DiscoverStartupsAZXJobs at AZX: Explore current Opportunities
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AZX
Actively Hiring
We deliver AI solutions for energy, real estate, supply chain and other infrastructure industries11-50 Employees
  • Growing fast
    Showed strong hiring growth in the past month
View 8 jobs

Jobs at AZX

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Engineering

Forward Deployed AI Engineer (Senior)

NewPosted 1 week ago

Forward Deployed AI Engineer (Senior)

  • Own your client's technical delivery end to end — discovery support, solution design, build, deployment into the client's environment, and a handover their team can actually run.
  • Build the trust machinery behind every system you ship: eval harnesses, replay loops, guardrails, cost/latency budgets, monitoring, and a defined "what happens when it's unsure" path.
Remote • Seattle
$140k – $230k
Engineering

Senior Product Engineer (AI, Full-Stack)

NewPosted 2 weeks ago

Senior Product Engineer (AI, Full-Stack)

  • Build and evolve the chat surface and agent workspaces — streaming protocol on both client and server, message/run persistence, tool-call and approval UX, and citation rendering.
  • Partner with the platform team on the app builder: the fixed app template and toolchain it generates against, the preview sandbox seam, and the generation/repair loop UX.
Remote • Seattle
$140k – $230k
Engineering

Senior ML Engineer (Energy & Utilities)

NewPosted 2 weeks ago

Senior ML Engineer (Energy & Utilities)

  • Own the reusable utility ML libraries — forecasting, disaggregation, demand response, detection, and asset health — each shipped with its own evaluation harness and documentation.
  • Build capabilities once as tested libraries with validation harnesses, so client pods deploy proven components (like meter disaggregation or load forecasting with abstention and monitoring built in) instead of reinventing them per engagement.
Remote • Seattle
$140k – $230k
Engineering

Senior ML Engineer (Client Solutions)

NewPosted 2 weeks ago

Senior ML Engineer (Client Solutions)

  • Own the full ML delivery lifecycle: data discovery and cleaning, modeling, evaluation, deployment into the client environment, scheduling, monitoring, and retraining policy.
  • Build forecasting and detection models that hold up against real-world data quality issues (late feeds, revised rows, missing labels).
Remote • Seattle
$140k – $230k
Engineering

Senior Backend Engineer (AI Platform)

NewPosted 2 weeks ago

Senior Backend Engineer (AI Platform)

  • Own the LLM gateway: routing, metering, budgets, guardrail composition, and provider/backend adapters across hosted and self-hosted models.
  • Manage the retrieval and knowledge service: connectors, chunking, hybrid search and reranking, grounded answers, and the MCP surface.
Remote • Seattle
$140k – $230k
Engineering

Senior Software Engineer (AI Inference & Runtime Platform)

NewPosted 2 weeks ago

Senior Software Engineer (AI Inference & Runtime Platform)

  • Manage the serving tier for open-weight models: engine deployment and configuration, cold-start strategy, per-model SLOs, and upgrade/canary discipline.
  • Administer the Kubernetes layer for inference and sandbox workloads: operators and CRDs, autoscaling (KEDA/Karpenter-class), GPU scheduling and sharing, and node lifecycle.
Remote • Seattle
$140k – $230k
Marketing

Marketing Program Manager

NewPosted 3 weeks ago

Marketing Program Manager

  • Master the operating calendar for all GTM programs, including dependencies across product milestones, deployment timelines, and sales priorities.
  • Day-to-day execution support of demand generation programs targeting a narrow, high-value universe of accounts.
Remote • Seattle
$80k – $120k
Other

Solutions Engagement Manager (AI/ML)

NewPosted 1 month ago

Solutions Engagement Manager (AI/ML)

  • Partner directly with clients to understand their desired outcomes — not just their stated requests — and translate that understanding into clear, actionable direction for the engineering team.
  • Lead engineers and act as the technical product manager for your accounts: define what should be built, why it matters, and how success will be measured. This includes reviewing system architecture, evaluating data pipeline designs, assessing API integrations, and/or doing technical requirements analysis before handing work to engineers.
Seattle
$130k – $200k
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