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Remote Langchain Developer Jobs (NOW HIRING)

Collaborate with DevOps and backend teams to deploy scalable AI services within CoreStory's cloud ... Strong hands-on experience with LlamaIndex , LangChain , or similar orchestration frameworks.

Senior AI Application Engineer

Tampa, FL ยท On-site +1

$140K/yr

This role follows a hybrid, remote-flexible work model with opportunities for onsite collaboration ... Deep hands-on experience with LLM frameworks - LangChain, LangGraph, LlamaIndex, OpenAI/Anthropic ...

Senior AI Application Engineer

Tampa, FL ยท On-site +1

$120K - $140K/yr

This role follows a hybrid, remote-flexible work model with opportunities for onsite collaboration ... Deep hands-on experience with LLM frameworks -- LangChain, LangGraph, LlamaIndex, OpenAI/Anthropic ...

$190K - $220K/yr

... and LangChain. * Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom ... Remote

$94K - $124K/yr

... developer experience initiatives is considered an advantage. * Familiarity with LLMs, LangChain ... Fully remote contract opportunity within Europe. * Flexible working environment with significant ...

Senior AI Developer

Salt Lake City, UT ยท On-site +1

$52.75 - $69.75/hr

Experience with frameworks such as LangChain or LangGraph * Prior work in consulting, professional ... Remote employees will be expected to travel to an office periodically.

Create data pipelines and AI model context protocols, leveraging tools like MCP, LangChain, vector ... Contribute to platform growth by authoring SDKs, APIs, and comprehensive developer documentation.

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Remote Langchain Developer information

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How much do remote langchain developer jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for remote langchain developer in the United States is $52.84, according to ZipRecruiter salary data. Most workers in this role earn between $40.38 and $64.66 per hour, depending on experience, location, and employer.

How do Remote Langchain Developers typically collaborate with team members and stakeholders across different time zones?

Remote Langchain Developers often work as part of distributed teams, which requires strong communication and collaboration skills. They frequently use tools like Slack, Zoom, or project management platforms to coordinate with colleagues and share progress. Developers may need to adjust their schedules for occasional meetings or code reviews to accommodate team members in other time zones. Clear documentation and proactive updates are essential to ensure everyone stays aligned on project goals and timelines.

What are the key skills and qualifications needed to thrive as a Remote Langchain Developer, and why are they important?

To thrive as a Remote Langchain Developer, you need strong Python programming skills, experience with natural language processing (NLP), and a solid understanding of the LangChain framework and large language models. Familiarity with cloud platforms, REST APIs, and version control systems like Git is typically required, along with any relevant certifications in AI or cloud computing. Excellent problem-solving, self-motivation, and effective remote communication skills help set you apart in distributed teams. These skills ensure the efficient development of robust, scalable AI solutions while enabling seamless collaboration and innovation in a remote work environment.

What are Remote Langchain Developers?

Remote Langchain Developers are software professionals who specialize in building applications using the Langchain framework, which is designed to facilitate the development of language model-powered applications. They work from remote locations, collaborating with teams online to integrate large language models (LLMs) like OpenAI's GPT into various products and workflows. Their responsibilities typically include designing, coding, testing, and deploying solutions that leverage Langchain's capabilities for tasks such as data processing, chatbots, document analysis, and more. Remote Langchain Developers must be proficient in Python and have a strong understanding of AI, machine learning, and natural language processing concepts.
More about Remote Langchain Developer jobs
What cities are hiring for Remote Langchain Developer jobs? Cities with the most Remote Langchain Developer job openings:
What are the most commonly searched types of Langchain Developer jobs? The most popular types of Langchain Developer jobs are:
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What job categories do people searching Remote Langchain Developer jobs look for? The top searched job categories for Remote Langchain Developer jobs are:
Infographic showing various Remote Langchain Developer job openings in the United States as of July 2026, with employment types broken down into 85% Full Time, 3% Part Time, 1% Temporary, and 11% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $109,905 per year, or $52.8 per hour.
AI/ML Engineer

Full-time

Posted 24 days ago


Job description

FTI Defense is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

FTI Defense delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.


  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.
  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

 Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelorโ€™s or Masterโ€™s degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

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