Senior AI/ML Engineer
Cybercoders
Job Description
Job Description
Senior AI/ML Engineer
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 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 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 app.
- Regular social activities, breakfast/snacks, and more .
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