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Build and maintain scalable data pipelines and infrastructure to power AI applications using LLMs, retrieval systems, and agentic architectures for enterprise clients.
Senior engineer builds and deploys LLM-powered agents and RAG systems for clients, owning presales scoping through production deployment with Python and cloud tooling.
Build and deploy enterprise-grade GenAI and ML applications for asset management workflows, integrating LLMs, RAG, and vector databases with full-stack Python/React systems in a regulated environment.
Build production-grade AI tools and data pipelines for the Group CEO, turning executive problems into reliable LLM-enabled workflows and decision-support systems while aligning with maritime and trading operations.
Build autonomous agents, data pipelines, and executive AI tools for a CEO while ensuring scalable, secure MLOps/LLMOps systems.
Build and expand a full-stack monolith for the wedding and real-estate industry, integrating AI agents, payments, and CRM while owning end-to-end features in Next.js, Prisma, and PostgreSQL.
Build and deploy generative AI solutions end-to-end, from LLMOps pipelines to cloud-native production systems, while collaborating with cross-functional teams to deliver client-ready AI applications.
Design and build generative AI and LLM-powered solutions for clients, including agent architectures, RAG systems, and cloud-based AI platforms on Azure/AWS/GCP.
Build and deploy end-to-end data/AI pipelines for clients, integrating ML models, cloud-native stacks (AWS/Azure/GCP), and real-time processing to turn raw data into business insights and operational tools.
Builds scalable data pipelines and infrastructure for AI systems, including LLMs and agentic architectures, using Python, SQL, and cloud platforms like AWS/Azure/GCP.
Build and deploy scalable AI/ML models and LLM-based systems on Hilti’s AI platform, using Python, Azure, and MLOps/LLMOps practices to power global construction workflows.
Build and maintain an AI platform: design services, deploy LLMs, optimize inference, and implement MLOps/RAG workflows for enterprise AI solutions.
The Manager: AI Architecture is responsible for designing, governing, and evolving the organization’s end-to-end Artificial Intelligence (AI) architecture. The role ensures AI solutions are scalable, secure, ethical,…
Build and deploy enterprise-grade AI systems using LLMs, Agentic AI, and RAG; integrate with cloud platforms and enterprise workflows while ensuring security, governance, and compliance.
Design and implement scalable AI/ML platforms on Databricks Lakehouse, leading data engineering, MLOps, and generative AI solutions for enterprise use cases.
Build and deploy enterprise-grade AI/LLM solutions using Snowflake, dbt Cloud, and Python, focusing on RAG, conversational AI, and MLOps pipelines for a large pharmacy retailer.
Lead Happiest Minds’ GenAI & Agentic AI practice, building Azure AI or AWS AI solutions, driving growth, pre-sales, and enterprise delivery with frameworks like LangGraph and CrewAI.
Build and maintain cloud infrastructure, CI/CD pipelines, and reliability for AI systems using AWS, Terraform, and GitHub Actions.
Build and deploy enterprise-grade AI solutions, including GenAI agents and RAG systems, using Python, cloud platforms (Azure/AWS), and frameworks like LangChain to improve customer experience and operational efficiency in an insurtech company.
Designs and leads enterprise-scale AI and cloud data platforms for an airline industry client, leveraging Azure services like Databricks, OpenAI, and Delta Lake.
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