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    Job · 22478485

    SCIKIQ logo

    Solution Architect - AI & AI Governance

    SCIKIQ · Gurugram · onsite · Posted 1d ago

    Not disclosed10–15 yrsfulltimeSourced fromFoundit

    About a minute. You'll make an account on the way through.

    About this role

    Job Description: Solution Architect - AI & AI Governance

    Company: SCIKIQ Data Private Limited

    Type - Product & Services

    Location: Gurugram, Sector 32

    Work Mode: Work from Office (5 days a week)

    Experience: 10+ Years (3+ in AI / GenAI)

    Employment Type: Full-time

    About SCIKIQ

    SCIKIQ is an AI-native, no-code data platform from Gurugram. Enterprises use it to connect their data ,govern it (catalog, lineage, data quality, policies) and use it through dashboards, data products and AI copilots driving relevant use cases.

    The Role

    You design the AI solutions our customers run on SCIKIQ - conversational analytics, copilots, GenAI apps and AI agents - on top of governed data. You also set up the AI governance that keeps them accurate, safe and auditable.

    What You Will Do

    • AI solutions: Design and deliver natural-language query, copilots, GenAI apps and AI agents on SCIKIQ for enterprise customers.
    • AI context layer: Connect glossary, semantic models, lineage and access rules to prompts, RAG and agents so answers are correct and permission-aware.
    • AI governance: Set up use-case risk classification, guardrails (PII out of prompts, output checks), human-in-the-loop, evaluation / hallucination testing, monitoring and audit trails.
    • Data governance for AI: Use SCIKIQ catalog, lineage, quality and trust scores to decide which data is safe for AI and show the evidence.
    • Delivery: Run workshops, pick the right LLMs and patterns, build POCs, write solution designs and take solutions to production.
    • Pre-sales: Demo AI capabilities and explain AI governance to CDOs, CISOs and compliance teams in plain language.
    • Work with the DWH architect: Agree on data contracts, definitions and access rules with the DWH Solution Architect. Solve use cases together.

    Must have

    • 10 - 15 years in data warehousing and ML architecture experience
    • 3+ years delivering GenAI solutions for enterprises.
    • Hands-on with LLM apps: Prompts, RAG, embeddings / vector search, tool calling, agent frameworks, LLM evaluation.
    • Working knowledge of ML basics and MLOps.
    • Strong Python
    • Good SQL required and should be comfortable with warehouses / lakehouses.
    • Hands-on AI governance: Risk assessment, guardrails, monitoring, explainability, audit evidence
    • Understands Data governance (catalog, lineage, quality, access) and AI security (data leakage, prompt injection).
    • Explains AI and its risks simply to business, risk and compliance teams. Comfortable on the ground with customers. Should have very good communication skill

    Sourced from foundit

    Skills

    accessQualityRetrieval Augmented Generationvector searchMLOpsMonitoringCatalogai governanceEmbeddingsai securityRisk AssessmentLLM Evaluationagent frameworkstool callingguardrailsprompt injectiondata leakageexplainabilitypromptslineagePythonML basicsLLM appsSQLData Governanceaudit evidence

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