ZipRecruiter

Log In

2

Remote Python Llm Jobs in Washington (NOW HIRING)

10a Labs

AI Red Teamer

Washington, DC · On-site +1

$70K - $90K/yr

Is comfortable scripting basic tests (Python, Bash, or similar) and working in Jupyter or prompt ... Fully remote (U.S.-based) with flexible hours. * Comprehensive health, dental, and vision.

Capital One

Distinguished AI Engineer (Remote)

Mclean, VA · On-site +1

LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or ... Remote (Regardless of Location): $244,700 - $279,200 for Distinguished AI Engineer McLean, VA: $269 ...

Capital One

Distinguished AI Engineer (Remote)

Mclean, VA · On-site +1

LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or ... Remote (Regardless of Location): $244,700 - $279,200 for Distinguished AI Engineer McLean, VA: $269 ...

next page

Showing results 1-20

People also search for

All JobsRemote Python Llm JobsRemote Python Llm Jobs in Washington

Remote Python Llm information

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.

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.

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 popular job titles related to Remote Python Llm jobs in Washington? For Remote Python Llm jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Remote Python Llm jobs in Washington look for? The top searched job categories for Remote Python Llm jobs in Washington are:
What cities in Washington are hiring for Remote Python Llm jobs? Cities in Washington with the most Remote Python Llm job openings:
Remote Python Llm jobs near you

Gen AI / Agentic Engineer

Interon IT Solutions

Chantilly, VA • Remote

Contractor

Posted 9 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