AI Engineer

Hotwire Communications; Fort Lauderdale (FL); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

401K Retirement Plan with Company Match

Paid Vacation, Sick Time, and Additional Holidays

Hotwire Service Discounts

Job summary

Hotwire Communications is seeking an AI Engineer in Fort Lauderdale, Florida, to design and build the core AI platform supporting its business units. This greenfield role offers high ownership, working closely with the Director of AI Implementation.

Responsibilities include building reliable AI pipelines, deploying models, and ensuring compliance with data security standards. Candidates should have strong Python skills and experience with production-grade LLM applications.

The position includes benefits like a 401K plan and paid vacation.

Qualifications

• 2-4 years building and operating production LLM applications.
• 4 years of software engineering experience.
• Expert-level Python programmer.
• Deep understanding of API design and distributed system fundamentals.
• Hands-on experience with CI/CD pipelines and containerization.

Responsibilities

• Design and build the core AI platform for reliable pipelines.
• Own the model deployment layer and LLM endpoints configuration.
• Implement a model abstraction layer to avoid vendor lock-in.
• Build internal AI SDKs for future engineers.
• Participate in Steering Committee reviews and translate risks.
• Build operational safety infrastructure around AI services.

Skills

Building production LLM applications

Software engineering

Python programming

API design

Microservices patterns

CI/CD pipelines

Containerization (Docker)

Cloud-native deployment

Job description

As an AI Engineer, you will be the technical engine behind every AI implementation the company runs, setting up the models, building the safety and reliability infrastructure, and establishing the engineering standards that every future AI project will inherit.

This is a greenfield role with high ownership. You will be designing and building the foundational AI platform that Hotwire's business units depend on. You'll partner closely with the Director of AI Implementation and AI Champions embedded in each business unit, translating validated workflow proposals into production-grade AI solutions.

Duties / Responsibilities

• Design and build the core AI platform that connects Hotwire's business applications, data sources, and AI models into reliable, production-grade pipelines
• Own the model deployment layer, configure, version, and maintain LLM endpoints across Azure OpenAI and/or AWS Bedrock with environment isolation (dev / staging / prod)
• Implement a model abstraction layer (e.g., LiteLLM) to ensure portability across model providers and avoid hard vendor lock-in
• Build and maintain an internal AI SDK / shared libraries so that future engineers and CoE projects can bootstrap quickly without reinventing plumbing
• Own infrastructure-as-code and CI/CD pipelines for AI services Other duties as required or assigned.
• Actively participate in Steering Committee reviews, translating technical risk and feasibility into language business leaders understand
• Build and enforce input/output security controls for every AI-facing endpoint:
• PII detection and redaction before data reaches external model APIs
• Prompt injection detection, pattern-based and embedding-based classifiers
• Content policy filtering and output moderation for customer-facing AI surfaces
• Role-based access control to AI capabilities across business units
• Partner with IT Security and Compliance to ensure every AI deployment meets Hotwire's data residency, encryption, and access audit requirements
• Maintain a centralized secrets management approach for API keys, model credentials, and third-party integration tokens
• Implement an LLM evaluation framework that every CoE project must pass before production promotion
• LLM-as-judge pipelines for automated output quality scoring
• Regression test suits that protect against model drift when providers update underlying models
• Semantic similarity and coherence metrics for RAG-based applications
• Golden dataset management and versioning for reproducible evals
• Own the eval harness integration into CI/CD, no model change ships without passing eval thresholds
• Track and report quality metrics to the Director and Steering Committee as part of the AI implementation lifecycle
• Build operational safety infrastructure around AI services:
• Rate limiting and token-budget enforcement per business unit and use case
• Circuit breakers to prevent downstream cascades when model APIs degrade
• Iteration caps and wall-clock timeouts on agentic workflows
• Async queue management and retry logic for high-volume pipelines
• Configure private endpoints and VNet integration for model APIs to keep data off public internet paths
• Implement cost allocation and spend controls so that per-department AI usage is visible and accountable
• Set up comprehensive tracing and monitoring across all AI services using tools such as LangSmith, LangFuse, or equivalent
• Build dashboards that surface latency, error rates, token consumption, quality scores, and cost per workflow, visible to both engineering and business stakeholders
• Establish alerting thresholds and on-call runbooks for AI service degradation
• Maintain audit logs of all model inputs and outputs for compliance review
• Serve as the technical reviewer for AI workflow proposals coming from business unit AI Champions before they reach the Steering Committee
• Write engineering standards, integration patterns, and runbooks that AI Champions and future engineers can follow
• Contribute to vendor evaluations, help assess new AI tooling, model releases, and platform options
• Other duties as required or assigned by supervisor.

Minimum Qualifications

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required.

• 2-4 years building and operating production LLM applications, not prototypes, not demos, production systems with real users and real SLAs
• 4 years of software engineering experience with a strong bias toward system design and production-grade architecture
• Expert‑level Python, you write clean, tested, maintainable Python, not just scripts
• Deep understanding of API design, microservices patterns, async programming, and distributed system fundamentals
• Hands‑on experience with CI/CD pipelines, containerization (Docker), and cloud‑native deployment
• Strong debugging instincts, you can trace a failure from a user‑facing symptom down to a model API edge case
• Experience deploying and managing LLMs on enterprise cloud platforms: Azure OpenAI Service or AWS Bedrock

Benefits

• 401K Retirement Plan with Company Match
• Paid Vacation, Sick Time, and Additional Holidays (including your Birthday!)
• Hotwire Service Discounts – for employees who live on a property serviced by Hotwire. Discounted service offerings are provided for high‑speed internet, video service, phone, and security service

Hotwire provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.