AI Knowledge & Execution Grounding Specialist

Bangalore - India

Monthly Salary: Not Disclosed

Experience Required: 04-05years

Posted on: 2 hours ago

Vacancies: 1 Vacancy

Job Summary

Job Title: AI Knowledge & Execution Grounding Specialist

This person is the architect of the "Ground Truth" that ensures the AIs advice is high-velocity and hyper-practical.

Role Summary
We are looking for a Knowledge & Execution Grounding Specialist to ensure our AI provides high-growth SMBs with accurate "ready-to-execute" strategies. You will sit in the Knowledge Team and act as the bridge between our proprietary growth frameworks and the Technical/Product teams. Your mission is to structure our "execution blueprints"templates SOPs financial models and growth hacksso the AI retrieves and applies them with 100% factual accuracy. You arent just managing content; you are managing the logic of execution.

Key Responsibilities

Content Engineering for RAG: Audit and restructure unstructured data (PDFs wikis transcripts) into "AI-ready" formats by optimizing semantic chunking and hierarchical data decoding.
Blueprint Deconstruction: Break down complex growth strategies (e.g. "Scaling Sales Teams" or "Inventory Management") into modular machine-readable blocks that the AI can accurately recompose for a users specific business size and industry.
Operational Metadata Design: Develop a tagging system that accounts for execution constraints. (e.g. Tagging advice by Capital Required Team Size or Tech Stack so the AI doesnt suggest a solution the SMB cannot execute).
RAG Strategy Liaison: Partner with the Tech team to define retrieval logic. You decide which "Playbooks" are the primary sources for specific user intents to prevent the AI from giving "generic" internet advice.
Execution Auditing: Conduct "Stress Tests" on AI outputs. If a business owner asks "How do I set up a CRM" you ensure the AI pulls from our verified partner stack and doesnt hallucinate a random software.
Grounding Quality Assurance: Regularly audit AI outputs for hallucinations and "unfounded" claims. Identify if errors stem from poor source data or technical retrieval failures.
Contextual Guardrails: Help refine the "Safety Logic" for the AI. If an SMB is in a pre-revenue stage you ensure the grounding layer prevents the AI from suggesting high-burn growth strategies.

Required Experience & Skills

35 Years Experience: Ideally in Management Consulting Operations or Business Analysis within the SMB/Startup ecosystem.
AI Grounding Literacy: You must understand how Retrieval-Augmented Generation (RAG) worksspecifically how "chunking" and "vector embeddings" impact the quality of a business recommendation.
Process Mapping: Proficiency in tools like Miro LucidChart or Notion to map out "Execution Workflows" before they are fed into the AI.
Technical Familiarity & Specific AI Tooling: While this is a Knowledge Team role you will use JSON YAML and SQL as the instructional languages to define how our AI orchestration tools (LlamaIndex or LangChain) interact with our proprietary growth content. You will not write application code but you will be responsible for structuring our execution blueprints into these formats so the AI can filter prioritize and retrieve the exact right action step for an SMBs specific context (e.g. industry team size or revenue stage) without hallucinating.
The "Scrappy" Mindset: A builder who can manually audit a 50-step growth plan and identify exactly where the AI lost the "logic" of the execution.

Required Skills:

Role Summary We are looking for a Knowledge & Execution Grounding Specialist to ensure our AI provides high-growth SMBs with accurate ready-to-execute strategies. You will sit in the Knowledge Team and act as the bridge between our proprietary growth frameworks and the Technical/Product teams. Your mission is to structure our execution blueprintstemplates SOPs financial models and growth hacksso the AI retrieves and applies them with 100% factual accuracy. You arent just managing content; you are managing the logic of execution. Key Responsibilities Content Engineering for RAG: Audit and restructure unstructured data (PDFs wikis transcripts) into AI-ready formats by optimizing semantic chunking and hierarchical data decoding. Blueprint Deconstruction: Break down complex growth strategies (e.g. Scaling Sales Teams or Inventory Management) into modular machine-readable blocks that the AI can accurately recompose for a users specific business size and industry. Operational Metadata Design: Develop a tagging system that accounts for execution constraints. (e.g. Tagging advice by Capital Required Team Size or Tech Stack so the AI doesnt suggest a solution the SMB cannot execute). RAG Strategy Liaison: Partner with the Tech team to define retrieval logic. You decide which Playbooks are the primary sources for specific user intents to prevent the AI from giving generic internet advice. Execution Auditing: Conduct Stress Tests on AI outputs. If a business owner asks How do I set up a CRM you ensure the AI pulls from our verified partner stack and doesnt hallucinate a random software. Grounding Quality Assurance: Regularly audit AI outputs for hallucinations and unfounded claims. Identify if errors stem from poor source data or technical retrieval failures. Contextual Guardrails: Help refine the Safety Logic for the AI. If an SMB is in a pre-revenue stage you ensure the grounding layer prevents the AI from suggesting high-burn growth strategies.

Required Education:

MBA

Job Title: AI Knowledge & Execution Grounding SpecialistThis person is the architect of the "Ground Truth" that ensures the AIs advice is high-velocity and hyper-practical.Role Summary We are looking for a Knowledge & Execution Grounding Specialist to ensure our AI provides high-growth SMBs with acc...

Job Title: AI Knowledge & Execution Grounding Specialist

This person is the architect of the "Ground Truth" that ensures the AIs advice is high-velocity and hyper-practical.

Key Responsibilities

Content Engineering for RAG: Audit and restructure unstructured data (PDFs wikis transcripts) into "AI-ready" formats by optimizing semantic chunking and hierarchical data decoding.
Blueprint Deconstruction: Break down complex growth strategies (e.g. "Scaling Sales Teams" or "Inventory Management") into modular machine-readable blocks that the AI can accurately recompose for a users specific business size and industry.
Operational Metadata Design: Develop a tagging system that accounts for execution constraints. (e.g. Tagging advice by Capital Required Team Size or Tech Stack so the AI doesnt suggest a solution the SMB cannot execute).
RAG Strategy Liaison: Partner with the Tech team to define retrieval logic. You decide which "Playbooks" are the primary sources for specific user intents to prevent the AI from giving "generic" internet advice.
Execution Auditing: Conduct "Stress Tests" on AI outputs. If a business owner asks "How do I set up a CRM" you ensure the AI pulls from our verified partner stack and doesnt hallucinate a random software.
Grounding Quality Assurance: Regularly audit AI outputs for hallucinations and "unfounded" claims. Identify if errors stem from poor source data or technical retrieval failures.
Contextual Guardrails: Help refine the "Safety Logic" for the AI. If an SMB is in a pre-revenue stage you ensure the grounding layer prevents the AI from suggesting high-burn growth strategies.

Required Experience & Skills

35 Years Experience: Ideally in Management Consulting Operations or Business Analysis within the SMB/Startup ecosystem.
AI Grounding Literacy: You must understand how Retrieval-Augmented Generation (RAG) worksspecifically how "chunking" and "vector embeddings" impact the quality of a business recommendation.
Process Mapping: Proficiency in tools like Miro LucidChart or Notion to map out "Execution Workflows" before they are fed into the AI.
Technical Familiarity & Specific AI Tooling: While this is a Knowledge Team role you will use JSON YAML and SQL as the instructional languages to define how our AI orchestration tools (LlamaIndex or LangChain) interact with our proprietary growth content. You will not write application code but you will be responsible for structuring our execution blueprints into these formats so the AI can filter prioritize and retrieve the exact right action step for an SMBs specific context (e.g. industry team size or revenue stage) without hallucinating.
The "Scrappy" Mindset: A builder who can manually audit a 50-step growth plan and identify exactly where the AI lost the "logic" of the execution.