AI Engineer

VStream Labs Inc · 1 month ago
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Applications Received
91

AI Engineer

Position Overview

VStream Labs Inc. is seeking a hands-on AI Engineer to design and deliver secure, production-ready Azure applications, APIs, microservices and AI-enabled workflows. This contract opportunity requires strong Node.js engineering, Azure cloud integration, identity, DevOps and generative-AI implementation experience.


Work Arrangement: Contract - Remote


Key Responsibilities

  • Design and integrate JVM-based services and components within the broader Azure and microservices architecture.
  • Build and integrate knowledge-graph capabilities, including entity and relationship modelling, graph-based retrieval and AI workflow enrichment.
  • Develop and support document-rendering workflows for reliable generation and transformation of business documents, including HTML and PDF outputs.
  • Build backend services and integrations using Node.js, REST APIs and microservices.
  • Deploy and operate solutions using Azure App Service, Blob Storage, Key Vault, API Management and Entra ID.
  • Implement OAuth 2.0 and OpenID Connect authentication and authorization.
  • Integrate ServiceNow, Jira, Microsoft Graph and other third-party APIs.
  • Develop AI-enabled workflows using Azure OpenAI or GitHub Models, prompt engineering and human-in-the-loop patterns.
  • Implement GitHub Actions, CI/CD pipelines, Git branching strategies and infrastructure-as-code where appropriate.
  • Apply secure engineering, testing, monitoring and production-readiness practices.
  • Strong JVM engineering experience is required; Ruby/Python-only experience does not meet this requirement.
  • Hands-on Graph DB experience, specifically Neo4j/Cypher, with proven GraphRAG implementation is required; vector RAG alone is not sufficient.
  • Hands-on experience with deterministic document rendering, such as Apache POI, PDFBox, or pptxgenjs, is required; HTML-to-PDF experience alone is not considered equivalent.
  • Azure should be the primary cloud platform; AWS-primary experience does not meet the preferred cloud requirement.
  • Experience with Akka and/or event-sourced workflow frameworks is required; Temporal experience alone is considered adjacent and does not fully meet this requirement.
  • Hands-on experience with MCP/A2A is required, including demonstrated implementation or production delivery experience.

Required Qualifications

  • Hands-on experience with the JVM ecosystem and integrating JVM-based applications or services.
  • Experience designing or implementing knowledge graphs, graph data models, graph-based retrieval or GraphRAG solutions.
  • Experience implementing production document-rendering solutions, including HTML-to-PDF or comparable document-generation pipelines.
  • Strong hands-on Node.js development experience.
  • Demonstrated REST API development and microservices design experience.
  • Hands-on Azure App Service, Blob Storage, Key Vault, API Management and Entra ID experience.
  • Experience implementing OAuth 2.0 and OpenID Connect.
  • Experience integrating ServiceNow, Jira, Microsoft Graph or comparable enterprise APIs.
  • Practical Azure OpenAI or GitHub Models experience, including prompt engineering and AI workflow integration.
  • Experience with GitHub Actions, CI/CD and Git branching strategies.
  • Strong JVM engineering experience is required; Ruby/Python-only experience does not meet this requirement.
  • Hands-on Graph DB experience, specifically Neo4j/Cypher, with proven GraphRAG implementation is required; vector RAG alone is not sufficient.
  • Hands-on experience with deterministic document rendering, such as Apache POI, PDFBox, or pptxgenjs, is required; HTML-to-PDF experience alone is not considered equivalent.
  • Azure should be the primary cloud platform; AWS-primary experience does not meet the preferred cloud requirement.
  • Experience with Akka and/or event-sourced workflow frameworks is required; Temporal experience alone is considered adjacent and does not fully meet this requirement.
  • Hands-on experience with MCP/A2A is required, including demonstrated implementation or production delivery experience.


Preferred Qualifications

  • Infrastructure-as-code experience.
  • Human-in-the-loop AI workflow design.
  • Experience delivering secure enterprise integrations in production.


What You Need to Have to Be Considered

  • 8+ years of experience in AI/ML, Data Science, or Software Engineering.
  • Strong understanding of machine learning algorithms, evaluation metrics, and model validation techniques.
  • Expertise in Agentic AI concepts, including LLMs, RAG, memory, reasoning, and prompt engineering.
  • Hands-on experience building AI solutions using OpenAI, Azure OpenAI, Anthropic, Gemini, or similar platforms.
  • Experience with Python and AI frameworks such as LangChain, LangGraph, Semantic Kernel, or LlamaIndex.
  • Proven experience evaluating AI systems, detecting hallucinations, and measuring model performance.
  • Knowledge of scalable architecture, workflow orchestration, and AI governance.
  • Experience deploying production AI solutions using MLOps/LLMOps practices.

These Will Help You Stand Out

  • Experience with multi-agent systems and advanced orchestration frameworks.
  • Cloud expertise in Azure, AWS, or Google Cloud.
  • Knowledge of AI security, compliance, and responsible AI practices.
  • Experience in regulated industries such as healthcare, insurance, or banking.
  • Relevant AI, ML, or cloud certifications.