Senior AI Engineer
Architect and build agentic workflows and conversational systems using LLMs and reasoning components to optimize recruiting. Lead the design, development, and deployment of advanced ML/NLP products from ideation to production.
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Architect and build agentic workflows and conversational systems using LLMs and reasoning components to optimize recruiting. Lead the design, development, and deployment of advanced ML/NLP products from ideation to production.
Lead complex, multi-system AI deployments end-to-end, managing the full engagement lifecycle from technical discovery to production. Architect multi-agent solutions and design personalized resource packs while mentoring junior engineers and driving strategic intelligence loops.
You will own the inference and orchestration layer that powers AI interactions, ensuring high reliability and low latency. Your role involves building production systems, designing inference pipelines, and managing monitoring and incident response.
You will build end-to-end product features and design agent workflows that handle planning, tool use, and failure recovery. You will collaborate with ML and backend teams to integrate LLMs and memory into reliable, production-grade systems.
Evaluate and analyze LLM performance while architecting and building inference and training pipelines. You will contribute to hands-on design, model training, and deployment strategies within a technical greenfield project.
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You will architect and build agentic workflows that integrate large language models and reasoning components to create adaptive conversational systems. Additionally, you will lead the development of ML/NLP products from ideation to production while mentoring engineering peers.
You will architect and develop agentic AI workflows that integrate large language models and reasoning components to create adaptive conversational systems. Additionally, you will lead the end-to-end development of ML/NLP products and mentor engineering peers to ensure scalable and maintainable AI solutions.
The role involves building and maintaining engine/editor plugins, SDKs, and services that integrate AI, specifically LLMs, into game clients, servers, and build tools. Responsibilities also include designing stable API surfaces, standing up CI/CD pipelines, automating QA, and implementing production LLM integrations with safety and cost controls.
The role involves building and evolving the core AI tutoring system, focusing on prompt architectures, agentic workflows, and real-time adaptive learning behaviors. Responsibilities also include running rigorous experimentation, designing scalable software integrations, and collaborating cross-functionally to implement pedagogical goals.
The role involves building agentic systems capable of reasoning, planning, and executing multi-step tasks reliably within the AI-driven media pipeline. Responsibilities include designing and deploying LLM-based services, developing video/image intelligence pipelines, and shipping scalable inference pipelines on cloud infrastructure.
The engineer will review and refine AI-generated content related to MLOps workflows, automation, monitoring, and deployment to ensure technical validity and industry best practices. This includes drafting realistic scenarios and assessing AI reasoning across various operational aspects of machine learning.
The role involves architecting and building agentic workflows that integrate large language models, reasoning components, and data pipelines to create adaptive conversational systems. Responsibilities also include leading the design and development of advanced ML/NLP products through to production, including experimentation with new agentic reasoning approaches.
The role involves architecting and building agentic workflows that integrate large language models, reasoning components, and data pipelines to create adaptive conversational systems. Responsibilities also include leading the design and development of advanced ML/NLP products through to production, including training, evaluation, and deployment.
The role involves architecting and building agentic workflows that integrate large language models, reasoning components, and data pipelines to create adaptive conversational systems. You will lead the design and development of advanced ML/NLP products from ideation through to production, including experimentation with new agentic reasoning approaches.
The role involves architecting and building agentic workflows that integrate large language models, reasoning components, and data pipelines to create adaptive conversational systems. Responsibilities also include leading the design and development of advanced ML/NLP products from ideation through to production deployment.
The Staff Backend Engineer will shape and scale the core infrastructure behind GitLab CI, focusing on integrating AI into CI/CD workflows to enhance performance, reliability, and usability for millions of jobs. This involves defining success metrics for AI agents, building necessary instrumentation, and hardening the underlying CI pipeline execution infrastructure.
The role involves building and evolving the core AI tutoring system, focusing on prompt architectures, agentic workflows, and real-time adaptive behaviors. Responsibilities also include running rigorous experimentation, designing scalable software integrations, and collaborating cross-functionally to translate pedagogical goals into technical solutions.
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Conduct experiments to efficiently train large language models and explore methods of guided generation and search. Mine relevant data at web scale and conduct experiments with various reinforcement learning configurations.
You will own the reliability, performance, and observability of the entire inference stack. This includes designing telemetry pipelines, tuning Kubernetes autoscalers, and creating automation for incident management.
Develop cutting-edge GenAI solutions and own production rollouts of GenAI applications. Serve as a trusted technical advisor to customers and collaborate cross-functionally with product and engineering teams.
Develop cutting-edge GenAI solutions and own production rollouts of GenAI applications. Serve as a trusted technical advisor to customers and collaborate with product and engineering teams.
Develop cutting-edge GenAI solutions and own production rollouts of GenAI applications. Serve as a trusted technical advisor to customers and collaborate with cross-functional teams.
You will own the end-to-end development of a self-contained area within a production agentic AI product for a cyber security organization. This involves integrating LLMs into frameworks and maintaining a prioritized backlog in collaboration with the client.
You will own, build, and scale your own startup in the Agentic AI field while receiving intensive coaching and support. You will iterate your product to achieve product-market-fit and build out your sales and marketing operations.
Design and build reusable platform capabilities for LLM applications, AI agents, and RAG workflows. Develop secure integrations and establish standards for AI deployment, observability, and lifecycle management.
You will be responsible for architecting and deploying high-impact AI solutions on the Moveworks ServiceNow platform to solve complex customer business challenges. This role involves full-stack ownership of the delivery lifecycle, from initial solution design to integration and ongoing product tuning.
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You will design and build an agentic identity platform, focusing on verifiable agent identity, instance integrity, and continuous runtime trust. You will also mentor the engineering team and set the technical direction for the platform's architecture.
You will build and ship production-ready, AI-powered products by integrating LLMs, RAG, and agentic workflows into financial service processes. Additionally, you will architect scalable cloud-native systems on AWS while ensuring high standards for reliability, latency, and operational excellence.
You will design and build tools for the GitLab Duo CLI, shaping AI-assisted developer workflows and infrastructure. You will also provide technical leadership, mentor team members, and collaborate across the AI Clients stage to ensure high-quality, performant, and intuitive developer experiences.
You will own the end-to-end design and delivery of features for the Duo Agent Platform, including onboarding and autonomous repository flows. You will also collaborate with cross-functional teams to build agentic experiences and contribute to the team's technical quality through code and design reviews.
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