AI Practitioner

Job overview

We are looking for a AI Practitioner who can help teams and clients identify, design, and adopt practical AI solutions that improve day-to-day work and business outcomes. This role combines hands-on AI tool usage, solution thinking, workflow analysis, stakeholder communication, and enablement. The ideal candidate is comfortable working independently, can translate business needs into actionable AI use cases, and can guide others in applying AI effectively across delivery workflows. The role is especially relevant in contexts such as AI readiness assessment, tool integration and configuration, team adoption support, hands-on training, and custom AI solution development.

Responsibilities

• Identify high-value AI opportunities through workflow analysis

• Design AI solutions by selecting appropriate tools, techniques, and prompting approaches

• Configure and use GenAI tools across delivery workflows

• Build lightweight automations and integrations, including API-based scenarios

• Support adoption through demos, pair-working, and hands-on enablement

• Deliver training and knowledge transfer tailored to audience and AI maturity level

• Present recommendations to stakeholders and manage expectations

• Apply responsible AI practices — mitigate risks such as data leakage, hallucinations, and bias

• Document and share AI practices to raise organizational capability

Requirements

Must have:

• Strong software engineering background (6+ years)

• Solid understanding of AI/ML fundamentals (LLMs, tokens, embeddings, RAG, fine-tuning) and their practical trade-offs

• Strong prompt engineering: systematic prompting, structured outputs, scenario adaptation

• Hands-on GenAI tool experience in delivery contexts

• Ability to work independently and deliver reliably (Competent level per framework)

• Experience in workflow analysis and AI solution design

• Strong communication across audiences: recommendations, sessions, training

• Awareness of responsible AI concerns: privacy, hallucinations, safe usage

• Broad delivery understanding to spot AI opportunities across adjacent roles

Nice to have:

• Experience building AI-enabled automations, internal helpers, or lightweight end-to-end workflows

• Experience integrating AI via APIs or configuring custom assistants / GPT-style workflows

• Familiarity with multiple AI product categories (coding assistants, conversational AI, productivity copilots)

• Ability to evaluate practical applicability of new AI tools across the broader ecosystem

• Experience delivering live demos, workshops, or pair-working sessions to support adoption

• Experience creating playbooks, guidelines, reports, or reusable learning materials

• Contributions to communities of practice, knowledge bases, or mentoring of less experienced practitioners

• Experience defining and tracking AI impact metrics: time saved, quality improvements, adoption rates, ROI

• Cross-industry exposure or ability to adapt recommendations to different client contexts