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Designs, tests, and deploys production-grade LLM prompts and chains for client solutions and internal tools, integrating with APIs, RAG pipelines, and structured outputs.
Senior AI Engineer builds and deploys production-grade LLM-powered and agentic AI systems for real customer workflows, from design to deployment and operation.
Build and deploy production-grade agentic AI systems for enterprise clients, embedding with their teams to design, architect, and ship multi-agent workflows, RAG pipelines, and evaluation harnesses in Python and cloud environments.
Design and deliver applied AI solutions like LLM workflows and agentic automation for clients, integrating them into business systems while working US hours from India.
At Jellyfish, we believe in the power of diverse perspectives and inclusive collaboration. We welcome individuals who excel in collaborative, varied teams and value the unique contributions that each person brings to…
GenAI Engineer at Capco supporting development of scalable Python applications focused on GenAI, applying techniques like document chunking and embeddings, collaborating on UIs (Angular/React) and deployment processes (Docker, Terraform, GitHub Actions), and working with stakeholders to translate requirements into code.
Build Python-based GenAI applications for banks, integrating LLMs, embeddings, and vector search with Angular/React frontends and DevOps tooling.
Callimacus is developing a platform that orchestrates multi-agent interactions for demanding enterprise customers. You will join a small, senior team where the foundation is still being set, and your decisions will…
Build and scale Netomi’s agentic AI platform, designing systems that turn messy enterprise knowledge into structured, production-grade AI agents for customer experience automation.
Build and scale AI agents and microservices for Dotmatics’ Luma platform, integrating Python backend (FastAPI, LangChain/LangGraph) with React frontends to orchestrate scientific research workflows.
Design and optimize enterprise RAG platforms using vector databases and semantic search to power AI-driven knowledge systems and integrations with LLMs.
Build Retrieval-Augmented Generation systems that combine LLMs with enterprise knowledge, designing vector search pipelines and document ingestion to deliver accurate, context-aware AI responses.
Architect and lead enterprise-scale data platforms, MDM, and agentic AI integrations (RAG, LLM workflows) in cloud-native environments, while setting engineering standards and mentoring teams.
Architect and lead enterprise-scale data platforms, MDM, and agentic AI systems, building scalable pipelines and trusted data foundations for analytics and AI-driven applications.
Senior role building scalable data pipelines, semantic layers, and automated quality controls to turn raw data into trusted analytics products using Python, SQL, and distributed systems.
Lead the architecture and engineering of a bank-grade AI & Agentic Platform, designing agentic runtimes, LLM gateways, identity layers, and cloud-native infrastructure to support secure, scalable agent workflows across the enterprise.
Build production-ready AI apps for enterprises using LLMs, RAG, AI agents and workflow automation, integrating them into existing systems.
Lead AI and Python development teams to design, build, and deploy machine-learning solutions in the cloud using Agile practices.
Lead a team to design and deliver Python-based GenAI solutions, guiding architecture, cloud deployment, and responsible AI practices for enterprise clients.
Lead the design and deployment of enterprise-scale AI/ML and LLM solutions, including generative AI, RAG, and knowledge graphs, while mentoring teams and ensuring Responsible AI compliance.
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