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Designs and implements security controls for autonomous AI systems, RAG pipelines, and agentic workflows to prevent misuse, data leakage, and compliance violations in a regulated federal healthcare environment.
Senior AI engineer builds and optimizes agentic AI systems that analyze legacy software codebases for federal healthcare modernization, using LLMs, RAG, and autonomous agents to deliver explainable, traceable answers.
We are looking for a Senior AI/ML Engineer to join our engineering team and work on challenging AI/ML projects for international clients. This role is a great fit for an experienced engineer who combines strong Machine…
The Senior AI Engineer will design and implement evaluation pipelines, observability frameworks, and quality metrics for AI-powered features within a board intelligence platform. The role involves hands-on development in Python or C#/.NET to ensure LLM-based systems are reliable, cost-effective, and performant in production.
Anor Bank приглашает Senior AI Engineer Мы ищем опытного Senior AI Engineer , который будет разрабатывать и внедрять современные AI-решения для автоматизации бизнес-процессов и создания интеллектуальных продуктов.…
This role involves architecting and building autonomous AI agents and RAG pipelines to automate enterprise workflows for non-technical users. The engineer will work on the full stack of LLM orchestration, tool-use, and production deployment using technologies like Python, Spark, and various vector databases.
Builds and deploys core AI platform components for NICE, including agent orchestration, RAG pipelines, and LLM integration, enabling enterprise automation across systems like Salesforce, ServiceNow, and Azure services.
Designs and maintains production-grade data pipelines for AI/ML and RAG systems, focusing on ingestion, transformation, and vector search infrastructure (pgvector, Pinecone). Ensures data governance, compliance, and quality for regulated sectors like healthcare and government.
Senior Data Engineer building AI-ready data pipelines, RAG/vector search infrastructure, and data governance solutions using Python, Airflow, Kafka, and vector databases like pgvector and Pinecone.
AI DevOps/MLOps Engineer building and automating CI/CD pipelines for LLM and AI model deployment on Kubernetes/OpenShift, using Jenkins, Docker, Terraform, and model serving platforms for a Singapore-based bank.
DevOps Engineer for AI systems: designs and maintains CI/CD pipelines, observability, and cost/performance management for LLM/agentic applications, bridging POCs to production-grade deployments with Kubernetes and Terraform.
Senior Golang engineer designing scalable backend microservices and integrating AI/LLM capabilities into POS and SaaS platforms.
The Senior Machine Learning Engineer will develop and deploy production-grade GenAI applications, including LLM-based solutions, RAG systems, and agentic workflows, to support various business lines at RBC. The role involves building scalable ML infrastructure and collaborating with cross-functional teams to deliver impactful AI solutions.
MLOps + DevOps Engineer responsible for operating an AI-native platform with agentic systems, ML workloads, and backend services on AWS. Core technologies include AWS (EKS, Lambda, Bedrock, SageMaker), Kubernetes, Kafka, Terraform, and observability stacks like Grafana, Prometheus, and OpenTelemetry.
Designs and leads enterprise-scale AI/ML and Generative AI solutions, focusing on LLMs, RAG architectures, and cloud-based deployments while mentoring teams and ensuring governance.
AI/ML Engineer designing and deploying end-to-end LLM and RAG pipelines, MLOps workflows, and data integration systems on AWS (SageMaker, Bedrock, Lambda, EKS) for enterprise clients in regulated industries.
Design, build, and maintain AI agents and RAG pipelines using LLMs (Claude, OpenAI, Bedrock), Python (Django/FastAPI), vector databases, and AWS for a remote data consultancy.
The Senior AI/ML Engineer will design and deploy enterprise-scale AI systems, including intelligent agents and copilots, using Python, LLMs, and RAG architectures. The role focuses on building scalable, production-grade AI services within a cloud-native environment.
Required Skills 8–11 years of software engineering experience Strong expertise in TypeScript and Node.js Strong programming experience in Python Hands-on experience with LLMs and Generative AI Experience with AI…
Develop, fine-tune, and deploy LLMs and ML systems for a B2B SaaS org-chart platform, building RAG pipelines, MCP servers, and Python microservices integrated into the web and cloud stack.
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