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Remote Python Llm Jobs in Leesburg, VA (NOW HIRING)

Anika Systems

AI Engineer

Leesburg, VA · Remote

This position is currently remote; however, in accordance with federal contract requirements and ... LLM based or Generative AI solutions. * Strong production experience in Python and TypeScript ...

Anika Systems

AI Engineer

Leesburg, VA · On-site +1

This position is currently remote; however, in accordance with federal contract requirements and ... focus on LLM based or GenerativeAI solutions. * Strong production experience in Python and ...

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All JobsPython Llm JobsRemote Python Llm JobsRemote Python Llm Jobs in Leesburg, VA

Remote Python Llm information

See Leesburg, VA salary details

$13

$59

$87

How much do remote python llm jobs pay per hour?

As of Jul 25, 2026, the average hourly pay for remote python llm in Leesburg, VA is $59.29, according to ZipRecruiter salary data. Most workers in this role earn between $48.89 and $67.36 per hour, depending on experience, location, and employer.

What remote jobs can you get with Python?

Remote Python jobs include roles such as software developer, data analyst, machine learning engineer, and automation engineer. These positions often require proficiency in Python programming, familiarity with frameworks like Django or Flask, and experience with cloud platforms or version control tools. Many of these jobs offer flexible schedules and can be performed from any location with internet access.

Will AI replace Python devs?

Remote Python developers are unlikely to be fully replaced by AI, as their role involves complex problem-solving, coding, and adapting to new requirements that AI tools currently cannot fully replicate. AI can assist by automating repetitive tasks and improving productivity, but human oversight and expertise remain essential for software development. Staying updated with new tools and skills can help Python developers remain valuable in an evolving tech environment.

What is a Remote Python LLM job?

A Remote Python LLM job typically involves working with large language models (LLMs) like GPT or similar AI technologies using the Python programming language, while operating remotely. Professionals in this role develop, fine-tune, and deploy machine learning models, especially those focused on natural language processing (NLP) tasks. Responsibilities may include building Python applications that integrate with LLMs, data preprocessing, and collaborating with teams across different locations. The remote aspect allows for flexible work arrangements and access to global opportunities.

What are some common collaboration methods used by Remote Python LLM engineers when working with cross-functional teams?

Remote Python LLM engineers frequently collaborate with data scientists, product managers, and other developers through virtual meetings, code reviews, and shared documentation platforms. Tools like Slack, GitHub, and Jira are often used to ensure smooth communication and project tracking, despite working across different time zones. Regular stand-ups and sprint planning sessions help align objectives and keep everyone updated on progress. Proactive communication and clear documentation are key to overcoming the challenges of remote, distributed teamwork in this role.

Is Python used in LLM?

Yes, Python is widely used in developing large language models (LLMs) and is a key skill for remote Python LLM roles. It provides extensive libraries and frameworks such as TensorFlow and PyTorch that facilitate model training, fine-tuning, and deployment.

What are the key skills and qualifications needed to thrive as a Remote Python LLM Engineer, and why are they important?

To thrive as a Remote Python LLM Engineer, you need strong proficiency in Python programming, experience with large language models (LLMs), and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and version control systems like Git is typically required. Excellent problem-solving abilities, self-motivation, and effective communication are crucial soft skills for remote collaboration and troubleshooting. These skills ensure you can develop, deploy, and maintain advanced language models efficiently while working independently in distributed teams.

Which LLM is good for Python coding?

For a Remote Python Llm role, models like OpenAI's GPT-4 and GPT-3.4 are widely used for Python coding due to their strong language understanding and code generation capabilities. Additionally, open-source models such as Meta's Llama 2 and EleutherAI's GPT-NeoX can be fine-tuned for specific coding tasks, making them suitable options for development environments requiring customization. Proficiency in integrating these models with APIs and understanding their limitations is essential for effective Python coding assistance.
What are popular job titles related to Remote Python Llm jobs in Leesburg, VA? For Remote Python Llm jobs in Leesburg, VA, the most frequently searched job titles are:
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What cities near Leesburg, VA are hiring for Remote Python Llm jobs? Cities near Leesburg, VA with the most Remote Python Llm job openings:
Remote Python Llm jobs near you
Infographic showing various Remote Python Llm job openings in Leesburg, VA as of July 2026, with employment types broken down into 58% Full Time, and 42% Contract. Highlights an 100% Remote job distribution, with an average salary of $123,332 per year, or $59.3 per hour.

Gen AI / Agentic Engineer

Interon IT Solutions

Chantilly, VA • Remote

Contractor

Posted 7 days ago

Job description

#W2 Role

Job Title: Gen AI / Agentic Engineer

Location: Remote 
Type: W2 Contract 
Experience: 10+ years overall IT, 2+ years GenAI/LLM

Job Summary

We are looking for a GenAI / Agentic Engineer to design, build, and deploy LLM-powered applications on AWS. This role is focused on real production engineering—APIs, RAG pipelines, agent workflows, evaluation, deployment, monitoring, and performance/cost tuning.

Responsibilities

  • Build and maintain LLM-powered backend services using Python and FastAPI (chat, search, summarization, Q&A).
  • Design and implement RAG pipelines end-to-end: ingestion, parsing, chunking, embeddings, indexing, retrieval, reranking, and grounded responses.
  • Develop agentic workflows for multi-step automation (tool calling, orchestration, state/memory, retries, audit logs).
  • Deploy and support GenAI workloads on AWS using ECS/Lambda, S3, SQS, DynamoDB/RDS, OpenSearch (or vector store), and related services.
  • Implement security and governance controls: auth, authorization, secrets, encryption, PII handling, and prompt-injection defenses.
  • Build evaluation and monitoring for quality, hallucination reduction, latency, and cost (test sets, regression checks, dashboards, alerts).
  • Work across full SDLC: design docs, estimates, coding, code reviews, CI/CD, testing, release, and production support.
  • Communicate architecture decisions clearly and explain tradeoffs (accuracy vs latency vs cost) to stakeholders.

Required Skills (Point-Based)

  • 10+ years overall IT experience with backend/API engineering and cloud deployments
  • 2+ years hands-on GenAI/LLM experience delivering real features (not just demos)
  • 6+ years strong Python (core Python, clean coding, debugging, packaging)
  • Experience with asyncio and concurrency (threads/async), plus profiling and performance tuning
  • Comfortable with stateful/long-running workflows: transaction handling, retries, idempotency, and failure recovery
  • 5+ years building REST APIs / microservices, strong API design and error handling
  • 5+ years with FastAPI (or similar) including middleware, dependency injection, background tasks
  • Experience implementing auth/security using JWT/OAuth, RBAC, secure configuration, secrets handling
  • Strong testing discipline using pytest (unit/integration tests, mocks, API contract testing)
  • Proven experience building RAG systems end-to-end: chunking strategies, embeddings, retrieval tuning, reranking, grounding/citations
  • Hands-on with RAG optimization: hybrid retrieval, metadata filters, top-k tuning, chunk tuning, reranking strategies
  • Experience with agentic patterns: tool calling, orchestration, memory/state, structured outputs, audit trails
  • Experience implementing guardrails: output schema enforcement (JSON), refusal handling, safety filters, prompt-injection defenses, PII masking
  • 5+ years AWS experience using ECS/Lambda, S3, SQS, DynamoDB/RDS (and related services)
  • Strong AWS security fundamentals: IAM, KMS, Secrets Manager, CloudWatch logs/metrics/alarms
  • Experience deploying LLM workloads via Amazon Bedrock (preferred) or SageMaker
  • Strong system design: scalability, caching, rate limiting, queues, resilience/failure handling
  • Ability to clearly explain GenAI architecture decisions and tradeoffs across accuracy/latency/cost

Nice to Have

  • LangChain / LangGraph / LlamaIndex (any)
  • OpenSearch vector search or vector DB experience (Pinecone/Weaviate/FAISS, etc.)
  • Docker, Terraform/CDK, CI/CD (GitHub Actions/Jenkins)
  • Experience in regulated environments (finance/healthcare/telecom) with governance controls