Chapter Lead AI/LLM Data Scientist in Agentic AI

ING Hubs B.V. Turkiye; Fatih; On-site; TRY 3,671,408 - 4,589,261; Full time

Benefits offered by this job

14 days of welcome leave

Comprehensive health insurance

Private pension plan

Meal card

Transportation allowance

MultiSport membership

English development support

Job summary

ING Hubs B.V. Turkiye is looking for a Chapter Lead in Fatih, Turkey. This role involves leading a team to build and apply advanced analytics while also contributing to project delivery. The ideal candidate should have strong Python skills, an understanding of LLM, and prior management experience in an Agile setting.

The position offers opportunities for growth and a vibrant work culture, with benefits including comprehensive health care, a private pension plan, and a meal card.

Qualifications

• Degree in Computer Science or similar field (NLP/ML background is a plus).
• Management experience in an Agile organization.
• Strong Python skills and experience delivering production-ready code.

Responsibilities

• Develop future DS capability craftsmanship with Tribe and Product Lead.
• Collaborate with other Chapter Leads to align capabilities.
• Coordinate allocation of capacity for global priorities.

Skills

Python skills

AI application development

Management experience in Agile

Building LLM/NLP solutions

Fluent English

Education

Degree in Computer Science or similar field

Tools

Azure AI Studio

OpenAI APIs

Job description

About the Role

As a Chapter Lead you have a dual role. You build a strong‑identity team that applies diverse skills and perspectives to achieve common goals, actively perform people management of chapter members and further develop and safeguard their knowledge and craftsmanship, in this instance for Advanced Analytics. On the other hand, you spend the majority of your time working together with your team as a contributor on the delivery as well. 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

• Work with the Tribe Lead and Product Lead to develop a view on the future of the DS capability craftsmanship and drive continuous development of your chapter members.
• Collaborate with other Chapter Leads to discuss and align on required capabilities and capacity across chapters for delivery.
• Coordinate allocation of capacity of your chapter members for the delivery of 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 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.

What We Offer

• Be Yourself, Be an ING'er
• Leave: 14 days of welcome leave, even in your first year
• Career Opportunities: self‑driven career paths
• Personal Growth: challenging work with endless opportunities
• Dynamic Environment: informal, vibrant, and innovative culture
• Innovation Culture: explore and apply PACE methodology
• Global Exposure: work on global projects
• Health Care: comprehensive health insurance for you and your family
• Private Pension Plan: secure your future
• Meal Card, Transportation Allowance, MultiSport Membership, English Development Support