AI Engineer

🔥 0 minutes ago

🔔 Pennsylvania – Remote

🔔 Pennsylvania – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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Arctiq

WebsiteLinkedInAll Job Openings

201 - 500 employees

🏢 Enterprise

☁️ SaaS

🔐 Security

Enterprise • SaaS • Security

Arctiq is a company that specializes in providing transformative infrastructure, security, and platform engineering solutions. They focus on enterprise security, modern infrastructure, and platform engineering, helping businesses architect practical and efficient solutions using world-class technologies. Arctiq offers managed security services, cloud security, and modern infrastructure solutions such as wireless networking and hybrid cloud infrastructure. They work with various sectors including healthcare, education, government, and more to enhance connectivity and bolster security using innovative technologies. Their services cover comprehensive infrastructure and security needs, from video surveillance in schools to smart city initiatives and cloud-native solutions for industries like oil & gas.

📋 Description

• Design, develop, deploy, and maintain Agentic AI solutions that automate business processes and complex workflows. • Build autonomous and semi-autonomous AI agents capable of reasoning, planning, tool usage, retrieval, memory management, and multi-step task execution. • Develop and deploy multi-agent systems that collaborate to accomplish business objectives. • Integrate Large Language Models (LLMs) from providers such as OpenAI, Anthropic, Google, Azure OpenAI, and open-source alternatives. • Build Retrieval-Augmented Generation (RAG) solutions leveraging vector databases and enterprise knowledge sources. • Design and implement agent orchestration frameworks using technologies such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, LlamaIndex, or similar platforms. • Develop APIs, microservices, and backend services that support AI-driven applications and workflows. • Integrate AI agents with enterprise systems including CRM, ERP, ticketing platforms, collaboration tools, databases, and third-party SaaS applications. • Implement robust observability, monitoring, evaluation, logging, guardrails, and governance frameworks for AI solutions. • Collaborate with business stakeholders to identify automation opportunities and determine where AI agents can deliver measurable value. • Evaluate emerging AI technologies and recommend practical approaches for implementation. • Perform hands-on development using Agile and Scrum methodologies. • Continuously optimize deployed AI systems for performance, reliability, cost efficiency, and user adoption. • Troubleshoot production AI applications and rapidly resolve operational issues. • Serve as a technical advisor on AI automation strategy, architecture, and implementation best practices.

🎯 Requirements

• 5+ years of software engineering experience with modern application development. • 1+ years of hands-on experience building and deploying Generative AI or Agentic AI solutions in production environments. • Demonstrated experience designing, developing, and deploying AI agents that interact with APIs, databases, enterprise systems, and external tools. • Proven experience building autonomous workflows using agent orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, LlamaIndex, or equivalent technologies. • Strong Python development experience and familiarity with AI application development ecosystems. • Experience integrating commercial and open-source LLMs into production applications. • Strong understanding of prompt engineering, agent design patterns, tool calling, memory management, context management, and AI workflow orchestration. • Experience implementing Retrieval-Augmented Generation (RAG) architectures and vector database solutions. • Experience working with cloud platforms such as Azure, AWS, or GCP. • Experience with Docker, containerized deployments, CI/CD pipelines, and modern DevOps practices. • Ability to interpret SDK documentation and rapidly implement integrations with new platforms and services. • Excellent problem-solving skills with the ability to decompose complex business challenges into scalable AI-driven solutions. • Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences. • Experience deploying AI solutions on Azure OpenAI, AWS Bedrock, Vertex AI, or similar enterprise AI platforms. • Experience with MCP (Model Context Protocol) implementations and AI tool ecosystems. • Bachelor's degree in Computer Science, Software Engineering, MIS, or related field.

🏖️ Benefits

• Flexible work arrangements • Professional development