Artificial Intelligence Engineer

Job Type – Contract to HireLocation – Remote – but MUST be near Miramar, FL or Dallas, TXRequirements - GC holder or USC requiredThe Senior AI Engineer reports directly to the VP of AI and is responsible for leading and advancing enterprise-wide AI initiatives. This role leads the design, development, and deployment of end-to-end AI systems and intelligent agents that drive automation, decision-making, and business value at enterprise scale. Operating as a senior independent contributor, this role works comfortably across multiple concurrent initiatives — spanning AI architecture, model integration, and developer tooling — while collaborating with Data Scientists, Data Engineers, product owners, and business stakeholders to translate complex requirements into production-ready AI solutions. With deep expertise in enterprise AI architecture and hands-on proficiency with AI coding assistants such as Claude Code and Codex, this individual accelerates delivery velocity while maintaining rigorous engineering standards across the full AI development lifecycle.Duties and Responsibilities:Design, build, and deploy end-to-end AI systems — from data ingestion and model development through inference, monitoring, and continuous improvementArchitect and develop AI agents and multi-agent frameworks capable of reasoning, planning, and executing complex workflows autonomouslyBuild cohesive AI solutions through the orchestration and integration of Models, LLMs, agentic services, expert systems, and knowledge graphsLeverage AI coding assistants (Claude Code, GitHub Codex, and similar tools) to accelerate development, automate repetitive engineering tasks, and improve code quality across the teamBuild and maintain scalable AI pipelines on Databricks and AWS, integrating with existing data infrastructure and enterprise systemsDefine and implement enterprise AI architecture standards, patterns, and best practices across the organizationEvaluate and integrate large language models (LLMs), foundation models, and generative AI capabilities into business applicationsCollaborate with Data Scientists to operationalize ML models and move experiments from prototype to productionPartner with cross-functional teams across multiple simultaneous initiatives to scope, design, and deliver AI-powered solutionsEstablish model monitoring, evaluation, and feedback loops to ensure AI systems remain accurate, safe, and performant in productionStay current with the rapidly evolving AI landscape and proactively recommend new tools, frameworks, and approaches that improve outcomesMentor junior engineers and contribute to a culture of technical excellence, experimentation, and continuous learningPrepare technical documentation, architecture diagrams, and executive presentations to communicate AI strategy and resultsRequirements:Bachelor's degree in Computer Science, Engineering, Mathematics, or related field; master's degree preferred7+ years of experience in software or data engineering with at least 5 years focused on AI/ML systems developmentDemonstrated end-to-end experience building and deploying AI systems and AI agents in production environmentsProficiency with AI coding assistants such as Claude Code, GitHub Codex, or equivalent tools as part of an active development workflowHands-on experience with Databricks for model training, feature engineering, and pipeline orchestrationSolid experience with AWS cloud services (SageMaker, Lambda, S3, EC2, Step Functions, or equivalent) for AI/ML workloadsStrong Python skills including SparkSQL, MLlib, PyTorch, spaCy, and NLTK for NLP and ML model developmentExperience integrating AI systems via REST APIs, GraphQL, and OAuth for secure, scalable enterprise connectivityProven ability to operate as a senior independent contributor across multiple initiatives simultaneously without close supervisionExperience designing enterprise AI architecture including APIs, orchestration layers, vector databases, and model serving infrastructurePreferred Skills:Experience building multi-agent systems and knowledge graphs using frameworks such as LangGraph, AutoGen, CrewAI, or the Anthropic Agent SDKFamiliarity with front-end and visualization technologies including React/Native, Figma, Dash or similar, and Bootstrap for building AI-powered user interfaces and data applicationsFamiliarity with prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques for production LLM applicationsExperience with MLOps practices including CI/CD for AI systems, model versioning, and automated evaluation pipelinesKnowledge of vector databases such as Pinecone, Weaviate, or pgvector for semantic search and retrieval applicationsFamiliarity with data governance, AI safety, and responsible AI principles in enterprise settingsExperience with Databricks Unity Catalog, Delta Lake, and MLflow for end-to-end model lifecycle managementStrong communication and stakeholder management skills — able to present technical AI concepts clearly to both engineering teams and business executivesAbility to evaluate build vs. buy tradeoffs for AI tooling and make architecture recommendations with long-term maintainability in mindExperience contributing to AI strategy, roadmap planning, and organizational AI adoption initiativesAttention to detail with a strong bias toward shipping reliable, well-documented, production-grade systems