Business Analyst – AI & Agentic Solutions

As a Business Analyst – AI & Agentic Solutions, you will serve as a vital link between clients, business stakeholders, product teams, and technical experts. Your role involves leveraging a strong foundation in Business Analysis alongside a deep understanding of Generative AI, Agentic AI, and AI-enabled products. You will analyze client business challenges, assess current processes, and identify opportunities where AI technologies can add value. Translating these insights into clear product and solution requirements will be key. While this role does not involve software development or coding, you will independently research AI models, platforms, APIs, and automation tools, collaborating closely with engineering teams to integrate these into solutions. Strong research, analytical, documentation, and client communication skills are essential for success in this position based in Islamabad, Pakistan.

Key Responsibilities

Business Analysis & Requirements Engineering
- Engage with clients and stakeholders to understand objectives, processes, pain points, users, constraints, and desired outcomes.
- Conduct discovery sessions, interviews, workshops, and research to gather and validate requirements.
- Translate business needs into functional and non-functional requirements.
- Develop business requirement documents (BRDs), functional requirement documents (FRDs), software requirement specifications (SRS), user stories, use cases, acceptance criteria, and process flows.
- Identify gaps, ambiguities, dependencies, assumptions, and risks, driving their resolution.
- Maintain requirements traceability throughout the project lifecycle.

Product & Solution Analysis
- Evaluate requirements for user experience, business value, feasibility, scalability, and long-term evolution.
- Translate business ideas into structured features, workflows, user journeys, and detailed specifications.
- Collaborate with product, UI/UX, AI, engineering, and QA teams to create actionable development tasks.
- Manage product backlogs and support prioritization based on value, impact, dependencies, and feasibility.
- Represent the client and end user throughout design and implementation phases.
- Participate in sprint planning, backlog refinement, demos, user acceptance testing (UAT), and release planning.

AI & Agentic AI Analysis
- Identify opportunities for Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), conversational AI, and intelligent automation.
- Apply knowledge of large language models (LLMs), multimodal models, embeddings, vector databases, agents, tool calling, memory, knowledge bases, prompt engineering, guardrails, and human-in-the-loop workflows.
- Understand AI agent interactions with applications, APIs, enterprise systems, databases, knowledge sources, and other agents.
- Translate processes into agentic workflows covering triggers, decisions, roles, tools, information sources, approvals, exception handling, and outcomes.
- Collaborate with AI and engineering teams to ensure workflows are implementable.
- Assess AI risks and limitations including hallucinations, privacy, accuracy, explainability, security, latency, cost, and reliability.

AI Technology & Solution Research
- Independently research AI models, APIs, platforms, open-source solutions, automation tools, agentic frameworks, and third-party services.
- Evaluate existing APIs, SaaS, open-source models, or automation platforms before recommending custom development.
- Compare options based on capabilities, accuracy, licensing, pricing, integration complexity, scalability, deployment, privacy, maturity, and vendor dependency.
- Research commercial and open-source models for text, voice, document intelligence, vision, OCR, search, and multimodal use cases.
- Explore low-code/no-code and orchestration tools such as n8n, Power Automate, Copilot Studio, Make, and Zapier.
- Prepare comparison matrices, feasibility assessments, solution options, and recommendations.
- Conduct hands-on experimentation with AI tools to understand capabilities (without coding).

Documentation & Solution Communication
- Produce clear, structured, client-ready documentation including process diagrams, workflow diagrams, user journeys, use cases, functional flows, and agentic workflow diagrams.
- Document AI use cases, agent responsibilities, knowledge requirements, system interactions, integrations, expected behaviors, and exception scenarios.
- Prepare solution concept documents, discovery reports, gap analyses, feature specifications, research reports, comparison matrices, and presentations.
- Explain technical concepts in business-friendly language.
- Maintain accurate, version-controlled, traceable documentation throughout the project.

Client & Stakeholder Coordination
- Act as the bridge between clients, stakeholders, product, AI, developers, QA, and project management teams.
- Lead or participate in client requirement and discovery meetings.
- Present requirements, workflows, features, research findings, and solution concepts to clients.
- Coordinate clarifications and ensure decisions and action items are documented and communicated.
- Manage stakeholder expectations and ensure alignment between client and delivery teams.
- Support client demos, UAT, feedback collection, and solution acceptance.

Quality & Acceptance
- Define clear, measurable acceptance criteria for conventional and AI-enabled features.
- Collaborate with QA to ensure test scenarios cover business requirements.
- Define expected behaviors and evaluation scenarios for AI assistants, chatbots, RAG applications, and agentic workflows.
- Support validation of conversational AI for relevance, accuracy, context handling, hallucinations, fallback behavior, and adherence to requirements.
- Participate in UAT to ensure delivery aligns with documented requirements and business outcomes.

Required Qualifications

- 4 to 8 years of relevant experience with strong Business Analysis fundamentals and demonstrated interest or experience in AI-enabled products.
- Proven expertise in requirements elicitation, analysis, stakeholder interviews, workshops, process analysis, and requirements management.
- Excellent skills in preparing BRDs, FRDs/SRS, user stories, use cases, functional specifications, acceptance criteria, process flows, and client-facing documentation.
- Ability to understand overall product vision, user journeys, business objectives, dependencies, and future evolution.
- Proficiency with process and product modeling tools such as Draw.io, Microsoft Visio, Miro, Lucidchart, or Figma.
- Strong practical knowledge of Generative AI, LLMs, RAG, AI agents, agent orchestration, conversational AI, prompt engineering, knowledge bases, tool calling, and AI automation.
- Ability to independently research and compare AI models, APIs, SaaS platforms, open-source technologies, agentic frameworks, and automation tools.
- Good conceptual understanding of APIs, webhooks, system integrations, databases, authentication, and data flows (coding not required).
- Exceptional written and verbal English communication skills for effective interaction with technical and non-technical stakeholders.
- Experience working directly with clients and coordinating across product, engineering, QA, design, and business teams.
- User-centric mindset with the ability to represent client and end-user needs throughout solution design.
- Experience with Agile and Scrum methodologies, including sprint planning, backlog refinement, reviews, retrospectives, and tools such as JIRA or ClickUp.
- Strong attention to detail with the ability to maintain structured documentation, decision logs, change history, and requirements traceability.
- Proactive problem-solving skills with the ability to identify gaps, evaluate alternatives, and drive requirements to closure.
- Adaptability to work in a fast-evolving AI landscape, quickly learning new tools and adjusting to changing client priorities.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Software Engineering, Information Systems