RecordPoint is seeking an AI Orchestration Engineer in Melbourne to design and implement a continuously operating, agentic GTM operating system that monitors signals, reasons about opportunities, and proactively supports sales execution. You will build a scalable multi‑agent orchestration framework, design signal pipelines from Salesforce, Microsoft Teams, internal knowledge bases and external feeds, and develop reasoning components for opportunity detection with explainability and source attribution. You’ll own production‑grade integrations with Salesforce and Teams, enforce governance by design with permission‑aware data access, audit trails and human approval workflows, and champion maintainable code with robust testing and CI/CD. Required: 5+ years backend or platform engineering, hands‑on AI/LLM workflows, proficiency in Python, TypeScript/Go or similar, cloud‑native patterns, secure auth and data pipelines. Apply via the button with your CV; police background check is required; no recruiters.
RecordPoint is building a continuously operating, agentic Go-To-Market (GTM) operating system that monitors signals, reasons about opportunities, and proactively assists sales execution. As an AI Orchestration Engineer, you will design and implement the underlying multi-agent orchestration framework, integrations, and governed AI capabilities that make this possible. You will write repeatable, maintainable code; establish best practices with your manager; and enable a broader internal community of AI Orchestration Engineers through 1:1 training, peer mentoring, workshops, and showcases.
Agentic orchestration framework supporting proactive, verticalized GTM personas (e.g., Public Sector, FSI, Healthcare)
Signal collection pipelines from external and internal sources (news, regulations, competitor activity, Salesforce, product/roadmap systems, Teams, analytics)
Reasoning and decision components for opportunity detection, account prioritization, and next-best actions with explainability, source attribution, and confidence
Content generation services for tailored messaging, executive briefs, sales presentations, and demo recommendations
Production-grade integrations with Salesforce, Microsoft Teams, internal knowledge bases, and external intelligence feeds
Governed AI foundations: permission-aware data access, audit trails, human approval workflows, model/prompt governance, and safe action boundaries
Design modular, reusable agentic components and orchestration patterns that scale across GTM and future operational domains
Implement robust data ingestion, normalization, correlation, and opportunity scoring pipelines
Build vertical specializations via configurable context, taxonomies, and policy-aware prompts
Deliver observability, telemetry, and reliability tooling for always-on, proactive agents
Embed explainability and traceability into recommendations, including evidence linking and rationale
Own end-to-end integrations with Salesforce, Microsoft Teams, product delivery and roadmap systems, analytics platforms, and external signal sources
Establish extensible connector patterns, error handling, and backoff/queueing strategies for scale
Partner with Security and Data teams to enforce governance-by-design
Champion maintainable code: clear module boundaries, testable units, typed interfaces, and robust CI/CD
Define coding standards, review guidelines, and documentation practices with your manager
Instrument performance budgets and SLAs for agent latency, throughput, and uptime
Work closely with the GTM Team to translate market and sales requirements into agent capabilities tied to measurable outcomes
Run internal workshops, peer mentoring, and 1:1 training to upskill engineers and domain experts into AI Orchestration contributors
Create showcases and reference implementations that accelerate adoption across RecordPoint
5+ years of backend or platform engineering with a strong track record of building production systems that are maintainable, well-tested, and observable
Hands-on experience with AI/LLM-powered applications or autonomous/agentic workflows (tools, planners, memory, retrieval, or function calling)
Proficiency in a modern language for services/orchestration (e.g., Python, TypeScript/Node.js, or Go) and familiarity with cloud-native patterns (containers, queues, event streams)
Experience integrating enterprise systems (e.g., Salesforce, Microsoft Graph/Teams, data warehouses, analytics) with secure auth and permission models
Data engineering fundamentals: schema design, normalization, enrichment, scoring models, and pipeline reliability
Strong focus on code quality: automated testing, CI/CD, code reviews, documentation, and architectural decision records
Security-first mindset: least privilege, PII handling, auditability, and compliance-aware design