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Job Post Details
Job details
Job type
- Full-time
Location
Full job description
About the role:
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
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Agentic orchestration framework supporting proactive, verticalized GTM personas (e.g., Public Sector, FSI, Healthcare)
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Signal collection pipelines from external and internal sources (news, regulations, competitor activity, Salesforce, product/roadmap systems, Teams, analytics)
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Reasoning and decision components for opportunity detection, account prioritization, and next-best actions with explainability, source attribution, and confidence
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Content generation services for tailored messaging, executive briefs, sales presentations, and demo recommendations
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Production-grade integrations with Salesforce, Microsoft Teams, internal knowledge bases, and external intelligence feeds
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Governed AI foundations: permission-aware data access, audit trails, human approval workflows, model/prompt governance, and safe action boundaries
You Will Deliver:
Engineering & Architecture
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Design modular, reusable agentic components and orchestration patterns that scale across GTM and future operational domains
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Implement robust data ingestion, normalization, correlation, and opportunity scoring pipelines
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Build vertical specializations via configurable context, taxonomies, and policy-aware prompts
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Deliver observability, telemetry, and reliability tooling for always-on, proactive agents
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Embed explainability and traceability into recommendations, including evidence linking and rationale
Integration & Platform
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Own end-to-end integrations with Salesforce, Microsoft Teams, product delivery and roadmap systems, analytics platforms, and external signal sources
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Establish extensible connector patterns, error handling, and backoff/queueing strategies for scale
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Partner with Security and Data teams to enforce governance-by-design
Quality & Best Practices
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Champion maintainable code: clear module boundaries, testable units, typed interfaces, and robust CI/CD
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Define coding standards, review guidelines, and documentation practices with your manager
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Instrument performance budgets and SLAs for agent latency, throughput, and uptime
Collaboration & Enablement
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Work closely with the GTM Team to translate market and sales requirements into agent capabilities tied to measurable outcomes
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Run internal workshops, peer mentoring, and 1:1 training to upskill engineers and domain experts into AI Orchestration contributors
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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
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5+ years of backend or platform engineering with a strong track record of building production systems that are maintainable, well-tested, and observable
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Hands-on experience with AI/LLM-powered applications or autonomous/agentic workflows (tools, planners, memory, retrieval, or function calling)
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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)
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Experience integrating enterprise systems (e.g., Salesforce, Microsoft Graph/Teams, data warehouses, analytics) with secure auth and permission models
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Data engineering fundamentals: schema design, normalization, enrichment, scoring models, and pipeline reliability
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Strong focus on code quality: automated testing, CI/CD, code reviews, documentation, and architectural decision records
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Security-first mindset: least privilege, PII handling, auditability, and compliance-aware design
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.