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Job Description Ready to take your career global? Make your mark at one of the biggest names in payments. We are seeking a highly skilled and forward-thinking AI Engineer to join our AI Engineering team. This role is…
What You'll Actually Do Design, build and deploy AI agents and multi-agent pipelines for B2B clients across sales, support, and operations Architect integrations between LLM layers, voice AI (VoIP/SIP), CRMs, and…
Line of Service Advisory Industry/Sector FS X-Sector Specialism Operations Management Level Manager Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced…
Senior AI/ML Engineer on Nivoda's Discovery Pod, building and running the ranking, recommendation, and search systems for its diamond and gemstone marketplace — including embedding-based retrieval, learning-to-rank, LLM-powered contextual/conversational search, and image-embedding search — owning models end to end on AWS/OpenSearch production infrastructure.
A hands-on, ~80% customer-facing architect role at an AWS Premier consulting partner: designing cost-efficient cloud and generative-AI architectures for startup clients, taking LLM/agent solutions from POC to production on AWS (Bedrock, RAG, agents), and driving FinOps optimization. Core stack: AWS, Terraform/CDK, Python/TypeScript.
Builds internal AI agents, data pipelines (BigQuery/Postgres), automation workflows, and internal tools for a performance-marketing agency in Bogotá that is turning into a software company. Core stack: Python, solid SQL, LLM APIs, REST integrations, and cloud deploys with Docker/Cloud Run/Cloudflare.
Senior full-stack engineer (hybrid in Cork, Limerick or Dublin) building and productionizing LLM applications — RAG pipelines, multi-agent workflows, Text-to-SQL — into secure, scalable services. Core stack: Python/FastAPI backends, React/Next.js frontends, PostgreSQL with vector search, and Docker/Kubernetes/Terraform on AWS/Azure/GCP.
Senior Data Scientist at a federal IT contractor who leads advanced analytics: framing business problems, building and validating statistical/ML models, and productionizing them into dashboards and executive-ready insights. Core stack is Python/R, SQL, scikit-learn, PyTorch/TensorFlow, Databricks, AWS SageMaker/Azure ML, Snowflake, and GenAI/RAG tooling.
Senior Manager role at Adobe in Bangalore leading a blended AI engineering team that builds an agentic AI platform (LLM orchestration, RAG, MCP/tooling) and the marketing solutions running on it. The manager owns roadmap, delivery, and quality across platform, applied-AI, and data engineering, with core tech in Python and cloud-native, containerized delivery.
Works as an AI & Data Solutions Architect on ICT projects focused on governance, cybersecurity and AI, fully remote with planned trips to Milan or Bologna. Day-to-day work centers on RAG, Python, FastAPI, SQL/PostgreSQL, pgvector, Redis and MLOps on AWS or Azure.
Cross River, a fintech building embedded payments, cards, and lending infrastructure, seeks a senior engineer in Jerusalem (hybrid, 3 days/week in office) to build its LLM-based agentic platform: Python/Node.js services, MCP servers linking AI agents to banking systems, and React interfaces. Requires Hebrew/English fluency and availability for some US hours.
Freelance senior DevOps/DBRE engineer joining a Cloud Platform Engineering team that runs 2500+ database services across Aiven, MongoDB Atlas and GCP. Work spans Python automation tools, Terraform infrastructure, GCP integration, FinOps cost optimization, resilience, and advanced administration of PostgreSQL, MySQL, MongoDB and related data stores.
Full-stack engineer (Member of Technical Staff) owning features end to end for an AI-native platform that helps healthcare practices run their operations. Day to day you build AI agents for clinic workflows (insurance, intake, claims), ship web/mobile features, and own services in production using Python/TypeScript, React/Next.js, PostgreSQL, AWS, Temporal and LLM tooling like Claude Code.
Hands-on staff-level technical lead for a product domain within a consumer lending platform, owning architecture and delivery of secure, scalable cloud-native services (microservices, APIs, event-driven workflows) on AWS. The role also integrates AI/LLM capabilities safely under fintech compliance, security, and data-privacy constraints, while mentoring SDEs and senior engineers.
About Avalon Healthcare Solutions : Avalon Healthcare Solutions is the nation’s leader in diagnostic intelligence, uniquely focused on transforming the role of diagnostic testing across the healthcare ecosystem. Our…
Builds, deploys, and optimizes machine learning, deep learning, and generative AI models — including agentic workflows, RAG, and MLOps pipelines — to power automation, personalization, and decision-making across Global Payments' fintech platforms, using Python, TensorFlow/PyTorch, GCP Vertex AI, AWS Bedrock/SageMaker, LangChain, and vector databases.
A founding Lead Data Engineer will architect and scale the data infrastructure for an AI assistant platform — building real-time and batch pipelines, analytics and vector-search systems, and setting the standards for the future data team. Core stack includes Python, PostgreSQL/NoSQL, Spark, Airflow, Kafka and vector databases.
Senior full-stack software engineer (Denver, on-site) building RAG-based AI features and high-throughput Java/Spring Boot microservices. Day to day involves designing LLM retrieval pipelines, deploying containerized services on AWS EKS with Helm, and working with Kafka, vector databases, and NoSQL stores like MongoDB and Redis.
Senior full-stack engineer who architects and ships enterprise Generative AI platforms and agentic systems end to end — owning a Python/TypeScript backend (FastAPI/NestJS, RAG pipelines, PostgreSQL and vector DBs) plus the consuming React/Next.js frontends, with self-managed Docker and CI/CD deployments.
Backend engineer on Capgemini's Data & AI team in Madrid, building and shipping GenAI applications: REST/GraphQL microservices that integrate LLMs (Azure OpenAI, OpenAI, Vertex AI, Bedrock), RAG pipelines, and agent orchestration (LangChain, LlamaIndex, Semantic Kernel) on Azure/AWS/GCP with CI/CD, containers, and LLMOps practices.
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