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Lead Generative AI Engineer, VP
Lead the design and deployment of generative AI systems for Citi, including LLM fine-tuning, RAG pipelines, and AI governance frameworks on Google Vertex AI.
Data Scientist
Build and deploy AI/ML models and GenAI assistants using Python, LLMs, and vector databases; develop APIs and frontend interfaces to integrate AI solutions into products.
Full Stack Developer (Angular, .NET, SQL)
Build enterprise-grade web apps using Angular for the front end and .NET Core for back-end APIs and SQL databases, optimizing performance and collaborating with cross-functional teams.
AI Engineer (Managed Services)
Build and deploy enterprise LLM applications, RAG systems, and AI agents using open-source models (DeepSeek, Qwen, Kimi) and frameworks like LangChain and vLLM.
Forward Deployed Engineer - AI
A customer-facing engineer designs and builds AI solutions (agents, RAG pipelines, LLM integrations) while advising enterprises on AI governance, security, and trust—traveling 40% to embed with clients.
Forward Deployed Engineer - AI
A senior engineer embedded with enterprise clients to advise on AI governance, scope AI projects, and build production-ready solutions using LLMs and agentic workflows.
Python GenAI Developer
Build and maintain production-grade GenAI agents in Python, integrating LLM tool-calling, RAG pipelines, and real-time speech/data systems for enterprise clients.
AI Systems Architect and Builder
Design and deploy production-ready AI systems, including LLM apps, RAG pipelines, and voice AI, for clients across healthcare, ecommerce, travel, and other sectors.
AI Engineer
Build and deploy enterprise-grade AI systems, including LLM agents, retrieval pipelines, and AI gateways, using Python/TypeScript and modern AI engineering patterns.
Data Scientist (LLM/RAG, project based)
Design and deploy autonomous AI agents using LLM/RAG to automate media planning, ad buying, and financial audits for an ad-tech client, covering the full lifecycle from modeling to production.
AI Engineer
Build and deploy generative-AI solutions using LLMs, RAG, and AI agents in Python on AWS, integrating with enterprise systems for a U.S. client.
Senior Consultant, Anthropic AI Engineer
Senior consultant builds and deploys AI-powered workflows using Anthropic’s Claude, Python/JavaScript, RAG pipelines, and vector databases to automate enterprise processes for global clients.
Инженер по ИИ/AI Agent Engineer (LLM & Agentic Systems)
Builds and maintains robust LLM-based AI agents and RAG pipelines, designs multi-step reasoning workflows, and implements quality evaluation frameworks to ensure reliable, production-grade AI systems.
Staff AI Platform Engineer, Infrastructure Services
Build and scale SentinelOne’s AI Gateway infrastructure (Kong-based) to route, secure, and monitor AI coding assistant traffic, while operating self-hosted LLM stacks and driving reliability across Kubernetes and CI/CD systems.
Senior AI Platform Engineer, Infrastructure Services
Build and scale SentinelOne’s AI Gateway infrastructure (Kong-based) to route, secure, and monitor AI coding assistant traffic, while operating self-hosted LLM stacks and driving reliability across Kubernetes and CI/CD tooling.
AWS AI Agent Engineer
Build and deploy enterprise AI agents and multi-agent workflows on AWS using Bedrock, AgentCore, and serverless components, with a focus on reliability, cost control, and observability.
Agentic AI- Senior Software Engineer
Build and deploy AI agents, copilots, and RAG systems using LangChain, LangGraph, and vector databases; integrate them with enterprise tools and cloud platforms.
Lead AI Engineer/AI Platform Engineer
Build and scale an internal AI platform using LLMs, vector databases, and agent frameworks to automate engineering workflows and create AI assistants for sales, design, manufacturing, and leadership.
Developer GenAI
Build and optimize Generative AI solutions using LLMs, RAG pipelines, and agent frameworks like LangChain to automate business processes and integrate with external systems.
Software Engineer, Search & Retrieval Infrastructure
Build and optimize core search and retrieval infrastructure for Pinecone’s vector database, enabling scalable, high-quality AI applications with semantic and hybrid search capabilities.