Chapter Lead AI/LLM Data Scientist in Agentic AI

ING Hubs Türkiye

Fatih

On-site

TRY 2,714,932 - 4,072,398

Full time

14 days+

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Benefits offered by this job

14 days of welcome leave

Self-driven career paths

Comprehensive health insurance

Job summary

ING Hubs Türkiye is seeking a Chapter Lead for Advanced Analytics. In this role, you will manage a diverse team, develop LLM-powered AI agents, and oversee delivery for global priorities. You should have a degree in Computer Science and strong management experience within Agile teams. The position offers the chance to work in a dynamic, innovative environment with global exposure and opportunities for personal growth.

Qualifications

Experience in building LLM, Generative AI, or NLP solutions.
Understanding of LLM fundamentals and modern AI development patterns.
Management experience in a matrix setup is a plus.

Responsibilities

Develop a view on DS capability craftsmanship with Tribe and Product Leads.
Build and deploy LLM-powered agents that interact with data.
Support teams in understanding AI agent behavior.

Skills

Management experience in an Agile organization

Strong Python skills

Ability to build end-to-end AI applications

Fluent in English

Education

Degree in Computer Science or similar field

Tools

Agentic AI frameworks

Modern workflow orchestration tools

Job description

Our goal is to help people advance in life and business. We are a well-established brand with strong financials, global reach, and omni-channel strategies. If you value innovation, agile principles balanced with compliance and quality, reliable service, and a practical work approach, this is the place for you.

ING Analytics is a new unit responsible for realizing this vision for ING, differentiating ING as a leader in data-driven organization, within the banking sector and beyond. The team consists of a number of Global Analytics Centre of Excellence around the bank’s key capabilities (such as Pricing, Risk Management, Financial Crime, Customer Intelligence and People Analytics.) as well as strong coordination areas around data management, technology, customer journey, UX, as well as external partnerships.

About the Role

As a Chapter Lead you have a dual role. You build a strong‑identity team that apply their diverse skills and perspectives to achieve common goals, actively perform the people management of your chapter members and further develop and safeguard their knowledge and craftsmanship, in this instance for Advanced Analytics. On the other hand, you are spending the majority of your time working together with your team as a contributor on the delivery as well. As a Chapter Lead you have the complete overview and insight on the capabilities, expertise and experience of your chapter members and you will be responsible to decide on allocation of your chapter members capacity for the global backlog delivery demand coming from the Product Lead and Tribe Lead.

What You’ll Do

Together with the Tribe Lead and Product Lead develop a view on the future of the DS capability craftsmanship and drive continues development of your chapter members.
Working closely together with the other Chapter Leads to discuss and align on required capabilities and capacity across chapters for delivery.
Together with the Tribe Lead, Product Lead and other People Leads, decide on the allocation of capacity of your chapter members for the delivery of the global priorities
Build and deploy LLM‑powered agents that interact with data, tools, and business applications.
Design agentic solutions that support complex workflows and decision‑making.
Work closely with engineers to productionize your AI agents using modern development practices.
Translate business problems into data‑driven solutions and actionable insights.
Support teams in understanding AI agent behavior and recommending improvements.
Strengthen the team’s overall AI craftsmanship through knowledge sharing and collaboration.

What You Bring

Degree in Computer Science or similar field (NLP/ML background is a plus).
Management experience in an Agile organization. Management experience in a matrix set up is a plus.
Experience in building LLM, Generative AI, or NLP solutions.
Strong Python skills and experience delivering production‑ready code.
Understanding of LLM fundamentals and modern AI development patterns.
Ability to build end‑to‑end AI applications and deliver business impact.
Fluent in English; comfortable working in Agile teams.

Nice to have (but Not Required)

Experience with agentic AI frameworks such as LangGraph, LangChain, Semantic Kernel, Autogen, CrewAI, or similar systems used to build tool‑using or multi‑step agents.
Familiarity with cloud AI platforms like Azure AI Studio, OpenAI APIs, Google Vertex AI Agent Builder, or Google AI SDK for building and deploying agent workflows.
Exposure to retrieval and memory systems (vector databases, embedding‑based search, knowledge stores) to support grounded and context‑aware agents.
Comfort with modern workflow orchestration tools (DAGs/graphs, workflow engines, event‑driven patterns) for building reliable multi‑step AI flows.
Understanding of LLM evaluation and safety practices, including structured outputs, scenario testing, and basic guardrail implementation.
Experience integrating AI systems with real APIs, tools, databases, or business processes, especially in settings where agents take actions rather than only generate text.