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# AI Engineer

- **Company:** Shrive Technologies Llc
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Big Data, Encodings, Computer Programming, Data Architecture, Information Engineering, Information Leak Prevention, Python (Programming Language), Knowledge-Based Systems, Open Source Technology, Search Technologies, SQL Databases, Data Streaming, Management of Software Versions, Web Applications, Web Application Frameworks, Data Processing, Large Language Models, Grafana, Multi-Agent Systems, Apache Spark, Generative AI, Data Lakes, Apache Kafka, Machine Learning Operations, Virtual Agents, Restful APIs, Streamlit Framework, Data Pipelines, Databricks, Microservices
- **Published:** June 9, 2026
- **Apply:** https://www.dice.com/job-detail/98ef62f1-7fa5-4be9-a322-04c04a5d6f35

## About the Role

Databricks & Lakehouse

 * Strong experience with Unity Catalog, Delta Lake, Vector Search, Databricks Workflows, and Model Serving
 * Hands-on with Lakehouse architecture patterns
LLMs & Generative AI

 * Experience with open-source LLMs (Llama, Mistral, etc.), prompting techniques, and fine-tuning approaches
 * Strong knowledge of RAG architectures and embedding strategies
AI Engineering & Frameworks

 * Expertise in LangChain, LlamaIndex, Semantic Kernel, AutoGen, or equivalent
 * Experience building agentic workflows and multi-agent systems
Programming

 * Advanced Python proficiency (APIs, web apps, orchestration, data processing)
 * Familiarity with REST APIs and microservices architecture
MLOps & Monitoring

 * Experience with MLflow, CI/CD pipelines, model lifecycle management, and observability tools
 * Knowledge of drift detection and model performance monitoring
Data Engineering Foundations

 * Experience with Spark, SQL, and large-scale data processing
 * Familiarity with streaming frameworks (Kafka, Structured Streaming)
Security & Governance

 * Expertise in AI security risks (prompt injection, jailbreaks, data leakage)
 * Experience implementing governance frameworks and compliance controls.

## Description

* Agent Development: 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.
 * LLM Integration & Optimization: Deploy, fine-tune, and serve open-source LLMs (e.g., Llama 3) using Databricks Model Serving; optimize latency, throughput, and cost.
 * RAG & Knowledge Systems: Design advanced RAG pipelines leveraging vector search, embeddings, semantic ranking, and enterprise data sources (structured + unstructured).
 * Context Engineering: Develop prompt strategies, memory frameworks, and metadata tagging to improve contextual accuracy and response quality.
 * UI & Experience Design: Build intuitive AI-driven applications using Databricks Apps (Streamlit/Dash) or modern web frameworks to enable business consumption.
 * Data Engineering for AI: Build reliable data pipelines (batch & streaming) supporting training, inference, and feature generation using Delta Lake.
 * Security & Governance: Implement enterprise-grade controls using Unity Catalog (row/column-level security, lineage, auditability) aligned with compliance standards.
 * LLM Guardrails & Responsible AI: Implement guardrails (e.g., NeMo Guardrails) for prompt injection prevention, hallucination mitigation, and safe output handling.
 * MLOps & AIOps: Establish CI/CD pipelines for AI models and agents, including versioning, monitoring, drift detection, observability, and incident response.
 * Performance & Cost Optimization: Optimize model performance, GPU/compute usage, and inference cost efficiency across environments.
 * Testing & Evaluation
 * Collaboration & Stakeholder Engagement
 * Documentation & Knowledge Transfer


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