Job Description:
Job skills:
LLM/NLP experience,
Some APLI experience is a plus,
Langraph, Langchain, experience in a big company dealing with all of the security hurdles we jump through to get stuff done.
Tools = AI foundry, OpenAI
LLM experience specifically is using an LLM to setup a RAG pipeline to analyze text. The roadmap for this project will likely be to move as much of the bespoke RAG stuff we've built to AI foundry so it's easier to sustain.
Key Responsibilities
- Implementation of enterprise AI solutions using Large Language Models (LLMs) such as GPT, LLaMA, Mistral, and Claude to solve strategic business challenges.
- Design and develop RAG pipelines and workflows, integrating with APIs, structured/unstructured data sources, and vector embeddings for scalable enterprise applications.
- Development of enterprise NLP and text analysis solutions, including summarization, semantic search, classification, sentiment analysis, and entity extraction.
- Build generative AI solutions such as chatbots, virtual assistants, and intelligent automation tools to enhance operational efficiency and improve customer experience.
- Prototype, build, and maintain scalable API endpoints exposing AI capabilities to internal and external applications across multiple platforms
- Ensure security, compliance, and governance in AI deployments, including navigating complex enterprise security hurdles and client requirements.
- Partner with cross-functional teams, including engineering, data, and product management, to translate AI capabilities into actionable business solutions.
Required Skills & Experience
- Proven expertise with transformer-based LLMs and applied NLP solutions.
- Hands-on experience with AI orchestration frameworks such as LangChain, LangGraph, or equivalent.
- Deep understanding of RAG, vector search, embeddings, and knowledge-grounded AI systems.
- Implement fine-tuning and prompt engineering strategies.
- Strong background in Azure Cloud platforms including Azure AI Foundry, Azure Machine Learning, Cognitive Search, Azure data factory and other related services
- Proficiency in API development and integration using languages such as Python, Java, C#, JavaScript/Node.js or any other relevant language.
- Experience working with data engineering pipelines, ETL processes and big data platforms such as Databricks, Snowflake, and Spark to support AI/ML workflows.
- Proficiencies in data cleansing, exploratory data analysis, and data visualization
- Knowledge of enterprise security, compliance, and governance frameworks relevant to large-scale clients and regulated industries.
Nice-to-Have
- Experience fine-tuning LLMs for domain-specific applications.
- Exposure to chatbot frameworks and conversational AI platforms.
- Prior involvement in large-scale enterprise AI deployments with strict compliance and security requirements.
- Familiar with MLOps practices, model monitoring, and deployment pipelines for enterprise-scale applications.
- Azure AI Engineer Associate certification (or willingness to obtain)
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