REMOTE Senior AI/ML Engineer - SaaS

Title: Senior AI/ML Engineer

Reports to: VP of Engineering, Operations

Location: Remote (MUST BE LOCATED IN CT/ET) Primary stack: Python, Kotlin, TypeScript, AWS

AI 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 doing

You 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 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) - 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 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 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 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 a…