Engineering Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of delivery and technical execution in line with the phase plan, ensuring adherence to scope commitments, sequencing, dependencies, and release readiness at each gate.

• Facilitate sprint planning, daily stand-ups, demos, and retrospectives, while maintaining visibility into potential blockers and scheduling risks.

• Convert product requirements into technical workstreams and feasible increments.

• Oversee team capacity and velocity across the data platform, ingestion layer, and analytical layer.

• Raise risks and highlight milestone concerns to leadership.

• Directly contribute to the codebase, focusing on foundational and high-risk components.

• Evaluate pull requests, design documents, and architecture decision records.

• Set standards for engineering quality and technical decision-making.

• Prototype and mitigate risks associated with agentic ingestion workflows and model execution patterns.

• Troubleshoot production issues in collaboration with the team.

• Collaborate with the Data Architect on data modeling, lineage, governance, and platform standards.

• Manage test coverage, CI/CD practices, environment promotion, observability, and the definition of done.

• Make and document decisions regarding build-versus-buy and tooling choices.

• Balance delivery demands with the management of technical debt.

• Ensure traceability and reproducibility of risk calculations, data transformations, and model outputs for regulatory audits.

• Enforce security protocols for the platform, including access control, tenant isolation, secrets management, and SOC 2-aligned controls.

• Organize production-readiness activities, such as load testing, penetration testing, and access control reviews.

• Recruit, onboard, and nurture a distributed team of engineers.

• Conduct one-on-one meetings, set expectations, provide feedback, and manage performance and career development.

• Foster a culture of constructive technical disagreement, ownership, accountability, collaboration, and continuous improvement.

• Collaborate with Product on requirements, sequencing, priorities, and scope trade-offs.

• Work with the Project Management Office to ensure plan integrity, dependency tracking, and gate-readiness reporting.

• Assist customer-facing teams during pilots and previews, including technical discovery and issue triage.

• Work with domain experts to ensure model behavior aligns with regulatory expectations.

⛳️ Requirements

• A minimum of 8 years of professional experience in software or data engineering, including at least 2 years in a formal management role.

• Proven experience remaining hands-on as a manager, with recent, demonstrable contributions to production systems.

• Experience delivering end-to-end data-intensive or ML-driven products, from architecture to production operation.

• Familiarity with modern cloud data platforms; strong preference for Databricks and Azure experience, including Delta Lake, Unity Catalog, and workflow orchestration.

• Proficient in Python and SQL, capable of reading, reviewing, and writing production-level code across the team's technology stack.

• Experience with CI/CD, infrastructure as code, environment promotion, and release management.

• Demonstrated ability to execute a phased delivery plan with firm external commitments and communicate progress transparently and effectively to executives.

• Experience in hiring, onboarding, and developing engineers in a distributed or fully remote setting.

• Strong written communication skills, capable of drafting design documents, architecture decision records, and clear status updates.

• Preferred: experience leading teams that develop regulated, audit-compliant software with outputs subject to external review.

• Preferred: familiarity with MLOps practices, including model registries, versioning, deployment, monitoring, and retraining pipelines.

• Preferred: experience with geospatial data and GIS-driven analytics.

• Preferred: exposure to agentic AI or LLM-based document extraction in production settings beyond prototypes.

• Preferred: experience integrating third-party or customer-supplied models into a controlled execution framework.

• Preferred: background in multi-tenant SaaS, including per-tenant isolation and data residency requirements.

• Preferred: experience utilizing AI-assisted coding tools such as Cursor or GitHub Copilot and/or agentic coding tools like Claude Code.

• Nice to have: understanding of pipeline integrity management concepts, including inline inspection, corrosion and crack growth, consequence modeling, and risk-based prioritization.

• Nice to have: familiarity with PHMSA 49 CFR 192, ASME B31.8S, or similar regulatory frameworks.

• Nice to have: prior experience in energy, utilities, or critical infrastructure software.

• Nice to have: experience establishing a new team on a new platform rather than inheriting a mature engineering organization.

🏝️ Benefits

• Competitive salary

• Comprehensive health plan options, encompassing medical, dental, and vision coverage.

• 401(k) plan with company matching.

• Flexible PTO policy along with company-paid holidays.

• Life insurance

• Pet insurance

• Employee discounts and perks programs.

• Generous one-time work-from-home stipend to assist in setting up your home workspace.

• Company events and opportunities for connection, including monthly team lunches, volunteer outings, and quarterly gatherings.

• Hybrid employees can enjoy complimentary snacks, beverages, and coffee at our Columbus, Ohio office.