Overview
Hybrid
Depends on Experience
Contract - W2
Skills
Azure AI
LLm
Vector Database
Model fine tuning
RAG
pen AI
Job Details
The ideal candidate will have strong expertise in Azure-based AI/ML platforms, hands-on experience with LLMs, orchestration frameworks, and vector databases, and a passion for identifying how emerging AI capabilities can transform audit processes.
Key Responsibilities
- AI Research & Exploration
- Continuously evaluate the evolving AI/ML landscape (LLMs, multimodal AI, agentic systems, orchestration frameworks like Semantic Kernel/LangChain).
- Publish white papers, thought leadership, and research notes on applicability of new AI technologies to the Audit and Assurance domain.
- Benchmark and compare existing vs. emerging technologies to guide architectural decisions.
- Prototyping & Demos
- Design and deliver POCs, prototypes, and demo applications to validate the feasibility of new AI solutions.
- Showcase end-to-end use cases such as intelligent document review, anomaly detection, automated audit workflows, or generative AI assistants.
- Translate research outcomes into practical, demo-ready solutions that highlight business value.
- Solution Architecture & Enterprise Readiness
- Ensure all AI solutions are Azure-native/compatible and align with enterprise security, governance, and compliance requirements.
- Integrate with Azure services (Azure OpenAI, Cognitive Search, Cosmos DB, Fabric, Synapse, AKS, etc.) to deliver scalable and secure platforms.
- Define reference architectures, reusable components, and best practices for integrating AI into legacy audit systems.
- Collaboration & Thought Leadership
- Partner with audit domain experts, data engineers, and product teams to identify high-impact AI opportunities.
- Present findings, demos, and POCs to senior leadership, clients, and research forums.
- Contribute to the firm s innovation agenda by staying ahead of AI trends and shaping the strategic roadmap.
Qualifications & Skills
- Bachelor s or master s degree in computer science, Data Science, AI/ML, or related field (PhD preferred).
- 7+ years of experience in AI/ML engineering, applied research, or solution architecture.
- Hands-on expertise in:
- Azure AI ecosystem (Azure OpenAI, Cognitive Services, Synapse, Fabric, Cognitive Search, Cosmos DB, AKS).
- LLMs and orchestration frameworks (Semantic Kernel, LangChain, LangGraph).
- Vector databases (Cognitive Search vector, Pinecone, Weaviate, Qdrant, pgvector).
- Model fine-tuning, embeddings, RAG patterns, and prompt engineering.
- Strong experience designing enterprise-ready AI solutions with compliance, governance, and security in mind.
- Proven ability to develop POCs, demos, and technical presentations that resonate with both technical and business stakeholders.
- Strong communication and writing skills; ability to publish white papers and research articles.
Passion for innovation, continuous learning, and applying AI in novel ways to industry-specific challenges.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.