Top Artificial Intelligence Jobs in Istanbul

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

As a Sales Engineer, you'll demonstrate Camunda's value, support product evaluations, conduct demos, and collaborate on sales strategies to convert prospects.

Lead architecture and delivery of AI-driven media platforms across cloud and hybrid environments. Design cloud-native solutions, build reusable NLP/computer vision components, develop POCs/MVPs, integrate third-party tools, supervise development teams, support pre-sales, and explore emerging AI technologies for content production and audience intelligence.

Design, build, and deploy scalable AI/ML systems for media monitoring, sentiment analysis, content classification, predictive modeling, recommendation engines, and real-time dashboards. Lead R&D pilots, integrate models into production and APIs, automate metadata and moderation workflows, and translate AI insights for cross-functional teams and clients.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

3–6 month internship supporting risk operations: monitor KRIs and case trends, assist investigations and case analysis, escalate findings, and help optimize AI/LLM tools, automation, and alerting workflows.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

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.

Design, build, and deploy production-grade AI systems: develop and optimize LLM and diffusion features, engineer prompt systems and evaluation workflows, collaborate with backend/product teams, and own feature lifecycle from prototype to scalable maintenance.

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.

Design, build, and run production agentic workflows and reusable components for delivery processes. Implement RAG-backed knowledge bases, monitoring, evals, observability, and human-in-the-loop feedback to improve agents and integrate them with delivery teams and business tools.

Produce polished video, motion, and static assets for major US TV/entertainment clients using professional creative software and AI-agent workflows. Deliver to spec with strong craft, brand judgment, versioning, QA, file discipline, and continuous workflow improvements.

Lead and own Agent0: co-own roadmap with Product, hire and grow a senior AI engineering team, drive delivery of production-grade agentic AI, set evaluation and monitoring standards, prototype innovations, and provide thought leadership on AI production excellence.

Build internal AI developer productivity tools (coding assistants, retrieval systems, workflow automation). Develop LLM-powered apps for code generation, understanding, and test automation. Integrate AI across the SDLC, embed with teams to remove friction, experiment with prompt engineering, RAG, and AI agents, and evaluate emerging AI technologies.

Early-career DevOps role focusing on Kubernetes and AWS operations, embedding security into the development lifecycle, automating processes, and implementing CI/CD solutions. Remote, fixed-term accelerator program for students and recent graduates.

Early-career TechOps role: build dashboards/alerts, script repetitive ticket steps, participate in RCAs, log user pain points and propose fixes, create a lightweight agent (e.g., Telegram bot) with reusable skills, optimize incident-management workflows, and write actionable runbooks to improve support-driven user experience.