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Build production-grade, tool-augmented AI agents using LLMs, RAG, and agent orchestration frameworks, integrating them with enterprise systems and enforcing safety policies.
Design, build, and optimize enterprise-grade AI agents and solutions, combining deep AI/ML technical expertise with strategic consulting to translate complex business challenges into production-ready architectures.
Builds and leads Dialpad’s next-gen AI agent platform, designing scalable multi-agent orchestration, real-time conversational reasoning, and enterprise-grade tool execution systems.
Designs and builds Dialpad’s next-gen AI agent platform, orchestrating autonomous workflows, real-time reasoning, and enterprise tool integration to resolve customer issues.
About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every…
Principal Engineer builds and scales AI-driven platforms and agentic systems for clients, guiding architecture and mentoring teams across diverse tech stacks.
Lead Software Engineer at a tech consultancy, leading client engagements from discovery to production across multiple languages and frameworks, with increasing focus on AI/ML and agentic systems.
LSports is a world-leading sports data provider, trusted by sportsbooks worldwide to deliver real-time data with unmatched accuracy and reliability. With technology that drives smarter trading and deeper engagement, we…
Salary: £? - ? per year Requirements: We are looking for an experienced AI Engineer or Generative AI Engineer with strong hands-on experience across Generative AI, Large Language Models, Retrieval-Augmented Generation,…
Build and operate large language model serving infrastructure at scale using Python, Kubernetes, and cloud platforms, applying site reliability engineering practices to AI platforms at J.P. Morgan.
Embedded AI engineer at Google Cloud who builds, deploys, and optimizes production-grade agentic AI systems for enterprise customers, bridging Google’s AI products with client infrastructure while feeding insights back to product teams.
Build and scale dunnhumby’s Enterprise AI Platform, designing production-grade AI systems including RAG, agentic workflows, and LLM-powered services using Python, LangChain, and cloud-native tools.
Monitors and secures AI tools, agents, and models across the company, hunting for unauthorized usage and data risks while supporting compliance with AI governance frameworks like ISO 42001.
Monitors and secures AI tools, agents, and models in use across the company, hunting for unauthorized AI activity and ensuring compliance with AI governance frameworks like ISO 42001.
Build and maintain Nexxen’s internal AI platform, designing reusable AI capabilities, multi-agent systems, and production-grade AI services using Python, Kubernetes, and modern cloud-native tools.
Build and scale production AI systems for English Language Learning, developing agentic content generation workflows and LLM-powered services (Conversation Brain, Ambient ORA) that serve multiple Pearson products. Work with Python (FastAPI, CrewAI, LangGraph, LangChain), Azure, and observability tools to operationalize AI from research into production.
Hands-on technical leadership role designing and delivering production-grade Generative AI and Agentic AI solutions, including LLM-powered applications, RAG pipelines, multi-agent architectures, and LLMOps using Python, agent frameworks, and cloud platforms.
Senior hands-on role designing and delivering scalable data and AI solutions—data pipelines, LLM/RAG integrations, and distributed data systems—translating architectural requirements into HLD/LLD specs and leading delivery teams in a hybrid setup based in Pune.
Designs and optimizes AI agentic systems (e.g., LangGraph, AWS Bedrock) for government clients, integrating LLMs with enterprise tools for workflow automation, testing, and debugging.
Designs and optimizes AI agent systems using foundation models (e.g., Claude Sonnet) to build intelligent workflows for government clients, integrating with enterprise tools and tuning agent behavior for real-world outcomes.
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