Overview:
SOFTSWISS continues to expand its AI capabilities, and we are looking for a Senior AI Solutions Analyst to join our dedicated AI Software Delivery team. We need a versatile professional who combines strong analytical thinking with hands-on AI skills — someone who can bridge the gap between business needs and technical AI solutions, while also building parts of those solutions independently.
Purpose of the role:
You will serve as the primary interface between business departments and the AI engineering team. Your mission is to understand business workflows, identify opportunities for AI-driven improvement, gather and formalize requirements, select the right tools and approaches, and ensure that delivered solutions are successfully adopted and maintained by the business teams themselves.
Unlike a traditional business analyst, you will also be a hands-on practitioner — capable of building lightweight AI solutions (prompt engineering, no-code/low-code workflows, simple automations) independently, while delegating complex engineering work to the development team. Your ultimate goal is enablement: every solution you deliver should be designed so the business team can own and evolve it going forward.
Key responsibilities:
- Requirements Engineering: Engaging with business departments to understand their workflows, pain points, and objectives. Translating business needs into clear, structured requirements for AI-enabled solutions
- Solution Design: Evaluating and recommending the optimal approach for each use case — from off-the-shelf AI tools (ChatGPT, Claude, Copilot) and no-code platforms to custom-built solutions requiring engineering effort
- Hands-on Implementation: Building and configuring AI-powered solutions independently, where full engineering effort is not required — prompt engineering, workflow automation, chatbot configuration, dashboard creation, and integration of existing AI tools
- Task Decomposition & Delegation: Breaking down complex solution requirements into well-defined tasks for the development team. Writing clear technical specifications and acceptance criteria for engineering work
- Business Enablement & Knowledge Transfer: Designing solutions with handover in mind. Training business teams to operate, maintain, and iterate on delivered AI solutions. Creating documentation and runbooks for ongoing support
- Stakeholder Management: Managing expectations, communicating progress, and facilitating collaboration between business teams, AI engineers, and leadership. Participating in Scrum ceremonies and contributing to the AI roadmap
- Tool Landscape Awareness: Continuously evaluating the evolving AI tool ecosystem to identify new opportunities. Recommending tooling decisions based on business value, security, compliance, and total cost of ownership
- Quality Assurance: Validating that delivered solutions meet business requirements and quality standards. Coordinating user acceptance testing with business stakeholders
Required Experience:
- 5+ years of professional experience in business analysis, systems analysis, solution consulting, or a related role
- English — Upper-Intermediate or higher
- Demonstrated experience working at the intersection of business and technology — translating business requirements into technical solutions and vice versa
- Hands-on experience with AI/LLM tools: proven ability to use ChatGPT, Claude, Copilot, or similar tools to solve real business problems (not just personal experimentation)
- Practical prompt engineering skills: ability to design, test, and iterate on prompts and AI workflows to achieve reliable business outcomes
- Experience with no-code/low-code platforms or automation tools (e.g., n8n, Make/Zapier, Power Automate, Retool, or similar)
- Strong requirements engineering skills: experience with requirements elicitation, documentation, user story writing, and acceptance criteria definition
- Understanding of software development lifecycle and ability to communicate effectively with engineering teams
- Experience with data analysis and visualization — ability to work with datasets, create reports, and derive actionable insights
- Excellent communication and facilitation skills — ability to run workshops, present to stakeholders, and translate between technical and non-technical audiences
- Experience in an Agile/Scrum environment
Nice to have:
- Russian language knowledge
- Experience in the iGaming, fintech, or other regulated industries where data security and compliance are paramount
- Understanding of RAG (Retrieval-Augmented Generation) concepts and how enterprise AI systems work at a high level
- Familiarity with MCP (Model Context Protocol) and how AI tools integrate with enterprise data sources
- Basic vibe coding skills (Python, JavaScript, SQL) — enough to prototype, query databases, or automate simple data workflows
- Experience with knowledge management systems and enterprise documentation platforms (Confluence, Notion, etc.)
- Experience designing solutions with a “self-service” or “citizen developer” mindset — enabling non-technical users to maintain and evolve AI-powered tools
- Familiarity with AI governance, responsible AI principles, and enterprise AI security considerations.
- Understanding of vector databases, embeddings, and semantic search concepts at a conceptual level
Learn more about our hiring process here – what to expect, how to prepare, and what makes SOFTSWISS different.