Are you interested in building the technical foundation of the worldwide transition to clean energy? Do you enjoy working with a highly motivated and talented team to deliver mission critical software?
Voltus is growing our Infrastructure team to help deploy, manage, troubleshoot, and enhance the Platform and tooling that every Voltus engineer and our dispatch-critical systems depend on. As a Senior Software Engineer on Infrastructure, you will own significant pieces of our core Platform, mentor other engineers, and help set the technical direction for how we build, deploy, and operate services at Voltus. You will join a team of [N] engineers supporting roughly [M] engineers across the org, so the leverage on your work is high and so is the responsibility.
Our Platform runs on HashiCorp's Nomad, Consul, and Vault in AWS. We are specifically looking for someone who brings deep Kubernetes experience to this team, because we expect to run Kubernetes workloads alongside Nomad and that is depth we do not have in house today. You will not be the only person who knows containers, but you may well be the one who knows Kubernetes best, and we want you to shape how we adopt and operate it.
You will develop the tooling that lets every engineering team ship reliably, build the testing and observability that keeps our real-time systems healthy, and help shape how we safely fold AI-assisted development and tooling into our day-to-day engineering.
When Voltus commits capacity to a grid operator, we are obligated to deliver it. That shapes how this team works: changes are planned around live dispatch windows, sequenced so each step can be rolled back, and owned by the person who made them, including on call.
Voltus is a fully distributed company and this role is remote. You can work from anywhere, but you must overlap with the Eastern time zone for at least 4 hours of the workday.
Own core Platform services and major migrations end to end , from proposal to production. Our team regularly leads multi-month migrations of stateful, business-critical systems with no customer-visible downtime.
Run our containerized workloads and the delivery path that ships them — orchestration and scheduling, GitOps-style deploys, progressive rollout and rollback, and service mesh. Bring Kubernetes practice to a team that runs Nomad today, and help us decide what belongs where rather than adopting a second scheduler for its own sake.
Architect and operate our AWS foundation. Multi-account structure and governance, IAM and cross-account access, VPC and Transit Gateway, PrivateLink, DNS and certificates, and the egress paths our dispatch traffic reaches grid operators over. On those paths, a changed address or an expired certificate is a market outage.
Treat identity, secrets, and encryption as first-class infrastructure — workload identity, least privilege, SSO and OIDC, machine-to-machine credentials, Vault, and key ownership and rotation. As we open more of production to cloud and AI access, you make sure every human and workload has exactly the access it needs and no more.
Operate the stateful systems everything else sits on : database upgrades and replication, message brokers in the critical path, caches and time-series stores, and the unglamorous part — backup coverage and restores you have actually tested.
Instrument deeply for observability. Distributed tracing, meaningful metrics and SLOs, and the testing frameworks that keep dispatch comms and market message flows healthy. Where monitoring has sprawled into overlapping tools with alerts that live only in a UI, consolidate it into something defined in code that an on-call engineer can actually reason about under pressure.
Build the infrastructure as code and developer tooling the whole org depends on , using Terraform, GitHub, Buildkite, Docker, Nomad, and our internal tools. That includes bringing older infrastructure under code: importing what was built by hand, detecting drift, and making what is in code match what is actually running.
Help build the infrastructure that AI runs on. AI-assisted development is central to where we are going: you will build the guardrails that let engineers and AI tools reach internal systems securely, and use those tools yourself to move faster and to understand and document large systems quickly.
Strong production software development experience in Go and/or Python. You build and maintain real services and tooling, write tests, and care about code quality, not just scripts.
Roughly 6+ years of professional software engineering , with several in DevOps / SRE operating production systems. You have owned deployments and been on the hook for reliability and on-call.
A track record of owning meaningful infrastructure projects end to end , ideally including a migration of a stateful or business-critical system with minimal disruption. You plan around operational windows, sequence work so each step has a rollback, and would rather phase a migration over weeks than take one clever shortcut.
Real depth in AWS , beyond launching resources in a single account. You have worked with multi-account organizations, IAM and cross-account access, VPC and network design, DNS, secrets management, and encryption key management, and you understand how those pieces constrain each other. You know the difference between provisioning and configuration management, and you default to least privilege.
Deep, hands-on Kubernetes experience in production. You have operated real clusters, not just deployed to someone else's: upgrades, networking and ingress, RBAC, resource management and autoscaling, and debugging a workload that is misbehaving under load. EKS and the surrounding ecosystem (ArgoCD or Flux, Helm, operators, multi-tenant clusters) is a strong plus. This is the clearest gap on our team and a large part of why we are opening this role.
Strong infrastructure-as-code skills (Terraform or similar). You have worked in a codebase that did not start out fully covered and improved it.
Real depth in monitoring and observability , and not only as a consumer of one managed vendor. You instrument systems thoughtfully, define metrics, alerts, and dashboards as code, and can introduce distributed tracing where none exists. Comfort operating the open-source stack (Prometheus, Grafana, and log and search clusters such as Elasticsearch or OpenSearch) matters here: capacity, retention, index lifecycle, and upgrades, not just querying it.
Hands-on operational experience with stateful systems : relational databases, message brokers, or both. You have done a version upgrade, a replication change, or a restore under pressure and know why backups you have not tested do not count.
Comfort operating and improving systems you did not build. Some of our most important work involves reading unfamiliar code, mapping undocumented dependencies, and making careful changes to systems whose original authors are not available to ask.
You communicate clearly, write good documentation, mentor teammates, and can drive cross-team coordination on shared infrastructure.
You are genuinely excited about AI-assisted development and the role of AI in modern infrastructure. You either use these tools today (Claude Code, MCP, agents) or are eager to, and you want to help build the platform that supports them safely.
Experience with the HashiCorp stack (Nomad, Consul, Vault).
Experience introducing Kubernetes to an organization that did not already run it, or operating it alongside another scheduler.
Experience running self-hosted CI and build tooling (Jenkins, ArgoCD, artifact repositories).
Experience with OpenTelemetry, or with consolidating several overlapping monitoring tools into one coherent stack.
Experience testing event-driven workflows, and with managed streaming platforms such as MSK.
Experience with AWS Organizations and Control Tower, service control policies, or leading an account restructuring or consolidation.
Experience owning an identity migration or SSO consolidation (Auth0, Okta, Cognito, Keycloak, or similar).
Experience building internal developer tooling or CLIs, and improving parity between local, dev, and production environments.
Ability to read Java or C++ well enough to debug and modify services in those languages, even if you would not choose to write them.
Hands-on experience with AI developer tooling (Claude Code, MCP servers, agent workflows) or with running model infrastructure (e.g. AWS Bedrock).
Interest in the energy industry and the clean energy transition.
