REMOTE Senior AI/ML Engineer - SaaS

CyberCoders, Inc.; United States; Remote; USD 140,000 - 240,000; Full time

Benefits offered by this job

Remote work

Unlimited vacation

Comprehensive benefits

Office spaces in Canada and Iceland

Collaborative, high-impact team

Social activities

Job summary

CyberCoders, Inc. is seeking a Senior AI/ML Engineer to design, build, and operate AI components that make our platform intelligent and trustworthy.

You will implement signal detection, an LLM-powered correlation engine, and a planning rules compiler for a Monte Carlo scheduling system, in a fast-growing product team. You’ll bring 5+ years of software engineering with 3+ years in production AI, hands-on agent orchestration, and strong fundamentals in prompt design, RAG, and evaluation-driven

Qualifications

• Proven track record shipping LLM-powered features or products used by real users.
• Hands-on experience orchestrating agents (multi-step reasoning, tool use, autonomous action with guardrails).
• Deep LLM engineering fundamentals: prompt design, RAG, function-calling, context management, evaluation-driven development.
• Production engineering discipline: tests, CI/CD, observability, reliability for production AI systems.
• Experience with event-driven or streaming systems (CDC, real-time pipelines).
• 5+ years software engineering, 3+ years AI/ML in production.
• Comfortable working embedded in a product team with domain engineers, PMs, designers.

Responsibilities

• Design, build, and operate AI components that make our platform intelligent and trustworthy.
• Signal & anomaly detection in CDC event streams and external integrations.
• Insight synthesis engine: LLM-powered correlation with root causes, confidence scores, evidence chains.
• Planning rules compiler: translate natural-language rules into deterministic Monte Carlo scheduling parameters.
• Evaluation & testing frameworks: regression suites, A/B testing, calibration pipelines.
• Define LLM-ready tool specs for runtime tool use in a hub-and-spoke agent architecture.

Skills

LLM engineering

Agent orchestration

Production AI

CI/CD

Observability

Event-driven

Kotlin

TypeScript

Python

Multi-tenant SaaS

Tools

LangChain

LlamaIndex

AutoGen

CrewAI

AWS Bedrock

Azure OpenAI

Vertex AI

Job description

Title: Senior AI/ML Engineer
Reports to: VP of Engineering, Operations
Location: Remote
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 app
• Regular social activities, breakfast/snacks, and more