Benefits
- Medical insurance coverage
- Dental care benefits
- Vision care benefits
- Income protection including disability, life/AD&D, critical illness, and accident coverage
- Employee Assistance Program (EAP) for personal support
- Healthcare Spending Account (HSA) and commuter benefits
- Lifestyle and wellbeing initiatives
- Pet insurance options
Work Arrangement
Hybrid
Benefits
- Medical
- Dental
- Vision
- Income Protection (disability, life/AD&D, critical illness, accident)
- Employee Assistance Program (EAP)
- Healthcare Spending Account (HSA), Commuter
- Lifestyle & Wellbeing Program
- Pet Insurance
Team
The Enverus AI team works across the Enverus ONE platform and evolves with technology. The team includes Product Managers, Senior Product Managers, and Principal Product Managers working in pods across AI engineering, platform teams, data strategy, domain PMs, customer success, marketing, and sales.
Performance Objectives
- Ship agentic products end-to-end. Own generative AI products from ideation and prototype through production deployment, adoption, and iteration. Define agent behavior, tool use, evaluations, guardrails, and the user experience around autonomous and semi-agentic workflows.
- Translate strategy into phased execution. Frame the long-horizon product direction, then break it into phases, milestones, and sprint-level work. Stay in the details with engineering and data science through delivery — not just at the planning stage. The handoff from strategy to execution is your job, not someone else's.
- Work directly with energy customers. Sit in on deployments, run discovery, lead demos, shadow real users, and bring customer problems back into the product. Customer proximity is the primary input to product direction, not an afterthought.
- Operate hands-on in the product. Use Enverus ONE daily. Test workflows yourself. Use coding agents (Claude Code, Cursor, or equivalents) in your own work. Prototype when needed. Ground your direction in firsthand experience, not secondhand reports.
- Drive cross-functional execution. Coordinate across AI engineering, platform teams, data strategy, domain PMs, customer success, marketing, and sales. Surface blockers early, drive alignment without formal authority, and keep work moving across pods, time zones, and geographies.
- Own backlog, sprints, and delivery. Maintain a clean, prioritized backlog. Write development-ready stories with clear acceptance criteria. Participate actively in agile ceremonies. Keep the team moving with urgency and clarity.
- Shape commercialization and GTM. Partner with commercial leaders on packaging, pricing, access models, and launch readiness. Translate technical capability into customer-facing value and clear product narratives.
- Communicate strategy and outcomes. Deliver structured, honest updates to leadership, product peers, and commercial teams. At the Principal level, this extends to executive-facing and external customer communication.
- Adapt as priorities move. The roadmap will shift. The technology will shift. Re-plan fast, re-scope cleanly, and keep the team productive through the change.
What we expect from every candidate
- Hands-on experience building agents. You have personally designed, built, or shipped generative AI agents — not just managed a team that did. You're fluent in tool use, retrieval patterns, orchestration, evaluation, and the real work of getting agentic systems to behave reliably in production.
- Technical depth in generative AI. Strong working understanding of LLMs, prompting, fine-tuning, RAG, agent frameworks, model evaluation, and where the frontier is today. You can hold a serious conversation with AI engineers and data scientists without a translator.
- Strategic and tactical in equal measure. You operate at the whiteboard and in the backlog on the same day. You formulate big-picture strategy, break it into phases, and work directly with technology and data science through execution and delivery.
- Customer-facing instinct. Comfortable in the room with enterprise customers. You run discovery, lead demos, sit through deployments, and take hard feedback without defensiveness.
- End-to-end delivery orientation. You own the full lifecycle — requirements, sprints, QA, launch, adoption, iteration — rather than a slice of it. Active product participant, not a pure requirements-writer.
- Bias for speed. You ship fast in ambiguous environments. You don't wait for perfect conditions. Build, test, learn, iterate.
- Can-do attitude. Your default mode is "I'll figure it out." You identify what needs doing and do it. You don't escalate when you should execute.
- Comfort with rapid change. You thrive when the plan shifts. If you need stability to do your best work, this role will frustrate you. If you enjoy the adjustment, you'll do your best work here.
- Cross-functional influence. You work effectively across teams, functions, and geographies without formal authority. You build relationships and maintain alignment through consistent, reliable follow-through.
- Crisp communication. Structured writer and speaker who can translate frontier-stage work into compelling narratives for executives, customers, and engineers.
- Energy industry experience (strongly preferred). Prior work with upstream, midstream, power and renewables, trading, financial institutions, or OFS is a significant advantage. Not a hard requirement, but candidates should be able to get up to speed fast and stay credible in front of energy customers.
Product Manager (typically 3–5 years of PM experience)
- Scope: A specific workstream or product surface.
- Strategy: Contributes to strategy for your area; primarily accountable for execution quality and delivery velocity.
- Execution: Drives day-to-day backlog, sprint execution, QA, and cross-functional coordination with engineering and data science.
- Communication: Within the product and engineering organization.
Senior Product Manager (typically 5–8 years of PM experience)
- Scope: A larger product area or multiple connected workstreams.
- Strategy: Defines roadmap and phasing; shapes direction for your area.
- Execution: Runs execution directly alongside engineering and data science — same backlog ownership, sprint participation, and hands-on product engagement as PM level, just across a wider surface.
- Communication: Across product, engineering, and commercial leadership. Leads customer engagements and contributes to commercialization decisions.
Principal Product Manager (typically 8+ years of PM experience)
- Scope: A significant slice of the Enverus AI portfolio; influences platform decisions that span multiple teams and pods.
- Strategy: Sets strategic direction. Shapes commercialization, packaging, pricing, and GTM readiness with commercial leaders. Has taken internal or early-stage AI products to market before.
- Execution: Still a hands-on practitioner. Writes stories when needed, sits in standups, tests agents, debugs flows, and ships alongside the team. The strategic work is additive to execution, not a replacement for it.
- Communication: Executive-facing and external customer communication responsibility.
Not specified
