Azure Gen AI Architect

Role: Azure GenAI Architect

Location: Mount Laurel, NJ

Experience: 15+ Years

Technical Skills

Expertise in ELK Stack: Proficient in Elasticsearch, Logstash, and Kibana.
Visualization Experience: Strong experience with Kibana visualization tools (Lens, Maps, Graph).
Data Modeling and Knowledge of JSON and REST APIs: Familiarity with JSON data format and RESTful API principles is crucial for interacting with Elasticsearch.
Querying: Proficiency in Kibana Query Language (KQL) and Elasticsearch aggregations.
Monitoring/Observability: Background in creating operational dashboards for log analysis or metric tracking.
Familiarity with Elasticsearch Ecosystem: Knowledge of related tools like Kibana, Logstash, and Beats enhances the engineer's ability to deliver complete solutions.
Basic Programming Skills: Proficiency in programming languages such as Python, Java, or Go is beneficial for automation and customization tasks.

Primary: AI/GenAI- open source/commercial LLM; Python; Azure; Databricks

Secondary: Datawarehouse

Job Description:

Develop; fine tune; and optimize LLMs; multimodal models; and generative AI pipelines for various business use cases.

Build scalable AI/ML systems; including data pipelines; model training workflows; and inference services.

Evaluate and integrate open source and commercial LLMs (e.g.; GPT; Llama; Claude; Mistral).

Implement RAG (Retrieval-Augmented Generation); vector databases; embeddings; and prompt engineering strategies.

Collaborate with product; engineering; and domain teams to translate business problems into AI powered solutions.

Conduct experiments; benchmarking; and A/B testing to validate model performance.

Deploy models using cloud platforms (Azure) and MLOps tools.

Monitor; troubleshoot; and continuously improve AI systems in production.

Strong programming skills in Python and experience with ML frameworks

Hands on experience with LLMs; transformers; and generative AI architectures.

Experience with prompt engineering; fine tuning; and model evaluation.

Familiarity with MLOps tools (MLflow; Kubeflow; Docker; Kubernetes).

Experience with agentic workflows; LangChain; LlamaIndex; or similar frameworks.

Knowledge of multimodal AI (vision + language models).

Hands-on data experience on Cloud Technologies on Azure; ADF; Synapse; Pyspark/Python

Ability to understand Design; Source to target mapping (STTM) and create specifications documents

Flexibility to operate from client office locations

Able to mentor and guide junior resources; as needed Nice to Have

Any relevant certifications

Banking experience on RISK & Regulatory OR Commercial OR Credit Cards/Retail