The AI Solution Analyst operates at the intersection of business analysis, applied AI development, and continuous learning. This role bridges the gap between strategic AI opportunities identified by solution architects and the technical implementation delivered by development teams. AI Solution Analysts bring a hands-on, experimental mindset to client engagements—prototyping solutions, engineering prompts, designing agent workflows, and translating business processes into AI-enhanced operations.

This is a delivery-oriented role with a strong exploration component: staying current with rapidly evolving AI capabilities and bringing that knowledge directly into client work and presales activities.

KEY RESPONSIBILITIES:

Client Project Delivery:

• Participate in active client AI projects as the hands-on AI specialist

• Design and build AI agent workflows, prompt chains, and orchestration logic

• Develop and refine prompts for specific business use cases (prompt engineering)

• Analyze existing client workflows and identify opportunities for AI enhancement

• Create working prototypes and proofs-of-concept to validate approaches

• Collaborate with developers on implementation handoff and technical specifications

Presales & Business Analysis:

• Support presales engagements with AI solution proposals and feasibility assessments

• Conduct business domain analysis to identify where AI creates genuine value

• Translate client business problems into AI-addressable solutions

• Prepare demonstrations and prototype artifacts for client presentations

• Provide input on effort estimation for AI components of proposals

AI Exploration & Knowledge Development:

• Monitor AI news, model releases, tool updates, and emerging techniques

• Evaluate new AI platforms, frameworks, and services for potential adoption

• Experiment with new approaches and share findings

• Document patterns, techniques, and lessons learned from project work

• Contribute to internal knowledge bases and training materials

Workflow Design & Optimization:

• Design agentic workflows using orchestration frameworks (e.g., n8n, LangGraph, custom pipelines)

• Optimize existing business workflows by introducing AI capabilities

• Define conversation flows, tool usage patterns, and handoff logic for AI agents

• Specify context management, memory strategies, and retrieval patterns

CORE COMPETENCIES:

Technical skills:

• Prompt engineering and LLM interaction patterns

• AI agent and workflow design (conceptual and hands-on)

• Understanding of RAG architectures, embedding strategies, and retrieval patterns

• Familiarity with AI platforms and APIs (OpenAI, Anthropic, open-source models)

• Workflow automation tools and integration concepts

Business skills:

• Business process analysis and optimization thinking

• Requirements gathering and stakeholder communication

• Ability to assess AI feasibility and set realistic expectations

• Presales support and proposal contribution

Research & Learning:

• Self-directed learning and experimentation

• Ability to synthesize trends and translate them into practical applications

• Knowledge sharing and documentation

Deliverables:

• Prompt libraries and engineering documentation for specific use cases

• Agent workflow designs (logic flows, tool definitions, conversation patterns)

• Proof-of-concept prototypes demonstrating AI approaches

• Business process analysis with AI opportunity mapping

• Presales solution outlines and feasibility assessments

• Internal knowledge articles on new tools, techniques, or project learnings

WE HAVE MANY THINGS TO OFFER:

Flexible schedule, international projects, home office kit, healthcare and more, you name it. Check out the whole list of benefits on our dedicated page, by clicking the following link: Benefits