26 to 50 of 206 Permanent LangGraph Jobs

experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks ...

experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks ...

Solid understanding of LLMs, Prompt engineering/tuning, Vector DBs (AstraDB, Pinecone, Weaviate etc), RAG pipelines (LlamaIndex, Haystack) and Agent/Workflow Orchestration (LangChain, LangGraph, CrewAI). Knowledge of SLM Finetuning and Distillation is a big advantage. Experience and knowledge of Agentic development platforms and experience building and delivering enterprise ...

understanding of CI/CD, Infrastructure as Code and release automation. Strong problem-solving, communication and stakeholder collaboration skills. Preferred Skills Experience with LangChain, LangGraph, Semantic Kernel, CrewAI or similar agent frameworks. Experience with Bedrock Knowledge Bases, vector databases such as OpenSearch, Pinecone or Weaviate, and embedding-based retrieval patterns. ...

Models (OpenAI, Anthropic, Gemini or open-source alternatives). Python and modern software engineering practices. AI APIs, SDKs and orchestration frameworks such as LangChain, LangGraph, LlamaIndex or similar. Retrieval-Augmented Generation (RAG), vector databases and semantic search. AI agents, workflow automation and orchestration. Cloud platforms such as AWS, Azure ...

Terraform, CloudFormation, or Pulumi). Working experience with LLM integration patterns, prompt engineering, or AI/ML application development. Familiarity with frameworks like LangChain, LangGraph, or similar orchestration tools. Nice to Have Skills: Experience with event-driven architectures (Kafka, EventBridge). Knowledge of vector databases and observability tools (Datadog, Splunk ...

just scripts (OOP, async, packaging, testing) Generative AI & LLM development - prompt engineering, fine-tuning, RAG pipelines, context window management Agentic AI frameworks - LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning - model development, training, evaluation, and deployment APIs & backend development - FastAPI, REST APIs, microservices architecture Vector databases ...

DevOps and business teams - Advise clients on AI platform capability and implementation strategy Tech environment: Python LLMs (prompt engineering, fine-tuning, RAG) LangChain/LangGraph Agent frameworks Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing enterprise ...

engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise ...

with engineering, data, DevOps and business teams to deliver end-to-end solutions. Tech environment Python, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure. What we're looking for Proven enterprise ...

engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise ...

Copilot Studio, Azure AI Foundry, Databricks Mosaic AI, Genie, MLflow) Design and tune RAG systems — embeddings, prompt engineering, evaluation Build AI agents using LangChain, LangGraph, AutoGen, and similar frameworks Deploy models via Azure OpenAI, Azure AI Foundry, and Docker Write clean, modular Python (OOP, Pydantic, PyTorch) following solid DevOps/ ...

validate, evaluate, and improve AI-generated outputs; understanding of AI limitations and responsible use Familiarity with agentic system concepts — awareness of orchestration frameworks (LangChain, LangGraph, or equivalent), RAG pipelines, and how full-stack applications connect to agent-based architecture; production experience preferred, conceptual understanding required ...

accelerate the software development lifecycle. Experience building intelligent systems and workflows: Autonomous systems Multi‐agent architectures Exposure to Generative AI tools and frameworks: LangGraph Crew AI Hugging Face OpenAI APIs Good to have: Experience with AngularJS. Proven track record leading full stack engineering teams across sectors. Experience building platforms ...

loops, tool-use, planning, and memory patterns. Hands-on experience (or strong aptitude to learn) building or integrating agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or the Model Context Protocol (MCP). Ability to design and expose Back End services as tools/functions callable by AI agents ...

analysis, and automated ticket enrichment. Knowledge of RAG, vector databases, embeddings, and AI-powered knowledge search. Python with AI frameworks such as LangChain, LangGraph, or OpenAI APIs. Education & Certifications: Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent experience. Preferred: Dynatrace Associate or Professional, Splunk Enterprise Certified Administrator ...

changing landscape of AI technologies. Experience AI Orchestration & Development: Expert‐level experience building complex LLM‐powered systems and multi‐agent workflows using frameworks like LangGraph, LangChain, AutoGen, or ADK. Artificial Intelligence & Machine Learning: Deep practical understanding of machine learning algorithms, natural language processing (NLP) techniques, and the optimization of large ...

similar tools. Experience evaluating and adopting emerging technologies, including build-vs-buy decisions. Hands-on experience building AI agents using frameworks such as LangGraph, LangChain, or LlamaIndex. Experience implementing Retrieval-Augmented Generation (RAG) solutions and governance controls for enterprise AI applications. Experience using agentic AI to automate engineering workflows such ...

models behave in production, not just in demos. Agentic Systems Design: Proven experience designing and deploying multi‐agent architectures and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI); tool‐use patterns, human‐in‐the‐loop workflows, and agentic safety at enterprise scale. AI/ML Engineering & MLOps: Full AI/ML lifecycle ...

models behave in production, not just in demos.* Agentic Systems Design:Proven experience designing and deploying multi-agent architectures and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI); tool-use patterns, human-in-the-loop workflows, and agentic safety at enterprise scale* AI/ML Engineering & MLOps: Full AI/ML lifecycle ...

environment. You'll ideally have experience with: Python and SQL Large Language Models (LLMs)Prompt engineering, fine-tuning and Retrieval-Augmented Generation (RAG) LangChain, LangGraph or similar agent frameworks Vector databases such as Pinecone, Chroma or FAISS AI Agents and Generative AI applications Cloud platforms including AWS and/ ...

doing: Designing end-to-end AI and LLM solution architectures Building scalable Agentic AI and multi-agent systems using frameworks such as LangGraph, AutoGen or Semantic Kernel Defining LLM integration strategies, including RAG, prompt engineering, fine-tuning, evaluation and guardrails Establishing MLOps/LLMOps best practices for production AI deployments ...

production environments Hands‐on experience designing and deploying agentic AI solutions in a production environment – non‐negotiable Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent – at production depth, not tutorial level Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management ...

observability tools. Hands-on experience with AI platforms such as OpenAI, Claude, or Vertex AI. Preferred Skills: Experience with agent frameworks such as LangGraph, AutoGen, or CrewAI. Experience designing multi-agent or distributed AI systems. Familiarity with enterprise-scale system integration. Experience optimizing AI workloads for cost and performance. Scope ...

genuine understanding of their capabilities, limitations and failure modes Practical familiarity with RAG architectures, vector databases and prompt engineering Exposure to agent frameworks (LangGraph, Claude Agent SDK, OpenAI SDK) or equivalent custom implementations An interest in LLM evaluation, debugging and observability Cloud platform experience (AWS, GCP or Azure ...