{"schemaVersion":"jobsearcher.job.v1","id":"3229780c8511d48d8e54d4aa","url":"https://jobsearcher.com/jobs/3229780c8511d48d8e54d4aa","canonicalUrl":"https://jobsearcher.com/jobs/3229780c8511d48d8e54d4aa","title":"Technical Architect - MLE","description":"While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.\n\nIf working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!\nAbout Quantiphi:\nQuantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations.\nSince our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology’s sake.\nHeadquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.\nWe’ve been recognized with:\n17x Google Cloud Partner of the Year awards in the last 8 years.\n3x AWS AI/ML award wins.\n3x NVIDIA Partner of the Year titles.\n2x Snowflake Partner of the Year awards.\nWe have also garnered top analyst recognitions from Gartner, ISG, and Everest Group.\nWe offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators.\nWe have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023.\nBe part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation.\nYour next big opportunity starts here!\nFor more details, visit: Website or LinkedIn Page.\nRole: Technical Architect Machine Learning Engineer - Agentic AI & Multi-Agent Systems\nExperience Level: 8-12 years\nLocation: US / Canada\nJob Summary:\nWe are seeking an experienced Senior Machine Learning Engineer to architect, build, and deploy production-grade agentic AI systems and multi-agent workflows from the ground up. The ideal candidate will have deep expertise in designing autonomous AI systems that can collaborate, reason, and execute complex tasks with minimal human intervention. You will be responsible for creating scalable, robust agentic workflows using cutting-edge frameworks like CrewAI/Langraph, while ensuring enterprise-grade deployment on major cloud platforms.\nRoles & Responsibilities:\nAgentic System Architecture & Development:\nArchitect & Build Agentic Systems: Design and develop end-to-end multi-agent systems from scratch. You will create the foundational agent harnesses, define communication protocols, and build orchestration layers using frameworks like CrewAI, Langgraph, and AutoGen. Architectural decisions to ensure:\nHierarchical and collaborative multi-agent structures with well-defined agent roles, responsibilities, and communication protocols\nDynamic task decomposition, sophisticated tool integration, planning mechanisms (ReAct), and self-correction loops\nDevelop state management systems and memory mechanisms for persistent agent interactions\nEngineer Advanced Agent Capabilities: Develop custom agent-tools and define specialized agent-skills that empower agents to perform complex, domain-specific tasks.\nPioneer Context Engineering: Implement advanced context engineering and memory systems to ensure agents maintain state, learn from interactions, and make informed decisions in dynamic environments.\nDeploy Production-Grade Solutions: Own the deployment, scaling, and maintenance of robust, low-latency agentic systems on major cloud platforms (GCP, AWS, or Azure). You will implement best-in-class MLOps practices for monitoring, continuous integration/continuous deployment (CI/CD), and system reliability.\nIntegrate and Optimize LLMs: Integrate LLMs to serve as the core reasoning engines for autonomous agents. You will apply advanced techniques like RAG and PEFT to optimize performance.\nTool Development & RAG Integration:\nCreate and maintain comprehensive tool libraries for agents including API integrations, database queries, and external service connections\nDesign and implement RAG systems using vector databases (Pinecone, Weaviate, ChromaDB)\nDevelop custom tools and plugins that enable agents to interact with various enterprise systems and APIs\nEnsure tool reliability, error handling, and seamless integration within agentic workflows\nObservability, Monitoring & Evaluation:\nImplement comprehensive monitoring and tracing systems for agent behavior, performance, cost optimization, and latency analysis\nDesign novel evaluation frameworks to assess multi-step agentic task success, reliability, and accuracy\nUtilize advanced observability tools (LangSmith, Arize AI, or custom solutions) to trace agent decision making processes\nEstablish metrics and KPIs for measuring agentic system performance in production environments\nRequired Skills & Qualifications:\nExperience:\n6-8 years of hands on experience in machine learning and AI engineering with proven track record of taking ML systems to production\nDemonstrated expertise in building multi-agent systems and agentic workflows, preferably with Langraph/CrewAI\nTechnical Skills - Must Have:\nProgramming & ML: Expert-level Python proficiency with ML frameworks (TensorFlow, PyTorch, Transformers). Experience with FastAPI, async programming, and microservices architecture\nData & Vector Systems: Hands-on experience with vector databases (Pinecone, Weaviate, ChromaDB) and building scalable RAG systems\nMonitoring & Observability: Experience with LLM application monitoring tools (LangSmith, Weights & Biases, custom telemetry solutions)\nProven ability to architect and implement complex AI systems from scratch in production environments\nCloud Platform Expertise: Production-level experience with at least one major cloud platform (AWS, GCP, or Azure), including:\nCompute services (EC2, GCE, Azure VMs)\nServerless functions (Lambda, Cloud Functions, Azure Functions)\nContainer orchestration (EKS, GKE, AKS)\nManaged AI/ML services (SageMaker, Vertex AI, Azure ML)\nProduction & DevOps: Strong skills in Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and containerization (Docker, Kubernetes)\nTechnical Skills - Good to have:\nExperience with prompt engineering techniques, fine-tuning SLMs (PEFT, SFT, RLHF), and model optimization\nKnowledge of distributed systems, message queues, and event-driven architectures for agent coordination\nFamiliarity with SDLC best practices, version control (Git), and agile development methodologies\nExperience with tool-calling agents, multi-step workflows, and stateful orchestration (e.g. graphs, planners, routers).\nHands-on evals for agents: trajectory / tool-use checks, golden traces, LLM-as-judge with fixed rubrics, regression suites.\nOnline evals, drift thinking, and clear quality gates before or after deploy (thresholds, alerts, rollback criteria).\nSafety and abuse: prompt injection via tools, untrusted retrieval, PII handling in prompts and logs, allowlists and guardrails.\nCost and latency discipline: budgets per run, timeouts, caps on turns and tool calls.\nModel lifecycle: routing / gateway patterns, version pinning, fallbacks, and which model for which step.\nMemory and state: what is persisted, retention, redaction, and what must never be stored\nSoft Skills:\nExceptional problem-solving and analytical thinking with ability to tackle complex, ambiguous challenges\nStrong communication skills to explain complex agentic concepts to both technical and non-technical stakeholders\nProven ability to work independently and drive large-scale projects to completion with minimal supervision\nLeadership mindset with experience mentoring team members and driving technical excellence\nIf you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!","company":"Quantiphi","rawCompany":"quantiphi","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-04T22:08:12.198Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Technical Architect - MLE","description":"While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.\n\nIf working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!\nAbout Quantiphi:\nQuantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations.\nSince our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology’s sake.\nHeadquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.\nWe’ve been recognized with:\n17x Google Cloud Partner of the Year awards in the last 8 years.\n3x AWS AI/ML award wins.\n3x NVIDIA Partner of the Year titles.\n2x Snowflake Partner of the Year awards.\nWe have also garnered top analyst recognitions from Gartner, ISG, and Everest Group.\nWe offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators.\nWe have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023.\nBe part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation.\nYour next big opportunity starts here!\nFor more details, visit: Website or LinkedIn Page.\nRole: Technical Architect Machine Learning Engineer - Agentic AI & Multi-Agent Systems\nExperience Level: 8-12 years\nLocation: US / Canada\nJob Summary:\nWe are seeking an experienced Senior Machine Learning Engineer to architect, build, and deploy production-grade agentic AI systems and multi-agent workflows from the ground up. The ideal candidate will have deep expertise in designing autonomous AI systems that can collaborate, reason, and execute complex tasks with minimal human intervention. You will be responsible for creating scalable, robust agentic workflows using cutting-edge frameworks like CrewAI/Langraph, while ensuring enterprise-grade deployment on major cloud platforms.\nRoles & Responsibilities:\nAgentic System Architecture & Development:\nArchitect & Build Agentic Systems: Design and develop end-to-end multi-agent systems from scratch. You will create the foundational agent harnesses, define communication protocols, and build orchestration layers using frameworks like CrewAI, Langgraph, and AutoGen. Architectural decisions to ensure:\nHierarchical and collaborative multi-agent structures with well-defined agent roles, responsibilities, and communication protocols\nDynamic task decomposition, sophisticated tool integration, planning mechanisms (ReAct), and self-correction loops\nDevelop state management systems and memory mechanisms for persistent agent interactions\nEngineer Advanced Agent Capabilities: Develop custom agent-tools and define specialized agent-skills that empower agents to perform complex, domain-specific tasks.\nPioneer Context Engineering: Implement advanced context engineering and memory systems to ensure agents maintain state, learn from interactions, and make informed decisions in dynamic environments.\nDeploy Production-Grade Solutions: Own the deployment, scaling, and maintenance of robust, low-latency agentic systems on major cloud platforms (GCP, AWS, or Azure). You will implement best-in-class MLOps practices for monitoring, continuous integration/continuous deployment (CI/CD), and system reliability.\nIntegrate and Optimize LLMs: Integrate LLMs to serve as the core reasoning engines for autonomous agents. You will apply advanced techniques like RAG and PEFT to optimize performance.\nTool Development & RAG Integration:\nCreate and maintain comprehensive tool libraries for agents including API integrations, database queries, and external service connections\nDesign and implement RAG systems using vector databases (Pinecone, Weaviate, ChromaDB)\nDevelop custom tools and plugins that enable agents to interact with various enterprise systems and APIs\nEnsure tool reliability, error handling, and seamless integration within agentic workflows\nObservability, Monitoring & Evaluation:\nImplement comprehensive monitoring and tracing systems for agent behavior, performance, cost optimization, and latency analysis\nDesign novel evaluation frameworks to assess multi-step agentic task success, reliability, and accuracy\nUtilize advanced observability tools (LangSmith, Arize AI, or custom solutions) to trace agent decision making processes\nEstablish metrics and KPIs for measuring agentic system performance in production environments\nRequired Skills & Qualifications:\nExperience:\n6-8 years of hands on experience in machine learning and AI engineering with proven track record of taking ML systems to production\nDemonstrated expertise in building multi-agent systems and agentic workflows, preferably with Langraph/CrewAI\nTechnical Skills - Must Have:\nProgramming & ML: Expert-level Python proficiency with ML frameworks (TensorFlow, PyTorch, Transformers). Experience with FastAPI, async programming, and microservices architecture\nData & Vector Systems: Hands-on experience with vector databases (Pinecone, Weaviate, ChromaDB) and building scalable RAG systems\nMonitoring & Observability: Experience with LLM application monitoring tools (LangSmith, Weights & Biases, custom telemetry solutions)\nProven ability to architect and implement complex AI systems from scratch in production environments\nCloud Platform Expertise: Production-level experience with at least one major cloud platform (AWS, GCP, or Azure), including:\nCompute services (EC2, GCE, Azure VMs)\nServerless functions (Lambda, Cloud Functions, Azure Functions)\nContainer orchestration (EKS, GKE, AKS)\nManaged AI/ML services (SageMaker, Vertex AI, Azure ML)\nProduction & DevOps: Strong skills in Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and containerization (Docker, Kubernetes)\nTechnical Skills - Good to have:\nExperience with prompt engineering techniques, fine-tuning SLMs (PEFT, SFT, RLHF), and model optimization\nKnowledge of distributed systems, message queues, and event-driven architectures for agent coordination\nFamiliarity with SDLC best practices, version control (Git), and agile development methodologies\nExperience with tool-calling agents, multi-step workflows, and stateful orchestration (e.g. graphs, planners, routers).\nHands-on evals for agents: trajectory / tool-use checks, golden traces, LLM-as-judge with fixed rubrics, regression suites.\nOnline evals, drift thinking, and clear quality gates before or after deploy (thresholds, alerts, rollback criteria).\nSafety and abuse: prompt injection via tools, untrusted retrieval, PII handling in prompts and logs, allowlists and guardrails.\nCost and latency discipline: budgets per run, timeouts, caps on turns and tool calls.\nModel lifecycle: routing / gateway patterns, version pinning, fallbacks, and which model for which step.\nMemory and state: what is persisted, retention, redaction, and what must never be stored\nSoft Skills:\nExceptional problem-solving and analytical thinking with ability to tackle complex, ambiguous challenges\nStrong communication skills to explain complex agentic concepts to both technical and non-technical stakeholders\nProven ability to work independently and drive large-scale projects to completion with minimal supervision\nLeadership mindset with experience mentoring team members and driving technical excellence\nIf you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!","datePosted":"2026-08-04T22:08:12.198Z","dateModified":"2026-08-04T22:08:12.198Z","hiringOrganization":{"@type":"Organization","name":"Quantiphi","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"3229780c8511d48d8e54d4aa"},"url":"https://jobsearcher.com/jobs/3229780c8511d48d8e54d4aa"}}