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# AI/ML Engineer

- **Company:** TEKSYSTEMS INC.
- **Location:** Salem, OR, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $80,200.0 - $120,400.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Automation of Tests, Microsoft Azure, Code Review, Communications Protocols, Cursor (Graphical User Interface Elements), Decision Support Systems, DevOps, Django Web Framework, Graph Database, Python (Programming Language), Machine Learning, Language Modeling, Node.Js, Open Source Technology, Performance Tuning, Next.js, Software Safety, Search Technologies, Systems Integration, TypeScript, Web Application Frameworks, Reinforcement Learning, Datadog, Data Logging, Google Cloud, Chatbots, GitHub Copilot, ReactJS, Large Language Models, Express.js, Multi-Agent Systems, Prompt Engineering, Model Validation, Generative AI, Backend, Fastapi, Vue.js, Containerization, AI Platforms, AngularJS, Kubernetes, Information Technology, Deployment Automation, HuggingFace, Performance Monitor, Machine Learning Operations, Front End Software Development, Virtual Agents, GPT, Software Version Control, Dynatrace, Automation Anywhere, Docker, Programming Languages, Microservices
- **Published:** June 12, 2026
- **Apply:** https://www.juju.com/job/00000000g7sa9a

## About the Role

code reviews, testing, documentation, and knowledge sharing to ensure high-quality software delivery * Mentor junior developers and contribute to technical decision-making processes Required Qualifications Education & Experience * Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or related technical field * 5+ years of experience in full-stack development with proficiency in modern frameworks and programming languages * 3+ years of hands-on experience building AI-powered applications and autonomous agent systems Technical Expertise * Programming Languages: Proficiency in Python, TypeScript/JavaScript, with experience in Rust, Go, or Java preferred * Frontend Frameworks: React, Vue.js, Angular, Next.js, or similar modern frameworks * Backend Technologies: Node.js, FastAPI, Django, Express.js, microservices architecture * Agent Frameworks: Hands-on experience with LangChain, AutoGen, CrewAI, LangGraph, OpenAI
Assistants API, or Microsoft ADK * LLM Integration: Proven experience integrating and optimizing multiple language models (GPT, Claude, Gemini, open-source models) * AI/ML Fundamentals: Strong understanding of transformer architectures, prompt engineering, embeddings, vector databases, and RAG systems Specialized AI Knowledge * Proven experience in building autonomous agents, multi-agent systems, and agent orchestration platforms * Strong understanding of agent-based modeling, reinforcement learning, AI planning techniques, and decision-making algorithms * Experience with Model Context Protocols (MCP) and multi-model integration patterns * Knowledge of AI safety, alignment, and ethical AI deployment practices * Familiarity with vector databases (Pinecone, Weaviate, Chroma) and semantic search implementations Preferred Qualifications Advanced Technical Skills * Experience with LangFuse for AI observability, tracing, and performance monitoring *
Knowledge of AWS Strands platform or similar agent coordination systems * Familiarity with open-source LLMs deployment and fine-tuning (Hugging Face, Ollama, vLLM) * Experience with AI development tools like Cursor, GitHub Copilot, Claude Code, Gemini CLI * Understanding of retrieval-augmented generation (RAG), knowledge graphs, and semantic search DevOps & Infrastructure * Experience with MLOps tools and practices including model versioning, experiment tracking, and automated deployment * Knowledge of Kubernetes for AI workload orchestration and GPU cluster management * Familiarity with cloud AI services (AWS Bedrock, Google Vertex AI, Azure OpenAI Service) * Experience with monitoring and logging tools specifically for AI applications Industry Experience * Previous experience in AI research, autonomous systems, or intelligent automation * Understanding of conversational AI, task automation, or decision support systems * Experience with AI
governance, model evaluation, and safety testing frameworks * Extremely good with natural language processing (NLP) technologies AND Language models, prompt engineering and context Engineering

Skills

machine learning

Top Skills Details

machine learning

## Description

maintain sophisticated agentic AI solutions including autonomous agents, multi-agent systems, and AI orchestration workflows * Build intelligent agents capable of reasoning, planning, decision-making, and autonomous task execution * Implement agent communication protocols and coordination mechanisms for complex multi-agent scenarios * Design and optimize AI workflows using agent frameworks such as Google ADK, A2A, AutoGen, CrewAI, Lang Graph, LangFlow, Semantic Kernel, and OpenAI Agent SDK Technical Architecture & Integration * Architect and develop robust frontend interfaces and backend services for AI-driven platforms using modern frameworks * Integrate multiple Large Language Models (LLMs) including GPT-4, Claude, Gemini, and open-source models like Llama 3, Mistral, CodeLlama, and Vicuna * Implement and optimize AI orchestration frameworks including LangChain, LlamaIndex etc. * Design Model Context Protocol (MCP) implementations for seamless model interoperability

 * Develop custom agent frameworks and extend existing platforms like Microsoft AI Agent Development Kit (ADK) and Google AI Platform DevOps & Production Systems * Implement comprehensive AI observability and monitoring using Lang Fuse, Pheonix, Datadog or Dynatrace * Deploy and manage AI applications using containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure) * Establish CI/CD pipelines for AI model deployment, version control, and automated testing * Implement prompt engineering best practices, A/B testing frameworks for AI responses, and performance optimization * Monitor model performance, drift detection, and implement feedback loops for continuous improvement Collaboration & Quality Assurance * Collaborate with research, product, and data science teams to prototype and deploy production ready intelligent systems * Ensure scalability, reliability, security, and ethical considerations in the deployment of agentic AI systems * Participate in


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