Senior AI/ML Engineer - Tempo Software

About Tempo

With over 30,000 customers, including a third of Fortune 500 companies, Tempo is trusted by organizations across the globe to make their workflows work better.

We create a suite of integrated solutions for time management, resource planning, budget management, roadmapping, program management, reporting and more. Since our beginning in 2007, Tempo has expanded to become the #1 time management add-on for Jira and one of the most trusted names in the Atlassian ecosystem.

About the Role

We’re looking for a Senior AI/ML Engineer who will work at the intersection of LLMs, real-time signal processing, and enterprise decision-making. This is not a research role or an isolated AI team position. You’ll sit alongside domain engineers as you ship production AI systems to enterprise customers.

We are looking for someone who uses AI heavily in their daily work, has built and shipped features powered by LLMs and autonomous agents, and holds strong opinions on what good AI product engineering looks like.

You’ll initially pair with external AI partners to absorb their work and establish patterns for the broader engineering team, ultimately serving as the internal anchor for AI engineering (prompt design, evaluation strategy, model selection, and agent architecture).

What You’ll Do

• Signal & Anomaly Detection: Build statistical and ML-based detectors that identify meaningful patterns in portfolio signals (velocity changes, capacity saturation, dependency risks) from CDC event streams and integrations.
• Insight Synthesis Engine: Develop an LLM-powered correlation engine that transforms raw signals into actionable insights with root causes, confidence scores, and evidence chains.
• Planning Rules Compiler: Design a reliable translation layer between natural language planning rules written by portfolio managers and structured parameters for our Monte Carlo scheduling engine.
• Evaluation & Testing Frameworks: Implement regression suites for prompt changes, A/B testing infrastructure for model updates, and confidence calibration systems.
• MCP Tool Definitions: Create LLM-ready tool specifications (Item Store queries, capacity lookups, scenario simulations) within our production hub-and-spoke MCP architecture.

Who You Are

Must Have

• A track record of shipping LLM-powered features or products to real users.
• Hands-on experience orchestrating agents (multi-step reasoning, tool use, guardrails) using frameworks like LangChain, LlamaIndex, CrewAI, AutoGen, or custom implementations.
• Deep LLM engineering fundamentals: prompt engineering, RAG architectures, function calling/tool use, context management, and evaluation-driven development.
• Production-quality engineering practices: automated testing, code review, CI/CD, and observability.
• Experience with event-driven or streaming data systems (CDC events, real-time pipelines).
• 5+ years of software engineering experience, with 3+ years focused on AI/ML in production systems.
• Ability to work embedded within cross-functional product teams alongside domain engineers, PMs, and designers.

Strongly Preferred

• Experience with AWS Bedrock, Azure OpenAI, or GCP Vertex AI (Tempo currently runs on Bedrock with Claude).
• Working knowledge of MCP (Model Context Protocol) or similar tool-use/agentic frameworks.
• Anomaly detection, time-series analysis, or statistical signal processing.
• Experience building confidence scoring or calibration systems for AI outputs.
• Proficiency in Kotlin or TypeScript alongside Python (platform is Kotlin/TypeScript; AI platform is Python).

Nice to Have

• Background in Monte Carlo simulations, optimization algorithms, or scheduling systems.
• Experience with portfolio management, project management, or resource planning.
• Experience with enterprise SaaS (multi-tenancy, compliance, audit trails).
• Contributions to open-source AI/ML projects.

Benefits

• Remote-first work environment
• Unlimited vacation in most locations
• Health, dental, and vision insurance plus savings plans
• WFH reimbursement and training reimbursement
• Optional in-person meetups and international office travel
• Employee referral program