Business Analyst (AI)
CV-LibraryLondonpermanentPosted: 11 June 2026
Apply NowBusiness Analyst within AI needed. We are seeking a forward-thinking Business Analyst. You will not just document legacy requirements. You will design the logical guardrails, metrics, and workflows for autonomous AI agents. You will act as the vital bridge between complex enterprise processes and our AI engineering teams.
Key Responsibilities
1. Workflow Orchestration & Deconstruction
* Deconstruct workflows: Break down complex human processes into structured agent instructions.
* Map state transitions: Outline the iterative "Observe, Think, Act" loops for AI agents.
* Define guardrails: Establish data requirements, exceptions, and human-in-the-loop checkpoints.
2. Pipeline & Value Management
* Qualify use cases: Evaluate enterprise bottlenecks to qualify agentic automation opportunities.
* Manage pipelines: Prioritize the high-value agentic AI transformation roadmap.
* Design validation metrics: Create framework tracking metrics to monitor agent performance.
3. Cross-Functional Collaboration
* Translate requirements: Turn business user needs into precise prompts, system specs, and tool-calling logics.
* Facilitate workshops: Lead discovery sessions with technical engineers and non-technical stakeholders.
Required Skills & Experience
Technical Knowledge
* Agentic Frameworks: Basic knowledge of orchestration ecosystems like LangChain, AutoGen, or CrewAI.
* LLM Foundations: Strong grasp of Large Language Models, prompt engineering, and semantic memory patterns.
* Tool-Use Integration: Clear understanding of function calling, data pipelines, and external API connectors.
Business Analysis Expertise
* Agile Frameworks: Proven success working inside Agile or Scrum software development lifecycles.
* Process Mapping: Mastery of decomposition techniques, data rules, and hand-off mapping.
* Data Fluency: Ability to run analytical assessments and query data to validate agent integrity.
Soft Skills
* Constructive Skepticism: Ability to challenge status-quo enterprise assumptions.
* Ambiguity Handling: Comfort with exploring fluid, evolving AI product definitions
Key Responsibilities
1. Workflow Orchestration & Deconstruction
* Deconstruct workflows: Break down complex human processes into structured agent instructions.
* Map state transitions: Outline the iterative "Observe, Think, Act" loops for AI agents.
* Define guardrails: Establish data requirements, exceptions, and human-in-the-loop checkpoints.
2. Pipeline & Value Management
* Qualify use cases: Evaluate enterprise bottlenecks to qualify agentic automation opportunities.
* Manage pipelines: Prioritize the high-value agentic AI transformation roadmap.
* Design validation metrics: Create framework tracking metrics to monitor agent performance.
3. Cross-Functional Collaboration
* Translate requirements: Turn business user needs into precise prompts, system specs, and tool-calling logics.
* Facilitate workshops: Lead discovery sessions with technical engineers and non-technical stakeholders.
Required Skills & Experience
Technical Knowledge
* Agentic Frameworks: Basic knowledge of orchestration ecosystems like LangChain, AutoGen, or CrewAI.
* LLM Foundations: Strong grasp of Large Language Models, prompt engineering, and semantic memory patterns.
* Tool-Use Integration: Clear understanding of function calling, data pipelines, and external API connectors.
Business Analysis Expertise
* Agile Frameworks: Proven success working inside Agile or Scrum software development lifecycles.
* Process Mapping: Mastery of decomposition techniques, data rules, and hand-off mapping.
* Data Fluency: Ability to run analytical assessments and query data to validate agent integrity.
Soft Skills
* Constructive Skepticism: Ability to challenge status-quo enterprise assumptions.
* Ambiguity Handling: Comfort with exploring fluid, evolving AI product definitions