Senior AI/ML Engineer

Title:

Senior AI/ML EngineerLocation:

Remote (EST/EDT)

• USA OR CANADASalary:

  $180K-210k/year CANPrimary stack: Python, Kotlin, TypeScript, AWSAI focus: LLMs, agent orchestration, RAG architectures, evaluation pipelines (Claude/Bedrock integration)Founded in 2006, we're one of the largest app vendors (300+ employees) supporting 30,000+ customers worldwide
• including Amazon, Disney, Dell, PayPal, and Hulu. In fact, 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 doingYou will design, build, and operate the AI components that make our platform intelligent and trustworthy:

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 youProven 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)

• LangChain, LlamaIndex, AutoGen, 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 experienceExperience 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 TypeScript in addition to Python (our product platform is Kotlin/TypeScript; AI platform is Python).History of absorbing work from external partners and improving inherited architectures.

Nice to haveMonte 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 offerRemote 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.