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Build and test AI-powered airline tools using Python, LLMs, and agentic workflows; validate accuracy, safety, and performance of generative AI systems for aviation operations.
Design and build AI agent systems using LLMs, agent frameworks, and tool integrations to create scalable, reasoning-driven applications for a financial services firm.
Senior Data Scientist builds and deploys AI models—including LLMs and computer vision—to optimize oil production workflows using Python, PyTorch, and cloud GPUs.
Lead backend architecture for an AI platform, designing scalable LLM integrations and distributed systems while mentoring engineers and shaping technical strategy.
Build AI models and APIs for geospatial imagery, including LLMs, computer vision, and AI agents, using Python and ArcGIS tools.
Builds LLM-powered agents that turn natural language into data analysis, using Python, pandas, LangChain, and text-to-SQL toolkits to process CSV and database queries.
Lead the DevOps strategy for AI agent workflows, owning CI/CD pipelines, containerization with Docker/Helm, and Python-based automation to deploy and test non-deterministic AI systems.
Own and optimize GitLab CI/CD pipelines, Docker packaging, and Helm charts for Python microservices on Kubernetes, collaborating with cloud teams to streamline releases.
Build and deploy AI systems including LLMs, computer vision, and autonomous agents using Python, PyTorch, and LangChain, then productionize them with MLOps on cloud platforms.
Build and optimize GenAI systems using LLMs, prompt engineering, RAG, and agent workflows with frameworks like LangChain. Integrate APIs, vector databases, and external tools for scalable AI solutions.
Designs the architecture for self-learning AI agents and GenAI systems, focusing on orchestration, reasoning layers, and scalable agentic workflows.
Build and deploy multi-agent AI systems using LLM APIs (Bedrock, OpenAI, Mistral), LangGraph/LangChain, and AWS serverless tools; focus on execution, not design.
Build production-grade AI features like RAG pipelines and agentic workflows using Python, FastAPI, and vector stores; ship LLM-powered services end-to-end.
Build and deploy multi-agent AI systems using LLM APIs, agent frameworks, and AWS services, focusing on execution and integration rather than design.
Job Summary We are seeking an experienced AI Automation Engineering Manager to lead our AI and automation initiatives across the organization. This role is responsible for managing a team of AI Automation Engineers,…
Build and ship AI-powered features end-to-end: prototype LLM workflows in React/TypeScript and Python/Node, then take them to production across GuardPass’s security-training platform.
Build AI-powered systems using Python, FastAPI, and LLMs; develop agentic AI, RAG pipelines, and workflow automations; deploy on AWS.
Designs the architecture for self-learning AI agents and GenAI systems, focusing on orchestration, reasoning layers, and scalable production pipelines.
Build and ship AI-powered agentic applications using Python, LangChain/LangGraph, and vector databases; lead system design, DevOps, and team mentorship.
Build production-grade AI agents and LLM-powered features like chatbots and RAG systems using Python, FastAPI, and third-party models (OpenAI, Gemini, Claude).
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