Senior AI Platform Engineer (Applied AI / LLM Ops)

iFIT's vision is to create the world's most holistic health and fitness platform — integrating physical fitness, mental health, nutrition, and recovery into a seamless, personalized experience. To accelerate that vision, we're building an AI-driven operating model that powers smarter innovation, greater efficiency, and intelligent decision-making across the organization.

We're looking for a Senior AI Platform Engineer — the first dedicated AI platform engineering role within Infrastructure — to lead the deployment, integration, and operationalization of large language models (LLMs) across iFIT. This is a hands-on role focused on building scalable AI-powered tools, embedding LLM capabilities into business workflows, and laying the foundation for enterprise-wide AI adoption.

You'll serve as the bridge between emerging AI capabilities and real-world business impact — enabling teams across IT, Product, and Operations to leverage AI safely and effectively. This is a greenfield opportunity with high ownership and autonomy, backed by executive visibility and support, with direct impact on operational efficiency, cost optimization, and product innovation. Beyond AI platform work, you'll also support broader platform and systems administration responsibilities, helping maintain and improve the infrastructure and automation that underpins our internal services.

Role Commitments

• Deploy, integrate, and operationalize LLM platforms (e.g., Claude) across internal systems and business workflows
• Design and build AI-powered tools, automation, and reusable services that drive measurable impact across teams
• Develop prompt frameworks, guardrails, and evaluation methodologies to ensure reliable, responsible AI use
• Establish observability, cost controls, and governance practices that support scalable, secure AI operations

Essential Duties & Responsibilities

AI Platform Engineering & Integration

• Build and maintain integrations with LLM APIs (e.g., Anthropic Claude, OpenAI)
• Develop backend services and APIs that support AI-powered applications
• Design reusable AI components for use across multiple teams
• Enable rapid prototyping and scaling of AI use cases organization-wide

Automation & Internal Tooling

• Develop AI-driven automation to reduce manual processes and operational overhead
• Build internal tools that enhance productivity, decision-making, and workflow efficiency
• Translate business needs into practical, AI-enabled solutions in partnership with stakeholders

Observability, Cost & Performance

• Implement monitoring, logging, and evaluation frameworks for AI systems
• Track usage, performance, and cost to ensure efficient, scalable operations
• Optimize prompt design and system architecture for performance and cost efficiency

Security, Governance & Responsible AI

• Implement guardrails that ensure safe and compliant use of AI technologies
• Collaborate with security and compliance teams to establish policies and controls
• Ensure proper handling of sensitive data within AI workflows

Systems Administration & Platform Operations

• Support the administration, maintenance, and optimization of core systems across on-prem and cloud environments
• Assist with server, application, and platform configuration, patching, and upgrades
• Contribute to infrastructure automation, scripting, and systems reliability initiatives
• Partner with infrastructure and cloud teams on troubleshooting and root cause analysis
• Help standardize operational processes, documentation, and tooling across the systems function
• Support identity, access, connectivity, and platform service integrations as needed

Education & Experience

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
• 4–8 years in software, backend, platform, or systems engineering
• Hands-on experience with LLM APIs (e.g., Anthropic, OpenAI) in production or real-world applications
• Strong proficiency in Python and/or Node.js
• Experience with cloud platforms (AWS preferred)
• Background in building internal tools, automation, or system integrations
• Experience supporting enterprise systems, infrastructure platforms, or systems administration

Preferred Qualifications

• Experience deploying AI-powered applications in production environments
• Familiarity with prompt engineering, evaluation techniques, and LLM limitations
• Experience with microservices architecture and API design
• Understanding of observability tools and practices (logging, tracing, metrics)
• Awareness of security and governance considerations for AI systems
• Comfortable working in fast-paced, cross-functional environments
• Familiarity with hybrid infrastructure (cloud and on-prem), Linux and/or Windows server environments
• Exposure to infrastructure as code, configuration management, and platform operations practices

DISCLAIMER

Compensation may vary based on the job level, your geographic work location, position incentive plan, and exemption status.
Although we currently may consider hiring in the states listed below, not all positions are available in all locations, and work in a particular state is not guaranteed. Current list of states where iFIT may consider hiring: AK, AL, AR, AZ, CA, CO, CT, FL, GA, ID, IL, IN, KS, KY, LA, MA, MD, MI, MN, MO, MS, NC, NH, NJ, NV, NY, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VA, WA, WI, WY.

Subject to applicable state laws, your employment at iFIT is "at-will". At-will employment means that you and the company each have the right to terminate the employment relationship at any time for any cause or for no cause at all.