Technical Business Analyst - AI Solutions

We are seeking a Business Analyst – AI & Agentic Solutions to serve as a critical link between clients, business stakeholders, product teams, and technical teams. The ideal candidate will possess a strong foundation in traditional business analysis combined with a deep understanding of Generative AI, Agentic AI, and AI-enabled products. This role focuses on analyzing client business problems, evaluating existing processes, and identifying opportunities where AI technologies can add value. The Business Analyst will translate these insights into clear product and solution requirements. While this is not a software development role and does not require coding, the candidate must independently research AI models, APIs, platforms, and automation tools, collaborating closely with engineering teams to integrate these technologies effectively. Strong research, analytical, documentation, and communication skills are essential.

Key Responsibilities

Business Analysis & Requirements Engineering:
Engage with clients and stakeholders to understand objectives, processes, pain points, and constraints. Conduct discovery sessions, interviews, and workshops to gather and validate requirements. Translate business needs into functional and non-functional specifications, including BRDs, FRDs, user stories, use cases, and acceptance criteria. Identify gaps, risks, and dependencies, ensuring traceability throughout the project lifecycle.

Product & Solution Analysis:
Evaluate requirements for user experience, business value, feasibility, scalability, and future growth. Convert business ideas into structured features, workflows, and user journeys. Collaborate with product, UI/UX, AI, engineering, and QA teams to create actionable development tasks. Maintain product backlogs and support prioritization based on impact and feasibility. Represent the client and end user throughout design and implementation phases, participating in sprint planning, demos, UAT, and release activities.

AI & Agentic AI Analysis:
Identify opportunities for Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), conversational AI, and intelligent automation. Apply knowledge of LLMs, multimodal models, embeddings, vector databases, agent orchestration, prompt engineering, and human-in-the-loop workflows. Translate processes into agentic workflows, detailing triggers, decisions, roles, tools, and exception handling. Collaborate with AI engineers to ensure implementable solutions and assess AI risks such as hallucinations, privacy, accuracy, and security.

AI Technology & Solution Research:
Independently research AI models, APIs, platforms, open-source solutions, automation tools, and agentic frameworks. Evaluate existing SaaS and open-source options before recommending custom development. Compare solutions on capabilities, pricing, integration complexity, scalability, and vendor maturity. Explore low-code/no-code orchestration tools and conduct hands-on experimentation to understand AI tool capabilities.

Documentation & Solution Communication:
Produce clear, structured, client-ready documentation including process diagrams, workflows, user journeys, use cases, and agentic workflow diagrams. Document AI use cases, system interactions, integrations, and exception scenarios. Prepare solution concepts, gap analyses, comparison matrices, and presentations. Communicate technical concepts in business-friendly language and maintain version-controlled documentation.

Client & Stakeholder Coordination:
Act as a liaison between clients, stakeholders, product, AI, development, QA, and project management teams. Lead or participate in requirement and discovery meetings. Present requirements, workflows, and research findings to clients. Manage clarifications, document decisions, and align expectations. Support client demos, UAT, feedback collection, and solution acceptance.

Quality & Acceptance:
Define measurable acceptance criteria for AI-enabled and conventional features. Collaborate with QA to ensure test coverage aligns with business requirements. Define evaluation scenarios for AI assistants, chatbots, and agentic workflows. Participate in UAT to verify delivery meets documented requirements and business outcomes.

Required Qualifications

- 1-2 years of relevant experience in business analysis with a strong foundation in requirements engineering, stakeholder engagement, and documentation.
- Proven ability to prepare BRDs, FRDs/SRS, user stories, use cases, acceptance criteria, and process flows.
- Practical understanding of Generative AI, LLMs, RAG, AI agents, prompt engineering, and AI-enabled automation.
- Strong skills in independently researching AI technologies, APIs, SaaS platforms, and open-source frameworks.
- Conceptual knowledge of APIs, system integrations, databases, and data flows (coding not required).
- Exceptional analytical, research, and problem-solving abilities.
- Excellent written and verbal communication skills in English, capable of engaging both technical and non-technical stakeholders.
- Experience working directly with clients and coordinating cross-functional teams.
- Familiarity with Agile methodologies, sprint planning, backlog refinement, and tools such as JIRA or ClickUp.
- Proficiency in process and product modeling tools like Draw.io, Visio, Miro, Lucidchart, or Figma.

Educational Qualifications
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Software Engineering, Information Systems, or a related field from a reputable university.

This role offers a unique opportunity to work at the forefront of AI innovation, bridging business needs with cutting-edge AI technologies in a dynamic and evolving environment.