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Build and deploy production-grade generative AI systems for insurance workflows using LLMs, LangGraph, FastAPI, and Azure/Databricks.
Build AI-powered analytics tools for Ford’s mobility data, using full-stack development, GCP/Terraform, and LLM-driven agentic workflows to automate industrial decision-making.
Lead the architecture and delivery of enterprise agentic AI systems using LLMs, orchestration frameworks, and cloud-native MLOps to automate and enhance business operations.
Working with Us Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens…
We are seeking a highly skilled and experienced Tech Lead to join our AI innovative team. This role requires a strong background in hands-on coding, excellent design thinking, and superior problem-solving abilities.…
Builds and optimizes AI/ML systems using Python, C++, and big-data tools like Spark and Langchain to power Cadence’s core products.
Designs and advises clients on secure GenAI or Computer Vision solutions, running discovery workshops and mapping workflows to scalable architectures under high-security constraints.
Own AI agent-based products for B2SMB marketing, writing specs, building prototypes, and iterating on prompts and retrieval to ship non-deterministic features.
Build and deploy multi-agent AI systems for global financial markets, using Python, FastAPI, and frameworks like LangGraph and CrewAI.
Architect and implement generative AI solutions on SAP BTP, designing RAG pipelines, knowledge graphs, and LangChain orchestration to embed LLMs into enterprise SAP applications.
Build and deploy AI models and GenAI agents using Python, Azure, and LLM APIs to automate decisions and enhance financial products in a hybrid role.
Lead AI engineering for generative-AI copilots and RAG systems in a regulated financial-services environment, building production-grade Python/LLM pipelines on Azure.
Build agentic AI workflows in Python to automate corporate IT reliability tasks like incident triage, root-cause analysis, and remediation, using LLMs, RAG, and agent frameworks.
Build and deploy AI/ML models and GenAI copilots to optimize Amgen’s global supply chain, integrating LLMs, vector databases, and orchestration frameworks like LangChain to automate decisions and improve efficiency.
Build and deploy AI-first contract intelligence features using LLMs, RAG, agentic workflows, and knowledge graphs to automate and accelerate deal-making for enterprise customers.
Builds and deploys production-grade agentic AI systems (LLMs, RAG, orchestration) for American Express’s global commercial services, integrating with cloud-native stacks (Go/TypeScript/Python, AWS/GCP, Kafka, Kubernetes) to enhance customer-facing financial solutions.
Build production-ready AI features using Azure OpenAI, RAG pipelines, and MCP agents to enhance SaaS workflows like onboarding and data intake.
Build production-ready GenAI apps and reusable AI assets using RAG, Langchain/Langgraph, and Azure Cloud, while collaborating with cross-functional teams.
Build and scale AI agents and reusable components for automation, using Python, LLM APIs, and cloud-native tools to productionize AI systems and optimize performance.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, then integrate them into enterprise systems with clean, testable code and CI/CD.
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