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.

• 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