AI Platform Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Develop, test, deploy, and manage AI-driven workflows, agents, and automations within RevOps systems such as Salesforce, Microsoft 365, Azure AI, and Copilot.

• Implement prompt logic, orchestration flows, tool invocation, and context retrieval for systems based on large language models (LLMs).

• Convert approved AI solution designs into scalable, maintainable, and secure implementations.

• Ensure that AI solutions are production-ready, observable, resilient, and aligned with business objectives.

• Create and maintain evaluation frameworks for LLMs that assess accuracy, relevance, consistency, and impact on outcomes.

• Conduct offline evaluations utilizing curated datasets, golden answers, and regression testing suites.

• Execute online evaluations leveraging user feedback loops, telemetry, and behavioral usage signals.

• Establish evaluation thresholds, quality gates, and criteria for launch readiness.

• Design and implement strategies to reduce hallucinations using retrieval-augmented generation (RAG), context filtering, grounding, citations, guardrails, validation checks, and response constraints.

• Monitor AI outputs, confidence indicators, and failure modes in live environments.

• Investigate the root causes of inaccurate or low-confidence outputs and implement corrective measures.

• Define and instrument metrics related to quality, adoption, latency, reliability, and operational or revenue impact.

• Develop telemetry that connects AI usage to downstream operational and revenue outcomes.

• Implement context pipelines using structured data, documents, and governed knowledge assets.

• Enforce data quality, access controls, grounding standards, and versioning.

• Support documentation, testing, auditability, change management, privacy, security, and responsible AI requirements.

• Collaborate with RevOps AI Product Managers, AI Solutions Architects, Systems teams, analytics teams, and go-to-market (GTM) stakeholders.

• Assist in enablement, adoption, reviews, retrospectives, and continual post-launch improvement.

⛳️ Requirements

• Over 3 years of experience in AI engineering and implementation.

• Strong background in software, data, or automation engineering with experience in operating production systems.

• Practical experience in building and managing LLM-based workflows and agents.

• Proven experience in designing and operating LLM evaluation frameworks.

• Knowledge of offline evaluations using test datasets and regression frameworks.

• Understanding of online evaluations utilizing user feedback, telemetry, and behavioral signals.

• Experience in minimizing hallucinations in production AI systems through grounding, validation, and guardrails.

• Strong grasp of retrieval-augmented generation (RAG), prompt design, and context engineering.

• Familiarity with RevOps systems such as CRM, GTM tools, and workflow platforms.

• Excellent analytical skills and ability to debug complex AI system behavior.

• Strong written and verbal communication skills suited for both technical and non-technical audiences.

• Experience in deploying AI or automation systems into production settings.

• Background in collaborating with cross-functional product, operations, and systems teams.

• Experience in supporting AI quality, reliability, and evaluation in live systems.

• Responsible for maintaining the confidentiality, integrity, and availability of company information assets.

• Accountable for ensuring data privacy and completing necessary privacy training.

• No degree requirement specified; Granicus does not mandate degrees for most roles.

🏝️ Benefits

• Remote-first company culture.

• Employee Resource Groups that promote diverse perspectives.

• Opportunity for "Coffee with Mark" sessions with the CEO.

• Microsoft Teams communities focused on wellness, art, pets, family, parenting, and more.

• Special guest sessions discussing topics relevant to employees.