Sr. AI Engineer: $90/hr
Apply Now! Job Code: 100926SAIEJob 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.