Top Artificial Intelligence Jobs in Izmir

Lead strategic engagements to accelerate adoption of Genesys AI and Experience Orchestration. Translate business goals into AI use cases, drive field execution, support deal strategy, run customer workshops, create proposals and pricing, capture customer insights, and partner cross-functionally to prioritize AI-led opportunities and pilots.

The role involves leading design for AI-native products at Synthesia, focusing on improving interaction patterns and enhancing user experience in AI-driven workflows.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

Develop and deploy production-ready generative AI applications using Python, LLMs, RAG, AWS Bedrock, and OpenAI APIs. Responsibilities include model customization, API integration, data preparation, performance tuning, production deployment, documentation, and cross-functional collaboration. The role focuses on applied engineering rather than research and requires experience integrating AI solutions into business applications.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Own the roadmap and delivery of AI automation products, including reliable AI agents, tool-calling workflows, n8n automation pipelines, API integrations, and React-based interfaces. Partner with sales, content, and marketing to identify opportunities, then monitor, debug, and improve shipped solutions. The role requires strong product ownership, hands-on AI and automation experience, technical range across frontend and integrations, and fluency with LLMs and agent frameworks.

Join the Compliance team to own AI and e-commerce legal workflows: GDPR and data protection documentation, AI systems inventory, risk assessments, product/feature reviews, contract and IP issue handling, TOS/privacy updates, and monitoring legal developments. Work with the Ethics & Compliance Officer and review uncensored AI content as needed.

Design, develop, and optimize autonomous AI agents capable of reasoning, planning, tool use, and multi-step execution. Build agent frameworks, human-AI collaboration mechanisms, monitoring and evaluation systems, and production integrations. Apply large language models, prompt engineering, reinforcement learning, planning algorithms, workflow orchestration, and system design. Collaborate cross-functionally while researching advances in agent technology and improving reliability, accuracy, safety, and efficiency.

Support product operations by collecting and tracking user feedback, coordinating product issues across teams, organizing requirements, analyzing basic data, maintaining web pages, and assisting with AI-related projects. The role requires cross-functional communication, problem-solving, execution skills, bilingual English and Mandarin proficiency, and availability for 3–5 days per week for at least six months.

Build and improve Restream’s web interfaces and user-facing features for the AI Clips team. Design UI and business logic, collaborate with product designers, participate in code reviews, improve system reliability, and evaluate emerging technologies. The role requires strong JavaScript and TypeScript expertise, advanced React knowledge, CSS preprocessor experience, and familiarity with backend development, cloud infrastructure, containers, and continuous deployment.

Lead enterprise AI strategy, operating model, governance, platform enablement, and CoE to deploy safe, compliant, and scalable AI across R&D, Clinical, Manufacturing, Quality, Commercial, and Corporate functions in a regulated pharmaceutical environment.

Lead design and ownership of shared libraries, Spring Boot starters, and agentic frameworks. Set standards for agent orchestration, evaluations, and guardrails. Mentor teams on Python-based agents (LangChain/LangGraph), drive adoption, prototype research directions, and improve developer experience across Kotlin backend and client libraries.

Provide EU-focused counsel on AI and privacy regulation (EU AI Act, GDPR, DSA); draft policies, DPA and contractual terms; translate legal requirements into technical and operational controls; advise product, engineering, and go-to-market teams; liaise with regulators and manage compliance programs and risk assessments.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Manage AI-powered client engagements from onboarding through reporting, serve as primary client contact, coordinate timelines and cross-functional teams using Monday.com, execute AI visibility campaigns, prepare performance reports and presentations, maintain SOPs and knowledge bases, leverage AI tools to streamline workflows, and identify process improvements to scale services.

Build high-performance, scalable React+TypeScript web applications for payment experiences. Design reusable UI components and optimize frontend performance while collaborating with cross-functional teams on architecture, testing, accessibility, and product delivery.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

As a Staff/Senior AI Product Engineer, you will build AI-powered product features, enhance the tech stack, and design AI workflows while collaborating with product teams. Your focus will be on agent-native architecture and improving the codebase for AI agents.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Lead and operate enterprise Azure and Microsoft 365 platforms, manage hybrid identity (Entra ID/AD), deliver and govern AI solutions (Azure OpenAI, Azure ML, Copilot), provide L2/3 support, secure and govern cloud resources, manage on‑prem infrastructure, and drive vendor, project, and stakeholder engagement to scale AI initiatives.

Early-career full stack internship developing frontend and backend features under senior guidance. Integrate AI coding tools into workflows, translate product requirements to implementations, contribute across the product lifecycle, and suggest cross-team process improvements while learning full-stack practices.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.