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Software Engineer (Full-Stack/Backend & Applied AI)
Builds scalable microservices and agentic workflows using Python, integrating LLMs and RAG pipelines into production systems while ensuring AI reliability and engineering quality.
Mid-Level Data Engineer
Builds and maintains cloud data pipelines and platforms (BigQuery/Fabric) using medallion architecture, semantic layers, and ELT/ETL workflows to enable reliable, AI-ready data for analytics and machine learning.
AI Technical Manager
Join our Team About this opportunity: Join our team at Ericsson as a AI Technical Manager, a critical role that drives our end-to-end technical solutions based on customer specifications and burgeoning business…
GTM Engineer (m/f/d)
The Role This is a hands-on engineering role at the intersection of GTM and AI. You build the systems that help Sales, Marketing, and CS work on the right things: automated lead identification, scoring models that flag…
Senior Backend Engineer (Integrations & RAG)
Build and scale distributed backend services in Go and Django to power an AI-native research platform, handling high-volume data and integrating retrieval-augmented generation (RAG) workflows.
Data and AI Engineer
Design and build AI solutions, agents, and LLM-based apps for enterprise financial services, integrating with systems and APIs.
Mid-Level Python Developer (Backend)
Build and maintain high-concurrency Python backend systems using async FastAPI, PostgreSQL, and AI-assisted workflows; own features from design to deployment.
Mid-Level Python Developer (GenAI)
Build and deploy production-grade GenAI features like agent workflows, RAG pipelines, and LLM integrations using Python, FastAPI, and vector databases.
Associate AI Engineer
Builds and deploys AI/ML and Generative AI models using Python, TensorFlow, and cloud platforms to solve business problems and enable data-driven decisions.
Senior AI Engineer
Senior AI Engineer builds enterprise AI solutions like chatbots and copilots, integrates LLMs via APIs, and advises on secure AI adoption across a large organization.
AI Engineer (Mid-Level)
Build and ship production LLM-based agent systems and RAG pipelines for regulated domains like healthcare, fintech, and logistics, working full-stack in Python/TypeScript on AWS/GCP.
Gen AI Architect
Designs and leads enterprise-scale GenAI/AI architectures, from strategy to production deployment, focusing on RAG pipelines, multi-agent systems, and cloud-native AI solutions while ensuring scalability, security, and business alignment.
Gen AI ML Engineer
Design and deploy scalable GenAI and ML models, including RAG pipelines and multi-agent systems, using frameworks like LangChain and Hugging Face, while collaborating with cross-functional teams to integrate AI solutions into enterprise products.
EG Senior AI Architect
Design and lead enterprise-scale AI and data architectures, integrating LLMs, RAG, and agentic systems with cloud platforms like AWS, Azure, and Google Cloud.
AI Platform Engineer: Build Scalable AI Foundations
Build and scale the infrastructure for AI products like LLM apps, RAG systems, and agents using Python, cloud platforms, and vector databases.
Lead AI Engineer
Lead the design and build of Mastercard’s next-gen agentic AI systems, including orchestration, governance, and cloud-native platforms that power enterprise-scale AI applications across the business.
Full Stack AI Engineer
Build and deploy AI-powered healthcare solutions using LLMs, RAG, and Azure services to automate document processing and enhance clinical insights for payors and providers.
AI/ML Engineer
Build production-grade AI architecture blueprints and open-source Quickstarts with Python, PyTorch, and Kubernetes, focusing on enterprise deployment, security, and regulated environments.
Full Stack Engineer (Agentic AI)
Build AI-powered multi-agent systems and full-stack applications using Node.js, React, and TypeScript, integrating LLMs, vector databases, and observability tools like Langfuse for agentic workflows and dashboards.
AI Solutions Engineer
Design and deploy AI-powered applications, agents, and automation solutions on Azure to improve efficiency and customer experiences in carbon management.