Job Title : AI / ML Full Stack Engineer / Azure Open AI
Location : Hybrid / Onsite (Philadelphia - PA / Charlotte - NC / Fort Lauderdale - FL / Scarborough - ME)
Job Type : W2 Contract to Hire (CTH)
Position Overview :
Client is currently hiring a Full Stack AI / ML Engineer to support work at client's large AI Cybersecurity Team.
Depth & Scope :
- Using Azure AI services to deploy AI models / applications – Azure Open AI, Azure Machine Learning, Azure AI Studio
- Full Stack Engineering background
o Linux, Windows Sys Admin, Middleware, disciplines, Network Engineering, and some development
o Someone who can truly navigate the full stack
o Understands hardware to application layer
o How to wire AI engines into this environment, how to build the architecture
o Deployments in Azure
Strong Prompt Engineering, Python Development and REST API skillsUnderstanding of different GenAI LLMs, development frameworks (Langchain, Semantic Kernel), and AI ecosystem tooling (evaluation, monitoring, governance, security, vector databases)Ability to identify and design approaches for creating guardrails to mitigate GenAI security / cyber risksDeep understanding of major components of RAG applications, usage patterns, and optimizationLLM Fine-tuning approachesUnderstanding the full lifecycle of AI model development, deploymentTools for support large scale InferencingSolid understanding of machine learning algorithms, neural network architectures, and LLM model training processesKnowledge of different Agentic frameworksFamiliarity with g Azure AI services – Azure OpenAI, Azure Machine Learning, Azure AI StudioSolid understanding of machine learning algorithms, neural network architectures, and AI model training processesExperience with adversarial machine learning techniques and familiarity with common attack vectors against AI systemsFamiliarity with AI ethics and bias in AI systemsKnowledge of techniques for interpreting and explaining AI model decisionsAbility to identify and design approaches for creating guardrails to mitigate GenAI security / cyber risks & adversarial attacksKnowledge of OWASP and NIST GenAI security guidelines & policiesUnderstanding the different areas of evaluation for a RAG systemLLM model evaluation tooling (e.g. Using LLMs-as-a-judge)
