• Design, develop, and maintain software solutions in a legacy MUMPS / Caché environment • Perform coding, unit testing, and debugging to support ongoing system enhancements and maintenance • Collaborate with business analysts to translate requirements into technical solutions and provide support for requirements analysis • Support system, integration, and user acceptance testing • Participate in Beta (IOC) testing activities with active medical centers, including issue resolution • Provide ongoing production support and troubleshooting for deployed applications • Provide documentation of technical designs, processes, and system behavior • Work independently and collaboratively within a cross-functional team to meet project deadlines

Role Description As a Senior Software Engineer, you will help shape the future of our Horizon platform and the way we build software. Horizon is the platform behind SkySpecs' wind and solar inspection and asset-management business, and the work is hands-on building, end to end. As the cost of producing code falls, an engineer's impact comes more than ever from judgment, design, and outcomes, not volume. AI is central to how we work here, and we treat it as serious leverage: a force multiplier for engineers who already have strong instincts, not a substitute for them. We expect everyone to keep pushing what AI, automation, and agents make possible, and to bring the judgment that makes that leverage pay off. We do not separate thinking from doing. Engineers are expected to understand the problems they are solving, formulate effective solutions, and participate directly in delivery by writing and owning production code. The people closest to the work are expected to challenge assumptions, improve proposed approaches, and actively shape how outcomes are achieved. This is a full-stack engineering role. While engineers may develop areas of deeper expertise, we expect everyone to be capable of working across frontend, backend, infrastructure, data, and developer tooling as needed to deliver outcomes. We value engineers who can understand the entire system, formulate end-to-end solutions, and contribute wherever the work requires. Our platform is built using: - AWS - GitLab - Auth0 - Grafana - Terraform - Kafka - Node.js - TypeScript - Apollo GraphQL - React - Ant Design - Vitest - Playwright - PostgreSQL IN A GIVEN WEEK, YOU WILL: - [15%] Work with product managers, customers, internal users, and other engineers to understand requirements, constraints, and desired outcomes. - [10%] Formulate solutions, evaluate tradeoffs, and break work into executable milestones and implementation plans. - [55%] Build and ship software. Examples include: - Authoring and infrastructure as code. - Designing and implementing new services and APIs. - Building reusable user experiences and workflows. - Improving reliability, performance, security, and developer productivity. - Reviewing code generated by peers and by agents. - Leveraging AI tools and autonomous agents to accelerate delivery. - [20%] Improve Horizon, our engineering systems, and the way we work. Examples include: - Building internal tooling and automation. - Improving documentation and architectural clarity. - Reducing operational toil. - Expanding AI and agent capabilities. - Improving testing, observability, and deployment workflows. - Exploring new ideas, experiments, and prototypes that could improve Horizon or the way we build software. Success is measured by outcomes delivered, not lines of code written. Qualifications - 5+ years in roles where you wrote, shipped, and operated production software. - Depth in at least one part of the stack and the range to work across the rest. - Strong software engineering fundamentals and systems-thinking. - Ability to independently drive work from requirements through delivery. - Good judgment around tradeoffs, architecture, and maintainability. - Strong written communication skills. - Demonstrated ability to work within a cross-functional team of technical and non-technical contributors. - Ability to work effectively across multiple layers of the stack. - Experience working with AI-assisted and agentic development workflows. - Hands-on experience with AI-assisted and agentic development workflows, and a track record of evolving how you use them. - Sound judgment when using AI tools, including reviewing and correcting agent-generated code. Requirements - Familiarity with our stack: AWS, GitLab, Auth0, Grafana, Terraform, Kafka, Node.js, TypeScript, Apollo GraphQL, React, Ant Design, Vitest, Playwright, and PostgreSQL. - Experience building internal platforms, developer tooling, or automation systems. - Experience operating distributed systems at scale. - Background in utility scale energy generation, emphasis on renewables. What We Value - Own outcomes, not assignments. - Have strong opinions that are loosely held. - Operate autonomously and are self-accountable. - Create clarity from ambiguity. - Improve systems, not just features. - Take initiative in identifying and addressing risks, improvements, and opportunities that increase the impact of their work. - Continuously learn, adapt, and experiment with new technologies and ways of working. Location & Logistics - This role may be remote or located in the SkySpecs Ann Arbor headquarters, depending on candidate location and preference. Remote applicants will be expected to attend team meetings primarily in the US Eastern timezone. - This position does not offer financial support for relocation. - Applicants must be currently located in the United States and legally authorized to work in the United States for this employer now and in the future, without the need for visa sponsorship. We are unable to sponsor or take over sponsorship of employment visas at this time. - Base salary dependent on experience and location. Position is eligible for discretionary annual bonus. SkySpecs is an equal opportunity employer. SkySpecs does not discriminate in employment with regard to race, color, religion, national origin, citizenship status, ancestry, age, sex (including sexual harassment), sexual orientation, marital status, physical or mental disability, military status or unfavorable discharge from military service or any other characteristic protected by law.

Role Description We are seeking a visionary and hands-on Cloud SRE Architect to lead the design, development, and evolution of our next-generation public cloud platform. This role will oversee the end-to-end architecture across CPU, GPU, RDS, storage, networking, serverless, and AI services, ensuring global scalability, reliability, and performance. The ideal candidate is a strategic thinker with deep technical expertise in cloud infrastructure, platform engineering, and AI systems, capable of bridging architecture vision with real-world engineering execution. You will collaborate closely with cross-functional teams and global partners to define our cloud technology roadmap, optimize multi-region deployments, and deliver world-class infrastructure and platform solutions that power large-scale AI and enterprise workloads. Key Responsibilities - Collection & Storage: - collection-agent - customer-sdk-gateway - metrics-store - logs-store - traces-store - profiles-store - analytics-lake - enrichment-service - collection-monitor - Alert, Correlation & SLO: - alert-engine-framework - alert-correlation - slo-framework - default M-series alert rules - Topology, Cluster-Health & Cluster Platform Services: - topology-service - cluster-health-rollup - OSS-SRE-tool collection plugins for K8s, Slurm, Ray, Volcano, Kueue, and KubeRay - Fault-Prediction: - prediction-engine-framework - built-in predictors (GPU, Link, Disk, XPA, Straggler, SDC, Stranded GPU) - Remediation, Workflow, Inspection & Jobs: - remediation-actuator - orchestration-substrate (workflow engine) - inspection-orchestrator - job-scheduler - NCCL-baseline inspection probe - Hardware Lifecycle & DC Ops: - hardware-lifecycle - dc-operations - boot-provisioning - rolling-upgrade - bare-metal-bmc-service - auto-discovery - ZTP D0–D5 pipeline - IPMI bare-metal management - Identity, Secrets, Tenant-Config & CMDB: - iam-service - secrets-service - tenant-sre-config - cmdb-cache - schema registry - Customer-Bridge, Ticketing & SRE Platform Portal: - customer-bridge - customer-ticketing - sre-operation-system - Customer Console BFF - SRE Console BFF - Backup, DR & Meta-Monitor: - backup-orchestrator - meta-monitor - external-watcher integration (Datadog or equivalent) - CI/CD, GitOps, Plugin Framework & SRE Image Registry: - cicd-pipeline - gitops-sync - plugin-registry - sre-image-registry - Self-Improving Agent: - agent-control-plane - agent-discovery - agent-codegen - agent-sandbox - per-Region LLM gateway - Global SRE Management: - maintenance-window-orchestrator - change-management - capacity-planner - cost-optimizer - gpu-efficiency-dashboard - network-stability-dashboard - patching-orchestrator - artifact-management - compat-matrix-service - security-platform Qualifications - 7+ years of production software engineering experience, including 2 or more years operating what you built (real on-call experience, not just shipping code) - Production-depth mastery of at least one systems-grade language—Go (preferred), Rust, or Java. Proficiency in Python for tooling and SDK work - Strong grasp of at-least-once vs. exactly-once trade-offs, idempotency, back-pressure, leader election, consistent hashing, gossip, and fan-out - Experience at production scale with Prometheus, VictoriaMetrics, Mimir, Thanos, Loki, Elasticsearch, Tempo, Jaeger, or OpenTelemetry - Hands-on experience with Argo, Flux, Helm, Kustomize, Cosign signing, signed-bundle promotion, and blast-radius-aware rollouts - Proven experience writing a controller or CRD handling real production traffic - Experience executing end-to-end mTLS bootstrap with certificate rotation - Ability to read a Prometheus query plan, build a recording-rule strategy, and write SQL that joins per-tenant telemetry against analytics-lake tables - Rigorous approach to unit, integration, contract, chaos, and soak testing - Ability to author clear design docs that align with existing platform architecture Preferred Qualifications (GPU / AI-Infra Context) - Deep understanding of DCGM and NVIDIA driver internals, including XID semantics and MIG / vGPU partitioning - Experience with InfiniBand or RoCE fabrics, including subnet managers, partitioning, optical health, and NCCL collective tracing - Experience managing Lustre, NetApp, Pure, DDN, VAST, or NVMe-oF under multi-tenant loads - Hands-on experience with BMC, IPMI, and Redfish at OEM scale (Supermicro, Dell, HPE, Lenovo) - Familiarity with Kubernetes GPU Operator, Slurm controller, or Ray GCS - BS/MS in Computer Science or similar - Hyperscale or NeoCloud experience Company Description Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure. Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence. Headquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.

Your role at DynatraceDynatrace's growth is increasingly tied to deep, co-engineered partnerships with the three hyperscalers and with the IDE and AI-tooling vendors developers actually use day-to-day. Recent integrations show that hyperscalers and IDE providers are no longer just deployment targets but co-development partners. The Model Context Protocol (MCP) has become the connective tissue: Dynatrace ships MCP servers so that Claude, Cursor, VS Code, JetBrains, Kiro, and other AI-assisted IDEs can query observability data natively. At the same time, customer workloads are shifting from traditional services to agentic AI systems that need a fundamentally new kind of observability. This role sits at that intersection. You will build the product code that makes Dynatrace work seamlessly with hyperscaler AI services and with the AI-native IDEs developers use to build on top of them, in close technical collaboration with engineering counterparts at AWS, Microsoft, Google, Anthropic, GitHub, and Cursor. The work is shipping code — APIs, agents, integrations, MCP servers, IDE extensions, telemetry pipelines — with partner engineers in the room. What you will do - Design and build integrations between Dynatrace and hyperscaler AI / observability services - Build and maintain Dynatrace's Model Context Protocol (MCP) servers so AI assistants and agents can query problems, traces, logs, and Davis insights as first-class tools — and contribute upstream to the MCP spec where it matters. - Co-develop with IDE providers (Anthropic / Claude Code, GitHub Copilot, JetBrains AI, Cursor, Windsurf, AWS Kiro, Gemini CLI) so Dynatrace observability shows up where developers already work — plugins, extensions, slash commands, MCP integrations. - Co-develop with partner engineering teams at AWS, Microsoft, Google, and IDE vendors — joint design docs, shared backlogs, paired debugging across org boundaries. - Extend Dynatrace's OneAgent and OpenTelemetry pipelines to capture traces, metrics, and evaluations from agentic AI workloads (tool calls, prompt chains, model latency, hallucination signals). - Contribute to launch-partner integrations — being one of the first observability providers shipping against a new hyperscaler or IDE-vendor service requires fast iteration against pre-GA APIs. - Own a slice of the partner-facing SDK, MCP server, or IDE-extension surface end-to-end: code, tests, docs, marketplace listing, on-call. - Represent Dynatrace engineering in technical reviews with partners; translate Dynatrace's Davis AI and causal-AI capabilities into terms partner engineers care about. - Mentor other engineers and raise the bar on how the team works across org boundaries. What will help you succeedEngineering foundation - 5+ years of professional software engineering experience building and operating production backend systems. - Strong proficiency in at least one of Java, Go, Python, or TypeScript; able to ramp on a second within a quarter. - Designed and shipped public-facing or partner-facing APIs (REST and / or gRPC), including versioning, backwards compatibility, and SDK ergonomics. Hyperscaler depth (at least one) - Hands-on, production-grade experience with AWS, Azure, or GCP — building against native SDKs, not just deploying to VMs. - Concrete familiarity with the partner-relevant surface of that cloud: AWS: Bedrock / AgentCore, Lambda, EKS, CloudWatch, AWS Marketplace, Partner Network (APN).Azure: Azure OpenAI, AKS, Azure Monitor, SRE Agent, Azure Marketplace, MISA.GCP: Vertex AI / Gemini, GKE, Cloud Operations, Google Cloud Marketplace, Partner Advantage. Observability and AI workloads - Working knowledge of observability primitives: metrics, logs, distributed tracing, OpenTelemetry instrumentation. - Understanding of how to instrument LLM and agentic-AI workloads: prompt / response capture, token usage, tool-call traces, evaluation signals, latency and cost attribution. - Comfortable reasoning about SLOs, error budgets, and incident response in customer-facing systems. MCP and IDE-provider integration - Practical experience with the Model Context Protocol (MCP) — building MCP servers, clients, or both. Comfortable with stdio and HTTP transports, tool / resource / prompt primitives, auth, and the realities of running MCP in production. - Built at least one IDE extension, plugin, or integration that real developers used — for VS Code, JetBrains, Cursor, Claude Code, GitHub Copilot, Gemini CLI, Kiro, or similar. - Understands the AI-assisted developer workflow end-to-end: how agents discover tools, how context windows fill up, how tool outputs get re-ranked, why a well-designed tool schema matters more than a clever prompt. - Can reason about trade-offs of agent-facing API design vs. human-facing API design (token cost, determinism, error surfacing, idempotency). Why you will love being a Dynatracer - Dynatrace is a leader in unified observability and security. - We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance. - Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances. - You'll get to work at the forefront of innovation with Dynatrace Intelligence—the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next— automatically. - Over 50% of the Fortune 100 companies are current customers of Dynatrace. Compensation and Rewards - We offer attractive compensation packages and stock purchase options with numerous benefits and advantages. - Due to legal reasons, we are obliged to list a salary range for this position, which is €61,000 up to €92,000 gross per year based on full-time employment (38.5 h/week). We’ve listed the salary range for transparency, but if your experience and skills bring unique value, we’d still love to hear from you—please apply even if you’re outside the range. Equal Employment OpportunityDynatrace provides equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected characteristic. We actively foster an inclusive workplace that celebrates differences and promotes accessibility, collaboration, and growth for all.