Sr. AI Engineer: $90/hr
Infonet Consulting Group
Miami, FL · Posted October 10, 2026
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Where Miami, FL ranks
Where Miami, FL placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for logistics and transportation jobs202 openings · of 17
- #3Cities with the most jobs that do not need a four-year degree in the Southeast257 jobs · of 72
- #5Best cities for consumer and retail jobs283 openings · of 50
- #7Best cities for education jobs206 openings · of 47
- #7Best cities for director and executive jobs in the Southeast23% · of 87
- #7Cities hosting the most sales conferences2 conferences · of 11
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
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How AI is used in this kind of work
Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
Sr. AI Engineer: $90/hr Position Now Available At Infonet Consulting Group Sr. AI Engineer: $90/hr Apply Now! Job Code: 100926SAIE Posted: 09-Oct-26 Location: Miami, FL Position Type: Full-time, Contract - Corp-to-Corp, Contract - Independent, Contract - W2 Rate: $90/hr 1099/Corp-to-Corp or $83/hr-W2 Job Length: 12 Months Telecommuting: Not Available Travel: Some Job Description One of Infonet's premier clients has an opening for a Sr. AI Engineer. TERMS : Contract SCOPE OF WORK • Own complex AI engineering work from design through production operations, raising standards for reliability, observability, and reuse • The role emphasizes AI Engineering ownership of technical foundations—platform services, MLOps/LLMOps pipelines, deployment patterns, observability, security, and architecture guardrails—so Data Science and business teams can deliver reliable AI/ML and GenAI outcomes in production • Build and operate Azure-based AI platform components for senior independent delivery and technical ownership, using Azure ML, Databricks, MLflow, and secure service patterns to make model deployment repeatable and supportable • Develop CI/CD, model registry, evaluation, prompt/version control, retraining, and release workflows that help teams manage ML models and GenAI systems consistently from experimentation through production • Package and deploy AI services with Docker, Kubernetes, identity controls, environment configuration, and runtime standards that improve reliability, portability, and operational readiness • Implement GenAI capabilities using GPT-class models, RAG patterns, embeddings, vector databases, prompt engineering, and agent workflows where they improve reuse, quality, and enterprise scalability • Improve engineering productivity through reusable templates, code standards, GitHub/Azure DevOps automation, documentation, and tooling that help Data Science and AI teams ship with fewer manual steps • Create monitoring dashboards and alerts for latency, cost, drift, model quality, hallucination risk, token usage, and service health so production AI systems can be managed with clear operating signals • Define and apply practical guardrails for security, identity, networking, data access, model serving, and GenAI evaluation so teams can move faster without bypassing enterprise controls • Own targeted technical projects that expand senior independent delivery and technical ownership, such as reusable deployment patterns, feature pipelines, evaluation harnesses, vector search services, or cost-optimization improvements • Work closely with Data Science, IT, Security, and business teams to make platform capabilities usable in real delivery contexts while maintaining clear ownership for engineering foundations and production operations • Explain architecture decisions, delivery risks, tradeoffs, and production-readiness expectations • Make platform capabilities usable in real delivery contexts while maintaining clear ownership for engineering foundations and production operations REQUIRED SKILLS / EXPERIENCE • Practical engineering depth in Azure ML, Databricks, MLflow, CI/CD, Docker/Kubernetes, and GenAI patterns, combined with clear communication, disciplined delivery, and a strong bias toward reusable enterprise capability rather than one-off prototypes • Demonstrated experience appropriate to senior scope with production AI/ML or GenAI systems, including the ability to move beyond prototypes into reliable, monitored, and maintainable services • Hands-on experience with Azure infrastructure patterns, including Azure ML, Databricks, Azure DevOps, identity, networking, secrets, compute, and deployment environments • Experience with MLflow, Azure ML pipelines, model registries, feature pipelines, deployment approvals, monitoring, retraining, and model lifecycle management • Experience managing GenAI systems through prompt/version control, RAG evaluation, embeddings, vector database operations, token/cost monitoring, safety testing, and quality measurement • Understanding of scalable service design, asynchronous processing, failure modes, observability, and performance tuning for production AI workloads • Knowledge of enterprise authentication, authorization, data protection, secure model serving, network boundaries, and compliance-aware deployment practices • Strong Python engineering skills with modern development practices, including testing, code review, Git workflows, packaging, APIs, Docker, and CI/CD automation PREFERRED EDUCATION • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience building production-grade AI systems TRAVEL REQUIREMENT • Yes – occasionally required to walk to the dock and ascend/descend the vessel • This position may require regular domestic or international travel ** No 3rd party vendors ** Unable to sponsor H1-B visas ** Please refer to position: 100926SAIE - Sr. AI Engineer: $90/hr in the subject line of all correspondence. Please select the "Apply Now" button. We look forward to reviewing your resume and speaking with you personally. Apply Now! Quick Links • Print this position • View more positions Why Infonet? Aggressive Rates - We only add a 10-15% markup. Transparency - We'll gladly let you know how much we're being paid. No Non-Compete Language - If we do our job well, you'll always want to stay with us. No Conversion Restrictions - You're free to accept a full-time position at any time. Your Approval Required - We need your approval to submit your resume. Discretion - We'll never contact your current employer without your approval. Sr. AI Engineer: $90/hr Job Code: 100926SAIE Posted: 09-Oct-26 Location: Miami, FL Position Type: Full-time Rate: $90/hr 1099/Corp-to-Corp or $83/hr-W2 Job Length: 12 Months Telecommuting: Not Available Travel: Some Job Description One of Infonet's premier clients has an opening for a Sr. AI Engineer. TERMS : Contract SCOPE OF WORK • Own complex AI e