What AI Job Listings Reveal About the Work Companies Need Done

Lately, I have been seeing more AI-focused positions on LinkedIn from companies hiring in Türkiye: AI Engineer, Data & AI Lead, AI-First Strategy Development Manager, and Yapay Zeka Grup Direktörü, or Group AI Director. What caught my attention was AI appearing in the job title itself, beyond being another skill requested for an established role.

These titles cover technical work, product management, team leadership and responsibility for transformation across a company. They may share the AI label, but they describe very different work. One candidate is expected to build a reliable production system. Another must decide which AI opportunities to pursue first. A third has to get different companies and teams working toward the same goals.

This article draws on 17 job descriptions reviewed as of 12 October 2026. They include Türkiye-based companies, the Turkish teams of international companies, and listings published by consultancies. I selected the examples myself. Some appeared to have been posted a few days earlier; others were months old. This is therefore a comparison of the work assigned to these roles, prompted by my own observation, rather than a study measuring growth in Türkiye’s job market.

Asking for AI skills and hiring for an AI role

CXL’s research on marketing job listings reports that 40% of the 878 US marketing listings it examined in the third quarter of 2026 required AI skills or responsibilities. In a separate first-quarter sample, the figure was 15%. The research also describes more visible expectations around automation and building workflows.

Those findings apply to the sampled US marketing listings. They cannot be generalized to Türkiye, and the two samples should not be read as tracking the same positions over time. CXL also uses the research to promote its own training. I treat the data as a limited indication of changing skill expectations.

What stood out in the Türkiye listings was different: AI was becoming part of the role’s name. Asking an existing employee to acquire a skill and defining a separate position for the work are different organizational decisions. The company also needs to define the teams the person will work with, the work they will take on, and the results they will own.

The job descriptions offer more detail on those decisions than the titles do.

Building a system that works in production

Hayat’s Senior AI Software Developer listing calls for integrating large language models with APIs, databases, SAP and other enterprise systems. Evaluating output accuracy, security, latency and cost is part of the job, alongside developing reusable components and reviewing the quality of AI-generated code.

Apilex’s AI Engineer listing brings together agent systems for legal workflows, information retrieval, evaluation and regression testing, and decisions about cost and reliability. Preserving the state of a task and recovering after a failure are also within its scope.

In both examples, the technical work extends beyond connecting a model to an application. Once the system has to handle real data, real users and recurring work, output testing and failure handling become part of the product.

That expectation does not automatically mean more model-development work. Integration, software quality, data access and responsibility for running the system can all fall within one position. Counting the technologies named in a listing gives only a partial picture of the job.

Product, data and process decisions can share one title

Modern Karton’s Data & AI Lead listing calls for turning data from SAP, manufacturing execution systems and sensors into business value, and developing analysis and dashboards for operational decisions. AI use cases sit alongside responsibility for data architecture, quality and security.

Here, production data and the decisions it supports provide the starting point for AI work. The data needs to be usable, the analysis needs to help, and the solution needs to fit the workflow. Those tasks are closely connected.

Massive Bio’s Senior Product Manager position in Istanbul has a different emphasis: the product roadmap, success metrics, acceptance criteria derived from clinical and commercial needs, and tracking results after release. Balancing new development against technical debt is also part of the role.

Deciding what an AI product should do, which user problem to prioritize, and how to judge whether it works is still product management. Adding AI to a title does not resolve those decisions. The person making them needs to understand the business context and what failure would cost.

Some roles are responsible for changing how the company works

TEB Yatırım’s AI Strategy & Transformation Lead listing calls for mapping investment processes, identifying bottlenecks and manual workloads, prioritizing opportunities and developing hypotheses about business value. KPIs, validation, model risk and governance are also included. The listing describes a strategic and operational transformation role.

Mavi’s AI-First Strategy Development Manager is expected to own the company-wide AI portfolio and transformation roadmap. The work includes reviewing existing processes with business owners, designing how those processes should work, conducting initial assessments of opportunities and tracking benefits after go-live. The listing states that the role reports to the Data Analytics Director & AI Group Leader.

Aydem Enerji’s Yapay Zeka Grup Direktörü, or Group AI Director, is expected to coordinate group companies, the central AI Office, company coordinators and technology teams. The listing describes assessing use cases by business value, data suitability, risk and resource requirements, and managing the progression from pilots to adoption and scaling. It explicitly states that the position reports to the holding company’s CTO.

In these three examples, technical knowledge is combined with responsibility for coordinating work and decisions across teams. Which projects are selected, what changes business units make, and how benefits are tracked all contribute to success.

These are expectations described in job advertisements. This review does not tell us how far the companies have established these ways of working, whom they have hired or what results the implementations have produced.

A new title may describe familiar work

Some of these AI-related jobs combine data, software, product and process expertise companies already need. The AI-titled BCG Platinion listings reviewed, for example, also devote substantial attention to enterprise architecture, digital transformation and strategic technology implementation. The AI label alone does not explain the full scope.

ING Hubs Türkiye’s Data & AI Team Manager listing emphasizes team capabilities, engineering standards, a capability roadmap and how the team works with product teams. Even when the technical field changes, responsibility for developing the team and delivering its work remains.

Judging a listing by its new-sounding title can miss much of what the job actually describes. Which duties previously belonged to another team? Which responsibility is genuinely new? Is the role expanding existing work, combining several jobs or taking on work that was not previously done? Reading the listings together helps us examine those questions, even if it cannot answer them definitively.

Hiring also requires designing the job

When a company advertises an AI-focused position, it should be able to explain what it expects the hire to deliver as clearly as it specifies the tools the candidate needs to know.

If the person is expected to develop a company-wide roadmap, for example, the company needs to clarify how they will work with business units on priorities and how much involvement they will have in investment decisions. If the aim is to create value from production data, data access and collaboration with process owners need to be defined. If the hire will take a system into production, it should be clear who will help assess quality and what responsibility the person will have once it is running.

As the role’s scope grows, so do these dependencies. A technical hire may not be able to set the product team’s priorities alone. A transformation manager also needs more than individual expertise to change data infrastructure and the way business units work. The role’s authority, resources and working relationships need to match the expected result.

The variety I see in AI-focused listings in Türkiye raises a broader set of hiring questions. Building technical systems, taking responsibility for product decisions and coordinating transformation across a company are different jobs. A company can bring them under an AI title, but it needs to explain the differences when hiring.

The clearest account of what a company needs comes after the job title: the work to be done, the authority to do it, and the result the company expects.