Observability Closed 📅 2 Weeks ago 💰 $50k 🇺🇸 United States 💻 Software Development 🟣 Senior Job Description Sr AI Engineer (Observability) Function: Engineering Reports to: Director, Software Engineering Location: Remote
United States Position Summary OnBoard is a board intelligence platform trusted by over 6,000 organizations to simplify governance, and we are building AI-powered product experiences across RAG pipelines, semantic search, summarization, and emerging agentic workflows. We are looking for a Senior AI Engineer to help make those experiences reliable, measurable, cost-effective, and safe in production. This is a hands-on engineering role for someone who wants to build AI systems, not just observe them. You will partner with product engineering teams to design and improve AI features, instrument them deeply, and — critically — define how we know those features actually work. You will build the evaluation pipelines and datasets that tell us whether an AI experience is good enough to ship, analyze real-world behavior, and turn production signals into product and architecture improvements. You will help define how OnBoard ships AI: how we test prompts and retrieval quality, detect regressions, monitor cost and latency, evaluate user-facing quality, and safely evolve models, prompts, datasets, and providers over time. The right person is a strong software engineer with practical LLM application experience and a genuine quality mindset. You care not only that an AI feature works in a demo, but that it performs consistently for customers, degrades gracefully, provides traceable results, and improves through feedback loops. And you have real opinions about what makes an evaluation trustworthy — not just that one exists, but whether it measures the right thing. What You’ll Do Build and improve AI-powered product systems
Posting details
Remote
Yes
Employment type
—
Workplace type
Remote
Source
remotefirstjobs
First seen
8/30/2026, 2:10:28 PM
Last seen
8/30/2026, 2:10:28 PM
Partner with product engineers to design, build, and improve AI features using LLMs, RAG, semantic search, and agentic workflows
Contribute directly to production codebases in Python, C#/.NET, or related technologies
Improve prompt, retrieval, context assembly, ranking, grounding, and response-generation patterns
Help teams make practical architecture tradeoffs across quality, latency, cost, privacy, and maintainability
Support model and provider evaluations, migrations, fallback strategies, and rollout plans Make AI quality measurable — define what “good enough” means This is a defining pillar of the role, not an afterthought. It is not enough to have an evaluation; you will be responsible for whether our evaluations are adequate.
Design and implement evaluation pipelines for LLM-powered features, and build scoring methodologies from first principles rather than reaching for the nearest metric
Build and maintain versioned golden datasets covering real-world use cases, edge cases, failure modes, and customer-critical workflows
Implement LLM-as-judge, heuristic, human-feedback, and task-specific quality scoring approaches
Establish the criteria that determine whether an existing evaluation is sufficient for a given feature and risk profile — and identify gaps before they become production issues
Establish prompt and retrieval regression testing as part of the development lifecycle
Define quality gates and thresholds that help teams know when an AI feature is ready to ship Own observability, reliability, and cost signals
Instrument LLM interactions, RAG pipelines, tool calls, and agent workflows using observability platforms (OnBoard currently uses Arize; comparable tools include Langfuse, LangSmith, W&B, and OpenTelemetry-based stacks)
Track latency, token usage, cost, retrieval quality, groundedness, failure modes, safety signals, and user feedback
Build dashboards and alerts that surface meaningful product and engineering signals, not just raw telemetry
Analyze production traces to identify quality issues, cost spikes, regressions, and improvement opportunities
Create runbooks and response patterns for common LLM and AI-product failure modes Scale AI quality across teams
Build reusable libraries, SDKs, templates, and reference implementations that make correct AI instrumentation and evaluation easy
Document standards for tracing, metadata, prompt/version tracking, evaluation, cost reporting, and incident response
Coach product teams on AI quality, evaluation design, observability, and reliable release practices
Help establish shared patterns that let OnBoard scale AI development across product lines Support responsible and compliant AI delivery
Ensure AI systems handle sensitive data appropriately and align with security, privacy, SOC 2, ISO 27001, and data-residency requirements
Monitor guardrails, policy enforcement, content safety signals, and safety-related anomalies as a distinct observability concern
Support auditability and traceability of AI interactions where required What We’re Looking For Required
5+ years of software engineering experience building production systems
Hands-on experience building or operating LLM-powered features, RAG systems, AI workflows, or similar AI applications
Strong engineering ability in Python, C#/.NET, or both
Practical understanding of prompts, embeddings, vector search, retrieval quality, orchestration patterns, and LLM application architecture
Experience designing evaluations, quality metrics, or regression frameworks for AI or software systems — with the judgment to assess whether an evaluation actually measures what matters
Strong observability fundamentals: tracing, logging, metrics, alerting, and production debugging
Experience with CI/CD, git workflows, cloud environments, and production release practices (Azure DevOps preferred)
Ability to communicate clearly with engineering, product, QA, security, and business stakeholders
Strong product judgment and genuine curiosity about how AI systems behave with real users
Proficiency with AI-assisted development tools (e.g., Claude Code, PlayerZero) Preferred
Experience with LLMOps or AI observability tools such as Arize, Langfuse, LangSmith, W&B, Humanloop, or Helicone
Experience with OpenTelemetry, Azure Monitor, Application Insights, or similar observability platforms
Experience with Azure AI Search, Pinecone, Qdrant, Weaviate, pgvector, or other vector search platforms
Experience with Semantic Kernel, LangChain, LlamaIndex, AutoGen, or related frameworks
Experience with LLM-as-judge evaluation, RAG evaluation, semantic similarity metrics, hallucination detection, groundedness scoring, or human-feedback workflows
Experience with dedicated evaluation frameworks (e.g., DeepEval, LangTest) and benchmarking approaches for LLM outputs
Experience with A/B testing, online experimentation, or product analytics for AI features
Experience in regulated environments with SOC 2, ISO 27001, PII handling, or data-residency requirements
Background in QA, ML, or data engineering that informs a rigorous approach to quality measurement You’ll Be Successful If You
Make AI feature quality measurable and visible
Help teams detect regressions before customers do
Improve reliability, latency, cost, and user trust in AI-powered experiences
Build reusable patterns that reduce friction for every product team
Translate ambiguous AI behavior into concrete engineering actions
Balance innovation with operational discipline Why This Role Matters AI is becoming a core part of the OnBoard product experience. This role helps determine whether that AI is merely impressive in demos or dependable for thousands of organizations making important governance decisions. You will have the opportunity to shape OnBoard’s AI engineering standards, influence product architecture, and build the systems that let teams ship AI faster, safer, and with greater confidence. Competencies
Accountability
Adaptability
AI Curiosity / Innovation
Applied Learning
Business Acumen
Collaboration
Customer Focus
Dealing with Ambiguity
Decision Making
Driving for Results
Initiating Action
Planning and Organizing
Technical / Professional Knowledge About the Company: Boards set the standard for what organizations can achieve. At OnBoard, our board management software helps boards function at a higher level so every organization can make a bigger difference in the world. Launched in 2011, today, OnBoard serves as the board intelligence platform for more than 5,000 organizations and their 12,000 boards and committees in 60 countries worldwide. With customers in higher education, nonprofit, healthcare systems, government, and enterprise business, OnBoard is the leading board management provider. OnBoard has grown from a class project at Purdue University in West Lafayette, Indiana in 2003 into the world’s leading board management software platform today. Backed by JMI Equity and the acquisitions of eScribe and Govenda, OnBoard is positioned to become the industry leader in Board Management and Meeting Solutions for private and public sector entities. Benefits and Perks: Fully remote work with company provided equipment (laptop, software, etc.) Employment with a growing, casual, fun, philanthropic minded company US Based Employees Comprehensive, high-quality medical/prescription drug plan options, as well as dental and vision plan offerings. An employer contribution to your Health Savings Account (HSA) if you participate in a High Deductible Healthcare Plan. Medical Flexible Spending Accounts available. Dependent Care Flexible Spending Accounts available. Basic life insurance in the amount of $50,000 or 1 X’s your salary (whichever is higher). Short and long-term disability and Accidental Death and Dismemberment benefits at no cost to you. 401K Retirement Savings Plan with automatic enrollment at the first of the month following 60 days of employment at 5% to help you secure your financial freedom. We offer a generous company match that starts on the first of the month following 60 days of employment. The company match is dollar for dollar on the first 3% of your pay that you contribute and $0.50 on the dollar on the next 2%, for a total match of 4%. Paid Time Off (PTO)/Holiday CAN Based Employees Employer paid Life and Accidental Death Insurance Contribution to Health Care Spending Account Dependent Life Insurance Optional Life Insurance LTD Insurance Drug and Paramedical Coverage Dental Insurance Vision Insurance EAP AUS Based employees Superannuation rate of 12% Monthly stipend of $400 AUD to purchase private medical insurance UK Based Employees (via EPG) Pension
Aegon Passageways/OnBoard contributes 8% of the employee’s basic salary Employees can contribute up to 100% of salary subject to max limits Enrolled from Day 1 of employment Private Medical Insurance Life Assurance Income Protection Critical Illness Employee Assistance Programme Serious Illness Benefit Help@Hand Cashplan Diversity Statement
Culture of Togetherness: At OnBoard, our mission is to encourage and celebrate a culture of togetherness. We acknowledge that uniqueness is powerful, and we welcome, foster, and appreciate all. Diversity, Equity, and Inclusiveness fuel the Pathfinder atmosphere and all our efforts. Our power is in our people and we Pledge 1% to give back to our communities and across the globe. OnBoard is an equal opportunity employer and committed to a diverse and inclusive working environment. We do not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Interview Transparency & Technology Disclosure We use video/audio recordings and artificial intelligence (AI) tools during our interview process to transcribe responses, evaluate skills, and streamline evaluations. Your data is processed securely and handled in line with our Privacy Policy and local data protection laws This job is filled or no longer available Explore more remote jobs Observability AI Engineer AI Senior Product Engineering Insurance LLM Data Make Design Azure 4247 similar remote jobs Explore latest remote opportunities and join a team that values work flexibility. View all jobs Senior AI Software Engineer, AI Controls Agility Robotics $187k-$292k Month ago Senior Software Engineer AI Engineer Midi Health $170k-$210k 4 Months ago Senior Software Engineer Forward Deployed AI Engineer MongoDB 7 Months ago Senior AI Engineer (Product Neuro Forge Team) AppFollow 2 Weeks ago Senior AI Engineer INDG | Grip Month ago Senior AI Engineer ShyftLabs $87k-$117k 4 Months ago Remote companies like OnBoard Find your next opportunity with companies that specialize in Enterprise Portals, Collaboration Software, Board Portals, and Software. Explore remote-first companies like OnBoard that prioritize flexible work and home-office freedom. All companies Calendly 501-1000 calendly.com Develops a scheduling automation platform for individuals, teams, and organizations globally. → Apriorit 201-500 www.apriorit.com Software engineering services → Trackforce 201-500 www.trackforce.com Develops a cloud platform for physical security workforce management, serving guarding companies and corporate enterprises globally. → Incode 501-1000 www.incode.com AI-powered identity verification and fraud prevention solutions for enterprises. → VComply 11-50 www.v-comply.com Agile GRC SaaS platform → CREATEQ 201-500 www.createq.com We build and manage dedicated software teams, focusing on AI-powered modernization, compliance, and security for high-stakes industries. → Project: Career Search Rev. 2026.9 [ Remote Jobs ] Direct Access We source jobs directly from 21,000+ company career pages. No intermediaries. Search Jobs Post a Job 01 Discover Hidden Jobs Unique jobs you won't find on other job boards. 02 Advanced Filters Filter by category, benefits, seniority, and more. 03 Priority Job Alerts Get timely alerts for new job openings every day. 04 Manage Your Job Hunt Save jobs you like and keep a simple list of your applications. 21,000+ SOURCES remotefirstjobs.com UPDATED 24/7