AI Orchestration Engineer

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.

You Will Build

• 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

You Will Deliver:

Engineering & Architecture

• 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

Integration & Platform

• 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

Quality & Best Practices

• 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

Collaboration & Enablement

• 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

Why RecordPoint:

• Fast-growth Australian-owned company
• Flexible work environment and a strong focus on work-life harmony
• Innovation is our way of life
• Personal Development budget for all staff
• Access to Employee Stock Ownership Plan
• A brilliant graduate program that provides both mentoring and growth opportunities for all
• Work on a product that makes a real social-good impact on the world
• Global opportunities!

Required Qualifications

• 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