Job Description
We are looking for Senior AI Engineer•Remote / Telecommute for our client in
Camden, NJ Job Title:
Senior AI Engineer•Remote / Telecommute Job Location:
Camden, NJ Job Type:
Contract Job Overview:
Pay Range:
$55/hr•$60/hr Requirement/Must Have:
Expertise in LangChain, LlamaIndex, Semantic Kernel, AutoGen, or equivalent. Strong experience with Unity Catalog, Delta Lake, Vector Search, Databricks Workflows, and Model Serving. Hands-on with Lakehouse architecture patterns. Experience with open-source LLMs (Llama, Mistral, etc.), prompting techniques, and fine-tuning approaches. Strong knowledge of RAG architectures and embedding strategies. Expertise in LangChain, LlamaIndex, Semantic Kernel, AutoGen, or equivalent. Experience building agentic workflows and multi-agent systems. Advanced Python proficiency (APIs, web apps, orchestration, data processing). Familiarity with REST APIs and microservices architecture. Experience with MLflow, CI/CD pipelines, model lifecycle management, and observability tools. Knowledge of drift detection and model performance monitoring. Experience with Spark, SQL, and large-scale data processing. Familiarity with streaming frameworks (Kafka, Structured Streaming). Expertise in AI security risks (prompt injection, jailbreaks, data leakage). Experience implementing governance frameworks and compliance controls. Responsibilities:
Build and orchestrate autonomous AI agents with multi-step reasoning, tool usage, and workflow chaining using frameworks like LangChain, CrewAI, AutoGen, Semantic Kernel, or LlamaIndex. Deploy, fine-tune, and serve open-source LLMs (e.g., Llama 3) using Databricks Model Serving; optimize latency, throughput, and cost. Design advanced RAG pipelines leveraging vector search, embeddings, semantic ranking, and enterprise data sources (structured + unstructured). Develop prompt strategies, memory frameworks, and metadata tagging to improve contextual accuracy and response quality. Build intuitive AI-driven applications using Databricks Apps (Streamlit/Dash) or modern web frameworks to enable business consumption. Build reliable data pipelines (batch & streaming) supporting training, inference, and feature generation using Delta Lake. Implement enterprise-grade controls using Unity Catalog (row/column-level security, lineage, auditability) aligned with compliance standards. Implement guardrails (e.g., NeMo Guardrails) for prompt injection prevention, hallucination mitigation, and safe output handling. Establish CI/CD pipelines for AI models and agents, including versioning, monitoring, drift detection, observability, and incident response. Optimize model performance, GPU/compute usage, and inference cost efficiency across environments. Testing & Evaluation. Collaboration & Stakeholder Engagement. Documentation & Knowledge Transfer.
