AI First Content Strategist

Who We Are Build. Scale. Sustain.

PALO IT is a global technology consultancy that crafts tech as a force for good. We design, develop and scale digital and sustainable products and services to unlock value across the triple bottom line: people, planet, profit. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company.

We are small enough to care locally, big enough to deliver globally (5 continents, 18 offices, +650 experts from +50 nationalities)

We are robust and resilient (100% independent and 0 debt)

We are entrepreneurs and passionate experts: We invest in what we believe genuinely and work as a collective intelligence

We are positive, courageous, caring, doers and committed to excellence

About Gen-e2 While the market is still largely AI-augmenting delivery, we have reinvented the SDLC to be AI First. Our approach is a game-changer in productivity and quality, with a strong collaboration between AI generative and our best talents:

We now generate 95% of the entire product — code, documentation, infrastructure as code, and even design — with GitHub Copilot

The quality consistently exceeds the output of our best traditional engineering teams

A product repository houses all product artefacts, giving AI full project context for higher-quality generation

A library of rules and prompts defines coding standards, design principles, and security guidelines

With Gen-e2, we deliver end-to-end products 2–3× faster than traditional approaches, while raising the bar for engineering excellence.

Your Role As a

Lead Content Ops & Conversational AI , you will define and scale the Content Operations practice, transforming content into a strategic, reusable, and AI-powered infrastructure across all customer touchpoints.

Define and implement the

Content Ops model , including governance, voice & tone frameworks, and content standards

Design and scale

omnichannel conversational systems

(chatbots, voice, messaging, email, in-product experiences)

Build and manage

modular, reusable conversational flows

aligned with user journeys and business goals

Establish

semantic QA frameworks

to ensure consistency, accuracy, and brand alignment across channels

Design and optimize

end-to-end content workflows , integrating Product, Marketing, CX, and Engineering

Define and manage

tooling architecture , including conversational platforms and content automation tools

Leverage

AI/NLP and LLMs

to design, generate, and optimize conversational experiences

Train, fine-tune, and evaluate

language models and conversational systems

Integrate platforms such as

Voiceflow, Dialogflow, Rasa, ChatGPT, Braze, Twilio, Sendgrid

Define and track

OKRs and KPIs , including comprehension rates, resolution rates, engagement, and conversion

Drive

content personalization and automation strategies

at scale

Act as a

strategic bridge

between Product, Marketing, Data, and Engineering teams

Influence stakeholders and scale adoption of Content Ops practices across the organization

Who You Are

Proven experience in

Content Ops, Conversational Design, or CX/UX Writing at scale

Strong experience designing

conversational experiences across multiple channels

Hands-on experience with

NLP, LLMs, or AI-driven content systems

Experience with conversational tools such as

Voiceflow, Dialogflow, Rasa, or similar

Familiarity with

CRM/engagement platforms (Braze, Twilio, Sendgrid)

Strong understanding of

content lifecycle, governance, and modular content systems

Experience defining

voice & tone systems and content guidelines

Soft Skills

Strong

strategic communication and storytelling mindset

High level of

empathy and user-centric thinking

Ability to

facilitate cross-functional collaboration

Strong

systems thinking applied to content ecosystems

Comfortable making decisions in

complex and ambiguous environments

AI-Native Engineering (Core Expectation)

Use

Generative AI coding tools

(e.g., GitHub Copilot, Cursor) as a first-class engineering assistant for:

Code scaffolding and refactoring

Code generation and optimisation

Test-cases and documentation generation

Build applications through

AI-driven development practices , including:

AI-assisted debugging and troubleshooting

Intelligent code completion and pattern recognition

Automated documentation generation

Apply