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The AI Consultant 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
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
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
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