Engineering Manager

Location: Remote (US)Department: Insights (AI/ML)Reports to: Director of Science and ArchitectureAbout The RoleIrth is building a new AI-driven threat and risk management platform for pipeline asset integrity. The platform brings together three capabilities that have never previously lived in one place at Irth:A governed, cross-product data platform built on Databricks and AzureAn AI-powered ingestion layer that normalizes, repairs, and enriches customer data without services-heavy onboardingA reusable analytical layer that runs industry-standard, Irth-developed, and customer-built risk models against that dataWe are looking for an Engineering Manager to lead the team building this platform.You will own delivery and technical execution across a small, senior team spanning data architecture, data engineering, data science, application engineering, and QA. You will be accountable for what the team ships against a phased, gated delivery plan.This is a player-coach role. You will spend a meaningful portion of each week in the codebase, reviewing designs, and participating in code reviews. We are not looking for someone who manages from a distance. We are looking for an experienced engineer who has grown into leading people and wants to continue doing both.The work is highly regulated. Pipeline operators use these outputs to determine where to dig, what to repair, and how to justify that spending to regulators. Every calculation therefore needs to be traceable, reproducible, and defensible under audit.If you enjoy solving problems where correctness genuinely matters, this is an opportunity to make a meaningful impact.Key Responsibilities2. Hands-On Engineering3. Technical Direction & Engineering Quality4. Compliance, Security & Audit Readiness5. People Leadership & Hiring6. Cross-Functional Partnership Delivery Ownership — Primary ResponsibilityOwn delivery and technical execution against the phase plan, including scope commitments, sequencing, dependencies, and release readiness at each gateRun the team's operating rhythm, including sprint planning, stand-ups, demos, and retrospectives, with clear visibility into blockers and schedule riskTranslate product requirements into technical workstreams and break them into achievable incrementsHold the line on scope when delivery plans are at riskManage team capacity and velocity across parallel workstreams spanning the data platform, ingestion layer, and analytical layerEscalate risks early and with a clear recommendation; surface milestone risk to leadership before it becomes a missed gateContribute directly to the codebase, particularly on foundational and high-risk components where experienced engineering involvement can materially improve outcomesReview pull requests, design documents, and architecture decision recordsEstablish and maintain a high standard for engineering quality and technical decision-makingPrototype and de-risk unproven approaches, including agentic ingestion workflows and model execution patterns, before the team commits to themDebug production issues alongside the team rather than delegating themPartner with the Data Architect to establish and enforce standards for data modeling, lineage, governance, and platform patternsOwn engineering quality, including test coverage, CI/CD discipline, environment promotion, observability, and the definition of doneMake and document build-versus-buy and tooling decisions, including evaluation of third-party ingestion and AI toolingBalance delivery pressure against technical debt and make those tradeoffs explicitEnsure risk calculations, data transformations, and model outputs are traceable and reproducible to a standard that can withstand regulatory auditHold the team accountable to platform security requirements, including access control, tenant isolation, secrets management, and SOC 2-aligned controlsPlan and schedule production-readiness activities, including load testing, penetration testing, and access-control reviews ahead of each release milestoneRecruit, onboard, and develop a distributed team of mid-level and senior engineersConduct regular one-on-ones, set clear expectations, provide direct feedback, and own performance management and career developmentBuild a team culture in which engineers challenge one another's designs and disagree productivelyFoster an environment of technical ownership, accountability, collaboration, and continuous improvementPartner daily with Product on requirements, sequencing, priorities, and scope tradeoffsWork with the Project Management Office on plan integrity, dependency tracking, and gate-readiness reportingSupport customer-facing teams during pilots and previews, including technical discovery and issue triageCollaborate with domain subject-matter experts to ensure model behavior remains aligned with regulatory expectationsRequirementsQualificationsRequired8+ years of professional software or data engineering experience, including 2+ years of formally managing engineersA track record of remaining hands-on as a manager, with recent and demonstrable individual contributions to production systemsExperience delivering data-intensive or ML-backed products end to end, from architecture through production operationWorking knowledge of modern cloud data platforms; Databricks and Azure experience strongly preferred, including Delta Lake, Unity Catalog, and workflow orchestrationStrong Python and SQL skills, with the ability to read, review, and write production code across the team's technology stackExperience with CI/CD, infrastructure as code, environment promotion, and release managementDemonstrated ability to run a phased delivery plan with hard external commitments and communicate status honestly and effectively to executivesExperience hiring, onboarding, and developing engineers in a distributed or fully remote environmentStrong written communication skills, with the ability to author design documents, architecture decision records, and clear status narrativesPreferredExperience leading teams that build regulated, audit-defensible software where outputs are subject to external reviewFamiliarity with MLOps practices, including model registries, versioning, deployment, monitoring, and retraining pipelinesExperience with geospatial data and GIS-driven analyticsExposure to agentic AI or LLM-based document extraction in production environments, beyond prototypesExperience integrating third-party or customer-supplied models into a governed execution frameworkBackground in multi-tenant SaaS, including per-tenant isolation and data residency requirementsExperience using AI-assisted coding tools such as Cursor or GitHub Copilot and/or agentic coding tools such as Claude Code as part of a professional development workflow, along with a thoughtful perspective on responsible adoption across an engineering teamNice to HaveUnderstanding of pipeline integrity management concepts, including inline inspection, corrosion and crack growth, consequence modeling, and risk-based prioritizationFamiliarity with PHMSA 49 CFR 192, ASME B31.8S, or comparable regulatory frameworksPrior experience in energy, utilities, or critical infrastructure softwareExperience standing up a new team on a new platform rather than inheriting a mature engineering organizationSuccess MetricsSuccess in this role will be measured by:On-time delivery: Phase commitments are delivered on schedule, with gate criteria met and supporting evidence producedHigh-performing team: A strong engineering team is hired, onboarded, developed, and retained, with clear ownership across the platformHands-on technical contribution: Sustained personal contribution through code, code reviews, design work, and other visible technical artifacts in the repositoryAudit-ready platform: Outputs are reproducible and defensible, with no material findings in security or compliance reviewsPredictable execution: Forecasts are accurate, risks are escalated early, and gate reviews have few surprisesCross-functional effectiveness: Strong working relationships are maintained with Product, the Project Management Office, customer-facing teams, and domain subject-matter expertsBenefitsWhat We OfferJoin a dynamic, growing company with a strong reputation in its industryCompetitive salaryComprehensive health plan options, including medical, dental, and vision coverage401(k) plan with company matchFlexible PTO policy plus company-paid holidaysAdditional benefits, including life insurance, pet insurance, and employee discounts and perks programsGenerous one-time work-from-home stipend to help you set up your home workspaceCompany events and opportunities to connect, including monthly team lunches, volunteer outings, and quarterly gatheringsHybrid employees have access to complimentary snacks, beverages, and coffee at our Columbus, Ohio office