{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/rag-pipelines"},"x-facet":{"type":"skill","slug":"rag-pipelines","display":"Rag Pipelines","count":7},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fff47210-64d"},"title":"Senior Software Engineer, Applied AI (Fullstack)","description":"<p>Secure Every Identity, from AI to Human</p>\n<p>Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organisations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.</p>\n<p>This is an opportunity to do career-defining work. We&#39;re all in on this mission. If you are too, let&#39;s talk.</p>\n<p>Okta&#39;s Business Technology organisation builds secure and intelligent internal platforms that power our global workforce. Our AI &amp; Automation team is delivering next-generation tools and experiences by integrating GenAI and intelligent automation into workflows across IT, HR, Finance, Sales, Marketing and Customer Support.</p>\n<p>We focus on real-world applications: virtual agents, AI copilots, internal RAG services, and AI-augmented self-service portals , all with scale, governance, and user experience in mind.</p>\n<p><strong>The Opportunity</strong></p>\n<p>As a Senior Software Engineer, Applied AI, you&#39;ll play a key role in building user-facing and backend systems that leverage GenAI to improve internal experiences and operations. This role requires strong full-stack engineering skills, with an emphasis on both AI integration and building intuitive, performant UIs that make AI accessible and useful to our internal customers.</p>\n<p>You&#39;ll work closely with software engineers, product managers, and designers to build secure, intelligent tools for employees across Okta.</p>\n<p><strong>What You&#39;ll Do</strong></p>\n<ul>\n<li>Design and build end-to-end GenAI-powered applications, including web-based UIs, API services, and backend orchestration.</li>\n</ul>\n<ul>\n<li>Implement and integrate LLM-based experiences using frameworks like LangChain, LlamaIndex, and tools like OpenAI, Claude, or Gemini.</li>\n</ul>\n<ul>\n<li>Define, implement, and champion operational excellence standards (SLOs, observability, incident response frameworks) for all services deployed.</li>\n</ul>\n<ul>\n<li>Develop responsive, accessible, and modern frontend interfaces using frameworks like React or Vue , with a focus on 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He didn&#39;t just theorize; he built instruments, ran experiments, and shared what he learned so that others could go further.</p>\n<p>At Mercury, we&#39;re making a deliberate, company-wide bet on AI. Frontier users are already pushing boundaries,building agents, automating workflows, moving fast. But they&#39;re doing it in silos. This role exists to change that: to take those scattered experiments and turn them into shared infrastructure, shared context, and shared capability. The goal is a multiplier effect,where the most ambitious AI work inside Mercury lifts the velocity of everyone else.</p>\n<p>You&#39;ll join a team that has already started building Mercury&#39;s internal AI platform and enablement layer. Your work will be to extend, harden, and scale what&#39;s in motion, and to help partner teams adopt it.</p>\n<p>You&#39;ll build and evolve MCP servers that connect internal systems and data sources into a coherent interface for agents and engineers. 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Build playgrounds and evaluation harnesses so internal AI agents can be tested and iterated in controlled environments before hitting production.</p>\n<p>This list is illustrative. Priorities will shift as we learn; the right person will help choose the next highest-leverage work.</p>\n<p>The ideal candidate has 5+ years of backend development experience in complex, production systems,you&#39;ve built things that other engineers depended on. Is fluent across programming languages and can navigate platform engineering, infrastructure, and developer tooling without needing a map. Has hands-on experience building LLM-powered systems,RAG pipelines, agents, eval frameworks,and has shipped at least one of these to production. Understands the real tradeoffs in AI deployments: cost modeling, observability, latency, and safety,not just the exciting parts. Is high-agency and self-directed. 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The member journey is the product. But the Residential OS only delivers on that promise if the operational machinery running beneath it is intelligent, instrumented, and self-improving.</p>\n<p>Most companies say they are AI-first. At Belong, it means something specific: by the end of 2025, the majority of communications across sales, leasing, homecare, and concierge functions are AI-generated. Human Advisors and Concierges handle trust-critical moments. AI agents handle everything else: triage, scheduling, status updates, escalation routing, vendor coordination, documentation.</p>\n<p>The operations product surface is where that architecture lives or dies. As Product Owner, Operations, your job is to design, deploy, and relentlessly improve the AI-powered system that runs the homeowner and resident journey from inspection through occupancy. You are not writing requirements for a future that engineers will build someday. You are shipping agent-driven workflows today, measuring their quality and deflection rates next week, and iterating the week after.</p>\n<p>This role is for someone who understands that the frontier of operations is not better dashboards. It is autonomous systems that perform with the judgment of your best operator, at infinite scale, at the moment the member needs it.</p>\n<p>Responsibilities</p>\n<ul>\n<li><p>AI agent architecture across the operational journey. Every operational phase, from home preparation, move-in orchestration, homecare and maintenance, to Pro coordination and vendor scheduling, has a human workflow today and an AI-assisted target state. You will define that target state phase by phase: what the agent handles autonomously, what triggers human review, what escalates immediately.</p>\n</li>\n<li><p>The agent-human handoff model. The Member Journey Brief is explicit: humans are deployed at trust-critical moments. AI handles orchestration, speed, and precision behind the scenes. You are the person who defines exactly where that line sits, and who moves it systematically as agent quality improves.</p>\n</li>\n<li><p>LLM-powered communication workflows. Belong&#39;s target is 80% AI-generated communications across operational functions by Q3. You will own the product layer that makes this real for operations: the prompt architecture, context retrieval pipelines, output quality review systems, and the feedback loops that improve generation quality over time.</p>\n</li>\n<li><p>Foundation as the AI control panel. Foundation is where Belong&#39;s operational teams live. Every tool your squad ships into Foundation is either creating leverage for humans or replacing manual work with agent-driven automation. You will define the roadmap for Foundation&#39;s evolution from task management system to AI control panel: where agents surface for review, where exceptions queue for human action, where quality scores and deflection rates are visible in real time.</p>\n</li>\n<li><p>Operational instrumentation and model feedback. AI systems degrade without structured feedback. You will build the instrumentation that captures ground truth: CSAT signals, escalation rates, rework rates, SLA breach patterns, and member sentiment. You will design the feedback loops that push this signal back into model evaluation and prompt improvement.</p>\n</li>\n</ul>\n<p>The AI Stack You Will Work With</p>\n<ul>\n<li>LLM-based communication generation with context injection from CRM and operational state</li>\n<li>Agentic scheduling and coordination workflows (Homecare triage, Pro dispatch, vendor coordination)</li>\n<li>Automated escalation routing based on signal classification</li>\n<li>Quality scoring and anomaly detection on agent outputs</li>\n<li>Retrieval-augmented generation for Concierge and Homecare agent context</li>\n</ul>\n<p>What Success Looks Like</p>\n<ul>\n<li>90 days: Every operational phase has a documented AI target state with defined autonomous scope, human escalation thresholds, and instrumentation in place.</li>\n<li>6 months: AI-assisted workflows have measurably reduced manual communication volume across at least 2 operational functions with no CSAT degradation.</li>\n<li>Year 1: The majority of routine operational communications in your product surface are AI-generated. Human operators are handling exceptions, escalations, and trust-critical moments, nothing else.</li>\n</ul>\n<p>Example KPIs You Will Be Held To</p>\n<ul>\n<li>AI deflection rate vs. manual handling baseline, by operational function</li>\n<li>CSAT from homeowners and residents at each operational phase (the constraint: deflection gains cannot come at CSAT cost)</li>\n<li>SLA compliance rates for homecare and Pro services</li>\n<li>Time-to-list (inspection to live listing)</li>\n<li>Move-in readiness rate and failed move-in rate</li>\n<li>Human escalation rate as a quality signal on agent confidence calibration</li>\n</ul>\n<p>Who You Are</p>\n<ul>\n<li>AI systems thinker. You do not think about AI features. You think about AI systems: input context, output quality, fallback behavior, quality measurement, and continuous improvement loops.</li>\n<li>Operationally grounded. You have worked in environments where things break in the real world, with real vendors, real homes, real members, and you understand that an agent operating without the right context is more dangerous than no agent at all.</li>\n<li>Outcome obsessed. You hold deflection rate and CSAT simultaneously. You do not celebrate automation that degrades experience.</li>\n<li>Technically fluent. You can write a SQL query, read a vector similarity result, reason about retrieval quality, and understand the tradeoffs in a prompt engineering decision.</li>\n<li>Cross-functional driver. Operations, Homecare, Leasing, Vendor Ops, and Engineering all touch your surface. You run the rituals, translate across languages, and hold the delivery cadence.</li>\n</ul>\n<p>What You Bring</p>\n<ul>\n<li>3 to 5 years of product experience, with at least 1 to 2 years directly building or operating AI-powered products in a production environment</li>\n<li>Hands-on experience with LLM integrations, prompt engineering, RAG pipelines, or agentic workflow design</li>\n<li>Demonstrated ownership of operational tooling or service orchestration products in a marketplace, logistics, or operations-intensive environment</li>\n<li>Proficiency with data: SQL, funnel analysis, and the ability to detect when a metric is being gamed or misread</li>\n<li>Experience with AI evaluation frameworks and output quality measurement is a strong advantage</li>\n<li>Prior work in consumer real estate, hospitality, or residential services is a plus</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_8db20763-21b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Belong","sameAs":"https://www.belong.com/","logo":"https://logos.yubhub.co/belong.com.png"},"x-apply-url":"https://jobs.lever.co/belong/12878464-3397-4603-91fd-a4645ee06afe","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AI systems thinking","LLM-powered workflows","Agentic scheduling and coordination workflows","Automated escalation routing","Quality scoring and anomaly detection","Retrieval-augmented generation","SQL","Funnel analysis","Data analysis","Prompt engineering","RAG pipelines","Agentic workflow design","Operational tooling","Service orchestration","Consumer real estate","Hospitality","Residential services"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:27:01.211Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Argentina"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI systems thinking, LLM-powered workflows, Agentic scheduling and coordination workflows, Automated escalation routing, Quality scoring and anomaly detection, Retrieval-augmented generation, SQL, Funnel analysis, Data analysis, Prompt engineering, RAG pipelines, Agentic workflow design, Operational tooling, Service orchestration, Consumer real estate, Hospitality, Residential services"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ffccb977-f95"},"title":"Senior Site Reliability Engineer","description":"<p>Are you excited by the idea of building fast, reliable, and intelligent infrastructure for a product used by engineering teams around the world? We&#39;re looking for a Senior Site Reliability Engineer to join the Backstage team at Spotify. We&#39;re building the next generation of our developer platform , one that doesn&#39;t just manage software, but actively helps create and maintain it through AI-native workflows.</p>\n<p>In 2026, SRE isn&#39;t just about uptime; it&#39;s about symbiosis. As part of our growing engineering team, you&#39;ll design, build, and operate the cloud infrastructure behind our external developer portal product and our internal fleet of background coding agents. You&#39;ll collaborate closely with experienced engineers (both human and AI-assisted) while operating at real-world scale, with deep observability, strong safety boundaries, and the unique reliability challenges of agentic production systems.</p>\n<p>Backstage is more than just a platform , it&#39;s a foundational force in the developer community. Born out of Spotify&#39;s quest for better developer tooling, Backstage now powers developer portals across the globe. But we didn&#39;t stop at catalogs and templates. Today, Backstage is becoming the command center for AI-native engineering. From enterprises orchestrating large-scale migrations to fast-moving teams using AI to improve velocity and quality, our solutions are redefining what great developer experience looks like.</p>\n<p>As part of the Backstage team, you&#39;ll shape developer experience for companies large and small, for our thriving open-source community, and for Spotify itself. You&#39;ll help define how reliable, secure infrastructure enables the next wave of agentic developer tooling.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Own fleet reliability. Lead the reliability, security, and scalability strategy for Portal&#39;s SaaS infrastructure, including the runtime environments that power our platform and LLM-driven agent workflows. Define SLOs, drive capacity planning, and ensure our systems meet the demands of a rapidly growing product.</li>\n</ul>\n<ul>\n<li>Architect for the agentic era. Design and evolve infrastructure on GCP and AWS using Terraform and infrastructure-from-code patterns. Shape how we structure environments for non-deterministic AI workloads , including sandboxing, resource isolation, cost governance, and security boundaries.</li>\n</ul>\n<ul>\n<li>Drive operational excellence. Evolve our incident management, on-call, and postmortem practices. Leverage AI assistants to accelerate root cause analysis and build increasingly self-healing capabilities into our production systems.</li>\n</ul>\n<ul>\n<li>Lead fullstack reliability. Operate across a modern web stack (TypeScript, React, Python). While not frontend-heavy, you&#39;ll diagnose and resolve issues across the stack and drive reliability improvements end-to-end.</li>\n</ul>\n<ul>\n<li>Mentor and multiply. Raise the reliability IQ of the broader engineering team. Establish SRE best practices, conduct production-readiness reviews, and mentor engineers on operational thinking.</li>\n</ul>\n<ul>\n<li>Shape the roadmap. Partner with engineering and product leadership to evolve our infrastructure in step with generative AI features. 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