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Remote / Online - Candidates ideally in
Pittsburgh, Allegheny County, Pennsylvania, 15201, USA
Listing for: Tempo Software
Full Time, Remote/Work from Home position
Listed on 2026-07-16
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 220000 - 300000 USD Yearly USD 220000.00 300000.00 YEAR
Job Description & How to Apply Below

Senior AI/ML Engineer

Remote (EST/EDT) Full-Time $220,000 - $300,000/yr

Founded in 2006, we're one of the largest app vendors (300+ employees) supporting 30,000+ customers worldwide - including Amazon, Disney, Dell, Pay Pal, and Hulu. One in three Fortune 500 companies relies on our products!! We are building the intelligence layer that helps product and engineering teams plan, allocate, and act with confidence - turning noisy signals into clear, actionable decisions.

You'll join a product team (not an isolated research silo) and ship production AI systems used by real customers. We're currently growing at a 40% YoY pace and we need your help to keep up with the momentum!

We're looking for a Senior AI/ML Engineer who will be working at the intersection of LLMs, real-time signal processing, and enterprise decision-making. If you treat AI as a production engineering discipline - not a notebook experiment - this is the role for you.

What you'll be doing:

  • Signal & anomaly detection
    - Build statistical and ML detectors that separate noise from real problems in CDC event streams and external integrations.
  • Insight synthesis engine
    - Ship an LLM-powered correlation engine that returns root causes, confidence scores, and evidence chains, not just alerts.
  • Planning rules compiler
    - Translate natural-language planning rules into structured parameters for a deterministic Monte Carlo scheduling engine.
  • Evaluation & testing frameworks
    - Create regression suites, A/B testing, and confidence-calibration pipelines so model changes are safe and measurable.
  • MCP tool definitions
    - Define LLM-ready tool specs (Item Store queries, capacity lookups, scenario simulations) for runtime tool use in a hub-and-spoke agent architecture.

What I need from you:

  • Proven track record shipping LLM-powered features or products (not prototypes) that real users rely on.
  • Hands-on experience orchestrating agents (multi-step reasoning, tool use, autonomous action with guardrails) - Lang Chain, Llama Index, Auto Gen, CrewAI, or equivalent.
  • Deep LLM engineering fundamentals: prompt design, RAG architectures, function-calling/tool use, context management, and evaluation-driven development.
  • Production engineering discipline: tests, CI/CD, observability, and reliability for production AI systems.
  • Experience with event-driven or streaming systems (CDC, real-time pipelines).
  • 5+ years software engineering, with 3+ years focused on AI/ML in production.
  • Comfortable working embedded in a product team - collaborating daily with domain engineers, product managers, and designers.

Preferred experience:

  • Experience with AWS Bedrock, Azure OpenAI, or GCP Vertex AI (we run on Bedrock with Claude today).
  • Familiarity with MCP (Model Context Protocol) or similar agentic frameworks.
  • Background in anomaly detection, time-series analysis, or statistical signal processing.
  • Experience building confidence scoring/calibration systems for AI outputs.
  • Proficiency in Kotlin or Type Script in addition to Python (our product platform is Kotlin/Type Script; AI platform is Python).
  • History of absorbing work from external partners and improving inherited architectures.

Nice to have:

  • Monte Carlo simulation, optimization, or scheduling systems.
  • Domain experience in portfolio, project, or resource planning.
  • Enterprise SaaS experience (multi-tenancy, compliance, audit trails).
  • Open-source contributions to AI/ML tooling or frameworks.

What we offer:

  • Remote work - work where you do your best thinking.
  • Unlimited vacation.
  • Comprehensive benefits (health, dental, vision).
  • Great office spaces in Canada and Iceland if you prefer.
  • A collaborative, diverse team and high-impact work - you'll be building the intelligence layer for enterprise portfolio management, not adding AI to a CRUD app.
  • Regular social activities, breakfast/snacks, and more.
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