AI Platform Engineer

Serving the People Who Serve the People

Granicus is driven by the excitement of building, implementing, and maintaining technology that is transforming the Govtech industry by bringing governments and its constituents together. We are on a mission to support our customers with meeting the needs of their communities and implementing our technology in ways that are equitable and inclusive. Granicus has consistently appeared on the GovTech 100 list over the past 5 years and has been recognized as the best companies to work on BuiltIn.

Over the last 25 years, we have served 5,500 federal, state, and local government agencies and more than 300 million citizen subscribers power an unmatched Subscriber Network that use our digital solutions to make the world a better place. With comprehensive cloud-based solutions for communications, government website design, meeting and agenda management software, records management, and digital services, Granicus empowers stronger relationships between government and residents across the U.S., U.K., Australia, New Zealand, and Canada. By simplifying interactions with residents, while disseminating critical information, Granicus brings governments closer to the people they serve—driving meaningful change for communities around the globe.

Want to know more? See more of what we do here.

The RevOps AI Engineer designs, builds, evaluates, and operates AI-powered systems that support revenue workflows across Sales, Marketing, Customer Success, Support, and GTM Operations. This role is responsible for turning AI designs and requirements into production-grade, measurable, and reliable AI solutions that deliver demonstrable business impact.

This role sits at the intersection of AI engineering, Revenue Operations, and systems delivery. The RevOps AI Engineer partners closely with RevOps AI Product Management, AI Solutions Architects, and GTM stakeholders to implement AI agents, workflows, and automation that are grounded in trusted data, governed content pipelines, rigorous evaluation frameworks, and continuous post-launch measurement.

This role is ideal for an engineer who values reliability, quality, and outcomes over experimentation, and who can operate AI systems as durable operational capabilities embedded in core revenue workflows.

Essential Functions

AI Engineering & Implementation with 3+ years of experience 

• Build, test, deploy, and operate AI-powered workflows, agents, and automations embedded within core RevOps systems (e.g., Salesforce, Microsoft 365, Azure AI & Copilot surfaces).
• Implement prompt logic, orchestration flows, tool calling, and context-retrieval mechanisms for LLM-based systems.
• Partner with AI Solutions Architects to translate approved solution designs into scalable, maintainable, and secure implementations.
• Ensure AI solutions are production-ready, observable, resilient, and aligned to defined business outcomes.
• Support iterative enhancement cycles based on measured performance and stakeholder feedback.

LLM Evaluation & Quality Frameworks

• Design, implement, and maintain LLM evaluation frameworks that assess accuracy, relevance, consistency, and outcome impact.
• Implement offline evaluations using curated test datasets, golden answers, and regression test suites.
• Implement online evaluations, including user feedback loops, telemetry, and behavioral usage signals.
• Define evaluation thresholds, quality gates, and readiness criteria required for launch and scale.
• Partner with Product and RevOps leadership to ensure evaluation results inform release decisions, prioritization, and iteration.

Hallucination Reduction & Reliability

• Design and implement hallucination-reduction strategies in production systems, including:
• Retrieval-augmented generation (RAG) patterns
• Context filtering, grounding, and citation techniques
• Guardrails, validation checks, and response constraints
• Continuously monitor AI outputs, confidence signals, and failure modes in live environments.
• Investigate root causes of incorrect or low-confidence outputs and implement corrective improvements.
• Contribute to shared standards for explainability, traceability, and user trust in AI-assisted workflows.

Metrics, Telemetry & Impact Measurement

• Define and instrument metrics for AI systems, focused on outcomes rather than feature delivery.
• Track model and workflow performance across quality, adoption, latency, and reliability dimensions.
• Build telemetry that connects AI usage to downstream operational and revenue impact (e.g., cycle time reduction, capacity unlocked, risk reduced).
• Partner with analytics teams to ensure AI metrics are trustworthy, interpretable, and consistently applied across initiatives.
• Support post-launch measurement to validate realized impact within defined timeframes.

Data, Context & Governance

• Implement context pipelines that draw from structured data, documents, and governed knowledge assets.
• Support enterprise content readiness by consuming content through standardized pipelines rather than ad hoc document handling.
• Enforce data quality, access controls, grounding standards, and versioning in AI workflows.
• Support governance requirements including documentation, testing, auditability, and change management.
• Ensure compliance with privacy, security, and responsible AI guidelines across all implementations.

Cross-Functional Collaboration

• Work closely with RevOps AI Product Managers to understand intent, success criteria, adoption goals, and delivery priorities.
• Collaborate with AI Solutions Architects, Systems teams, and GTM stakeholders to ensure implementations align with real-world workflows.
• Support enablement and adoption efforts by improving system reliability, explainability, and usability.
• Participate in reviews and retrospectives to continuously improve delivery quality and operational impact.

Knowledge / Skills / Abilities

• Strong software, data, or automation engineering background with experience operating production systems.
• Hands-on experience building and operating LLM-based workflows and agents.
• Demonstrated experience designing and operating LLM evaluation frameworks.
• Familiarity with:
• Offline evaluations using test datasets and regression frameworks
• Online evaluations using user feedback, telemetry, and behavioral signals
• Experience reducing hallucinations in production AI systems using grounding, validation, and guardrails.
• Comfort defining metrics and success measures, not just implementing features.
• Strong understanding of retrieval-augmented generation (RAG), prompt design, and context engineering.
• Familiarity with RevOps systems such as CRM, GTM tooling, and workflow platforms.
• Strong analytical mindset with the ability to debug complex AI system behavior.
• Clear written and verbal communication skills across technical and non-technical audiences.

Experience / Credentials

• Experience in AI engineering, applied machine learning, automation engineering, or related roles.
• Experience deploying AI or automation systems into production environments.
• Experience working with cross-functional product, operations, and systems teams.
• Experience supporting AI quality, reliability, and evaluation in live systems.

Other Job Info

• Role operates in a highly cross-functional environment supporting end-to-end revenue operations.
• Focused on production reliability, measurable impact, and continuous improvement of AI systems.

• Deliver AI-powered solutions that improve how Sales, Marketing, Customer Success, and Revenue Operations teams work by reducing manual effort, accelerating execution, and improving decision quality.
• Build, deploy, and support production-grade AI agents, workflows, and automations integrated with platforms such as Salesforce, Microsoft 365, Azure AI, and Copilot.
• Contribute to AI systems that are accurate, reliable, secure, and measurable, ensuring users can trust AI-generated outputs in critical business processes.
• Develop evaluation and testing capabilities that improve solution quality and help prevent regressions as systems evolve.
• Help reduce hallucinations and improve response quality through grounding, retrieval, validation, and guardrail techniques.
• Instrument telemetry and measurement frameworks that connect AI usage to operational and revenue outcomes.
• Partner with Product Managers, Architects, and GTM stakeholders to translate business requirements into scalable AI solutions that deliver measurable value.
• Contribute to the continuous improvement of Granicus' AI capabilities through experimentation, operational excellence, and ongoing optimization after launch.

A passion for building AI-powered products that solve real business problems rather than technology for technology's sake.

Experience developing software, automation, data, or AI solutions that operate in production environments. [JD for Rev...m Engineer | Word]

Hands-on experience with LLMs, AI agents, prompt engineering, orchestration frameworks, retrieval-augmented generation (RAG), or workflow automation. [JD for Rev...m Engineer | Word], [JD for Rev...m Engineer | Word]

Strong curiosity and a desire to understand why AI systems succeed, fail, or behave unexpectedly. [JD for Rev...m Engineer | Word], [JD for Rev...m Engineer | Word]

An analytical mindset and enjoyment of debugging complex technical problems using data and evidence. [JD for Rev...m Engineer | Word]

Comfort working across technical and business teams to translate requirements into practical solutions. [JD for Rev...m Engineer | Word]

A quality-first approach with an appreciation for testing, reliability, observability, security, and governance. [JD for Rev...m Engineer | Word]

Strong communication skills and the ability to explain complex concepts to both technical and non-technical audiences. [JD for Rev...m Engineer | Word]

A desire to help shape how AI transforms revenue operations, customer engagement, and go-to-market workflows at scale. [JD for Rev...m Engineer | Word], [JD for Rev...m Engineer | Word]

Don’t have all the skills/experience mentioned above? At Granicus, we are trying to build diverse, inclusive teams. We do not have degree requirements for most of our roles. If you don’t meet every requirement above but are excited to learn more, we encourage you to apply. We might just be able to find another role that could be a perfect fit!

Security and Privacy Requirements

• Responsible for Granicus information security by appropriately preserving the Confidentiality, Integrity, and Availability (CIA) of Granicus information assets in accordance with the company's information security program.
• Responsible for ensuring the data privacy of our employees and customers, their data, as well as taking all required privacy training in a timely manner, in accordance with company policies.

The Team

• We are a remote-first company with a globally distributed workforce across the United States, Canada, United Kingdom, India, Armenia, Australia, and New Zealand.

The Culture

• At Granicus, we are building a transparent, inclusive, and safe space for everyone who wants to be
  a part of our journey.
• A few culture highlights include – Employee Resource Groups to encourage diverse voices
• Coffee with Mark sessions – Our employees get to interact with our CEO on very important and
  sometimes difficult issues ranging from mental health to work-life balance and current affairs.
• Microsoft Teams communities focused on wellness, art, furbabies, family, parenting, and more.
• We bring in special guests from time to time to discuss issues that impact our employee
  population
  
  

The Impact

• We are proud to serve dynamic organizations around the globe that use our digital solutions to make the world a better place — quite literally. We have so many powerful success stories that illustrate how our solutions are impacting the world. See more of our impact here.