planning, and multi-provider routing.
• Expertise with realtime analytics engines (ClickHouse, Pinot, Druid) and CDC pipelines at scale.
• Experience deploying ML systems into single-tenant or air-gapped enterprise environments.
• Knowledge of security and compliance frameworks such as SOC 2, PCI DSS, or FedRAMP.

Culture & Benefits

• Competitive base salary and equity package.
• Flexible "take what you need" vacation policy.
• Comprehensive medical, dental, and vision insurance for employees and families.
• Retirement planning options, including 401K.
• Parental leave and family building benefits through Carrot.
• Daily lunches and snacks provided in the office.