AI Platform Engineering Consultant

Location: Hybrid, with work at client locations and listed hirify.global offices across the United States; regular travel to client locations required.

Annual salary range: $54,400–$205,800, depending on location, role, skills, and experience.

Company

hirify.global is a global professional services company helping organizations build digital, cloud, data, AI, and operational capabilities.

What you will do

• Work with client technology teams to understand contact-center, telephony, cloud, data, and operational constraints.
• Build AI platform infrastructure, model-serving environments, inference endpoints, deployment pipelines, containers, and infrastructure-as-code across cloud and hybrid environments.
• Run load and performance testing for real-time voice and chat workloads, tune latency, plan capacity, and optimize AI costs through routing, caching, token usage, and right-sizing.
• Build data pipelines and platform components for service data lakes, reporting, dashboards, and analytics agents.
• Set up observability, logging, alerting, SLO monitoring, incident response, and operational runbooks.
• Support production rollout, client training, handoff, reusable accelerators, mentoring, and technical communication with client stakeholders.

Requirements

• 3+ years of professional experience in platform, cloud, DevOps, site reliability, data engineering, or client-facing technical consulting, including hands-on deployment and operation of AI or LLM applications in production.
• 1+ year of experience with customer service, contact-center, or customer-experience projects or operations, including metrics such as resolution, average handle time, and CSAT.
• Hands-on experience with at least one of AWS, Azure, or Google Cloud, including containers, Kubernetes, Terraform or other infrastructure as code, and CI/CD.
• Python programming and scripting skills, plus SQL for querying data and validating pipelines.
• Experience deploying and operating AI or ML workloads, including model serving and inference, on platforms such as Amazon Bedrock, Microsoft Azure AI Foundry, Google Vertex AI, or Databricks Mosaic AI.
• Experience with observability and performance tools such as OpenTelemetry, Grafana, or Datadog, including load testing.
• Experience with modern data platforms such as Databricks, Snowflake, BigQuery, or Microsoft Fabric.
• Ability to translate technical work into business value and communicate with developers and client leaders.
• Willingness to travel regularly to client locations and authorization to work in the United States without current or future visa sponsorship.

Nice to have

• Experience with Amazon Connect, Genesys Cloud, NICE CXone, voice and telephony infrastructure, SIP, WebRTC, or real-time speech services.
• Experience with calls, chats, transcripts, workforce data, or quality data.
• Associate-level cloud or FinOps certification.
• Portfolio of real-world AI projects or deployed solutions.
• Client-facing experience in consulting, agency, or professional services.
• Bachelor’s degree in computer science, engineering, or a related field, or equivalent experience.

Culture & Benefits

• Hybrid collaboration with client teams and production-focused delivery across service AI and data engagements.
• Medical, dental, vision, life, and long-term disability coverage.
• 401(k), bonus opportunities, paid holidays, and paid time off.
• Inclusive workplace committed to equal employment opportunity and reasonable accommodation.