AI Solutions Engineer

🔥 31 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Granicus

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1999

🏛️ Government

☁️ SaaS

📋 Compliance

Government • SaaS • Compliance

Granicus is a company focused on transforming the way governments interact with their constituents through digital services and technology solutions. It provides the Government Experience Cloud to improve service delivery, community engagement, and operational efficiency across local, state, and federal governments. Granicus offers tools for agenda and meeting management, digital communication and engagement, public records management, and more, all designed to enhance customer experience and foster transparent and equitable interactions between governments and the people they serve.

📋 Description

• Build, test, deploy, and operate AI-powered workflows, agents, and automations within Salesforce, Microsoft 365, Azure AI, and Copilot • Implement prompt logic, orchestration flows, tool calling, and context retrieval for LLM-based systems • Translate approved AI solution designs into scalable, maintainable, and secure implementations • Ensure AI solutions are production-ready, observable, resilient, and aligned with business outcomes • Design and maintain LLM evaluation frameworks for accuracy, relevance, consistency, and impact • Implement offline and online evaluations using test datasets, golden answers, regression suites, feedback loops, telemetry, and behavioral signals • Define evaluation thresholds, quality gates, and launch-readiness criteria • Design hallucination-reduction strategies using RAG, context filtering, grounding, citations, guardrails, validation, and response constraints • Monitor AI outputs, confidence signals, and failure modes in live environments • Investigate incorrect or low-confidence outputs and implement corrective improvements • Define and instrument metrics covering quality, adoption, latency, reliability, and operational or revenue impact • Build telemetry connecting AI usage to cycle-time reduction, capacity unlocked, and risk reduction • 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 Product Managers, AI Solutions Architects, Systems teams, analytics teams, and GTM stakeholders • Support enablement, adoption, reviews, retrospectives, and continuous post-launch improvement

🎯 Requirements

• 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 • Experience with offline evaluations using test datasets and regression frameworks • Experience with online evaluations using user feedback, telemetry, and behavioral signals • Experience reducing hallucinations in production AI systems using grounding, validation, and guardrails • Experience defining metrics and success measures • Strong understanding of retrieval-augmented generation (RAG), prompt design, and context engineering • Familiarity with CRM, GTM tooling, and workflow platforms • Strong analytical and debugging abilities for complex AI system behavior • Clear written and verbal communication skills across technical and non-technical audiences • 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 • Experience with LLMs, AI agents, prompt engineering, orchestration frameworks, retrieval-augmented generation (RAG), or workflow automation • Quality-first approach incorporating testing, reliability, observability, security, and governance • No degree required; Granicus states it does not have degree requirements for most roles

🏖️ Benefits

• Remote-first work environment • Employee Resource Groups • Coffee with Mark sessions with the CEO • Microsoft Teams communities focused on wellness, art, pets, family, and parenting • Special guest sessions addressing issues impacting employees