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Internship Langchain Developer Jobs in Washington

Internship, academic project, research, or personal project experience in software development ... AI/ML concepts or exposure to tools such as OpenAI APIs, LangChain, vector databases, or LLM ...

Internship, academic project, research, or personal project experience in software development ... AI/ML concepts or exposure to tools such as OpenAI APIs, LangChain, vector databases, or LLM ...

Internship, academic project, research, or personal project experience in software development ... AI/ML concepts or exposure to tools such as OpenAI APIs, LangChain, vector databases, or LLM ...

Internship Langchain Developer information

What are Internship Langchain Developers?

Internship Langchain Developers are students or early-career professionals who work in a temporary, learning-focused role, specifically developing applications using LangChain, a framework for building applications powered by language models. These interns help design, code, and test solutions that integrate large language models with external data sources and tools. The role provides practical experience in AI, natural language processing, and software development while working on real-world projects. Interns often collaborate with experienced engineers and receive mentorship to develop their technical and problem-solving skills.

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

To thrive as an Internship Langchain Developer, you need a solid understanding of Python programming, basic knowledge of natural language processing (NLP), and a familiarity with machine learning concepts. Experience with tools such as LangChain, OpenAI APIs, and version control systems like Git is typically required. Strong problem-solving skills, eagerness to learn, and effective communication set standout candidates apart. These skills and qualities are crucial for building effective language-based applications, collaborating with teams, and adapting to a fast-evolving AI landscape.

What kinds of projects can an Internship Langchain Developer expect to work on, and how do these projects contribute to skill development?

As an Internship Langchain Developer, you can expect to work on projects involving the integration of large language models (LLMs) with various data sources and APIs, such as building chatbots, automating document analysis, or developing knowledge retrieval pipelines. These projects are usually collaborative, requiring you to work closely with senior developers, data scientists, and sometimes product managers. This hands-on experience helps you develop practical skills in Python, prompt engineering, and leveraging frameworks like Langchain, while also improving your problem-solving abilities in real-world scenarios. Additionally, you’ll learn best practices for deploying and maintaining AI-powered applications, which can be valuable for pursuing advanced roles in AI development.

What is the difference between Internship Langchain Developer vs Junior AI Developer?

AspectInternship Langchain DeveloperJunior AI Developer
Required CredentialsEnrolled in or recent graduate of CS, AI, or related fieldBachelor's degree in CS, AI, or related field
Work EnvironmentInternship setting, mentorship, project-basedEntry-level position, collaborative team environment
Employer & Industry UsageTech companies, startups focusing on NLP and AITech firms, AI startups, research labs
Common Search & ComparisonYesYes

The main difference between an Internship Langchain Developer and a Junior AI Developer lies in experience level and employment status. Internships are typically temporary, mentorship-focused roles for students or recent graduates, while Junior AI Developers are entry-level full-time employees. Both roles involve working with AI and NLP technologies, but internships often emphasize learning and skill development, whereas junior roles focus on contributing to ongoing projects.

What are the most commonly searched types of Langchain Developer jobs in Washington? The most popular types of Langchain Developer jobs in Washington are:
What job categories do people searching Internship Langchain Developer jobs in Washington look for? The top searched job categories for Internship Langchain Developer jobs in Washington are:
What cities in Washington are hiring for Internship Langchain Developer jobs? Cities in Washington with the most Internship Langchain Developer job openings:
Infographic showing various Internship Langchain Developer job openings in Washington as of July 2026, with employment types broken down into 82% Full Time, 5% Part Time, 1% Temporary, and 12% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.
Federal AI Solutions Engineer (Entry Level)

Federal AI Solutions Engineer (Entry Level)

A-TEK Inc.

Mclean, VA

$85K - $105K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 17 days ago


Job description

A-TEK is seeking an early-career Federal AI Solutions Engineer to support the design, development, and deployment of mission-focused AI and cloud solutions across AWS and Azure environments. This role is ideal for recent graduates with a strong academic foundation in Artificial Intelligence, Machine Learning, software engineering, and cloud technologies who are eager to apply their skills to real-world federal mission challenges.

The engineer will work alongside senior architects and engineers to develop AI-enabled applications, cloud-native solutions, automation workflows, and rapid prototypes that support A-TEK's DigitalShift innovation initiatives.

This is a hybrid role based in McLean, VA. No visa sponsorship is available for this role. This role requires the ability to obtain and retain a public trust level security clearance.

Key Responsibilities

AI Solution Development

  • Assist in the design, development, and deployment of AI-powered applications and prototypes using:
    • AWS Bedrock
    • Azure OpenAI
    • LangChain, LlamaIndex, Semantic Kernel, CrewAI, or similar frameworks
  • Develop and test prompt engineering strategies, retrieval-augmented generation (RAG) workflows, and AI agent capabilities.
  • Support integration of AI solutions with APIs, enterprise systems, and cloud services.

Cloud Engineering

  • Build and maintain cloud-based environments in AWS and Azure.
  • Assist with infrastructure deployment using Infrastructure-as-Code tools such as Terraform, AWS CDK, or Bicep.
  • Support containerized deployments using ECS, EKS, or AKS.
  • Participate in CI/CD implementation and cloud automation efforts.

Technical Support & Innovation

  • Support senior engineers in troubleshooting cloud, AI, and data integration challenges.
  • Assist in developing reusable templates, accelerators, and reference architectures.
  • Participate in rapid prototyping efforts that demonstrate mission value for federal customers.

Collaboration & Knowledge Sharing

  • Collaborate with Cloud, Cybersecurity, Data Intelligence, and Agile Engineering teams.
  • Contribute to technical documentation, architecture diagrams, and knowledge-sharing initiatives.
  • Stay current with emerging AI, machine learning, and cloud technologies.

Security & Compliance

  • Support implementation of solutions that align with:
    • NIST AI Risk Management Framework (AI RMF)
    • FedRAMP requirements
    • Zero Trust principles
    • Secure coding and responsible AI practices

Required Qualifications

Education (Required)

Bachelor's degree in Computer Science with a concentration, specialization, minor, or significant coursework in Artificial Intelligence, Machine Learning, Data Science, or a closely related field.

Experience

  • 0-2 years of professional software engineering, AI/ML, or cloud development experience.
  • Relevant internships, research projects, capstone projects, graduate assistantships, or co-op experience may be substituted for professional experience.
  • Demonstrated programming experience in Python through coursework, projects, internships, or employment.

Technical Skills

  • Foundational understanding of machine learning, generative AI, and large language models.
  • Experience using cloud platforms (AWS or Azure) through coursework, internships, certifications, or projects.
  • Familiarity with:
    • REST APIs
    • Git version control
    • Containerization concepts
    • Data pipelines and databases
  • Understanding of prompt engineering, RAG concepts, or AI agents through academic or personal projects.
  • Strong analytical and problem-solving skills.

Certifications

One of the following is preferred within the first year of employment:

  • AWS Certified Cloud Practitioner or AWS Solutions Architect Associate
  • Microsoft Azure Fundamentals (AZ-900) or Azure AI Fundamentals (AI-900)

Preferred Qualifications

  • Academic or project experience with:
    • LangChain
    • LlamaIndex
    • Semantic Kernel
    • CrewAI
  • Exposure to vector databases such as Pinecone, Weaviate, FAISS, or Milvus.
  • Experience building AI, machine learning, or cloud-based capstone projects.
  • Familiarity with DevOps, MLOps, or CI/CD concepts.
  • Interest in federal government missions and emerging AI technologies.

Compensation

Salary Range

$85,000 - $105,000 annually

Salary will be determined based on education, certifications, internship experience, technical proficiency, and security clearance eligibility.

Benefits

  • Medical, Dental, and Vision Insurance
  • 401(k) with Employer Match
  • Paid Time Off and Federal Holidays
  • Professional Development and Certification Reimbursement
  • Career Growth and Mentorship Opportunities