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Designs scalable, event-driven IT systems and AI workflows, modeling business processes and data structures while collaborating with dev teams on microservices and API integrations.
Design enterprise AI solutions using generative agents, RAG, and ITSM/AIOps workflows to automate IT support, diagnostics, and operations with human-in-the-loop oversight.
Builds and optimizes multi-agent AI systems, RAG pipelines, and LLM integrations, focusing on production-grade prompt engineering, evaluation, and deployment.
Build and own the AI reasoning layer and agent orchestration framework for an enterprise GRC platform, shipping production-grade agentic systems that automate governance, risk, and compliance workflows.
Software Engineer (Full-Stack/Backend & Applied AI) Location: Ukraine, Armenia Department: Dream Team Workplace: remote Employment Type: full Description We are looking for a Software Engineer who operates at the…
Builds and deploys AI/ML models (focusing on speech recognition and legal insights) in production, optimizing performance, latency, and GPU usage while integrating LLMs and agentic workflows where applicable.
Build and deploy generative AI solutions using RAG, prompt engineering, and frameworks like LangChain on Google Cloud or Azure.
Build production-grade AI agents for corporate travel using LLMs, agent orchestration, and RAG pipelines to automate bookings and optimize travel programs for global enterprises.
Build and deploy enterprise-grade AI systems using LLMs, RAG, and Agentic AI frameworks to automate workflows and enhance customer experiences in banking.
Build, deploy, and scale AI applications using GenAI, LLMs, RAG, and classic ML on Google Cloud and Azure, while automating data pipelines and model monitoring for enterprise clients.
Build and scale production LLM and agentic systems for a healthcare specialty-care platform, including RAG pipelines, multi-agent workflows, and compliance-grade AI in Azure.
Build and scale production-grade LLM and agentic systems for a healthcare specialty-care platform, including RAG pipelines, multi-agent workflows, and compliance-ready AI in Azure.
Data & AI – Manager CFGI, founded in 2000, is a dynamic and fast-growing financial consulting firm, serving as the trusted partner to CFOs and their organizations. We help clients tackle complex challenges across…
Build and ship AI platform features on top of MariaDB’s relational database, integrating agent frameworks (LangChain) and vector search for enterprise RAG systems.
Build and deploy AI agents using LLMs, orchestration frameworks, and RAG pipelines to automate multi-step tasks for Morgan Stanley’s financial services platform.
Build and deploy AI-agent systems for enterprise clients, owning the full lifecycle from discovery to production using Python, FastAPI, and agent frameworks like Strands.
Build and deploy production-grade agentic AI systems for enterprise clients, including multi-agent orchestration, RAG pipelines, and LLMOps tooling.
Design and enforce AI security controls for an AI-first enterprise platform, including agent governance, model risk management, and ML-driven threat detection across 500+ customer environments.
Lead the architecture of production-grade agentic AI systems for reliability engineering at a major bank, designing autonomous agents that reason, analyze, and act across cloud infrastructure and application stacks.
Lead the design and scaling of SS&C’s enterprise AI agent platform, integrating MCP, multi-agent orchestration, and LLM workflows for financial services and healthcare clients.
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