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Llm Engineer Remote Jobs in Reston, VA (NOW HIRING)

Eliassen Group

Lead AI Engineer

Rockville, MD · On-site +1

$99 - $110/hr

Hybrid 3 days onsite / 2 days remote in Rockville, MD Our client seeks a Lead AI Engineer to design ... Develop LLM-driven compliance reasoning and scalable RAG grounded in regulatory content.

Eliassen Group

Lead AI Engineer

Rockville, MD · On-site +1

$99 - $110/hr

Hybrid 3 days onsite / 2 days remote in Rockville, MD Our client seeks a Lead AI Engineer to design ... Develop LLM-driven compliance reasoning and scalable RAG grounded in regulatory content.

Sage

Senior Software Engineer I

Washington, DC · On-site +1

$111K - $128K/yr

Experience leveraging AI and LLM-powered features to enhance the platform. The Senior Software ... Work effectively in a remote capacity. Attend in person meetings and events several times a year ...

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All JobsLlm Engineer Remote JobsLlm Engineer Remote Jobs in Reston, VA

Llm Engineer Remote information

See Reston, VA salary details

$26

$55

$79

How much do llm engineer remote jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for llm engineer remote in Reston, VA is $55.80, according to ZipRecruiter salary data. Most workers in this role earn between $45.00 and $64.76 per hour, depending on experience, location, and employer.

What is the difference between Llm Engineer Remote vs Data Scientist Remote?

AspectLlm Engineer RemoteData Scientist Remote
Required CredentialsAdvanced degree in CS, ML, or related field; experience with NLP and deep learningDegree in CS, Statistics, or related; experience with data analysis and machine learning
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesData analysis, model development, reporting; across various industries
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, tech, e-commerce, and more

While both roles involve machine learning, Llm Engineers focus on developing large language models and NLP applications, often requiring deep expertise in AI research. Data Scientists analyze data to inform business decisions, with broader industry applications. The roles share some credentials but differ in focus and daily tasks.

What are some typical challenges faced by remote LLM Engineers when collaborating with cross-functional teams?

Remote LLM Engineers often work closely with data scientists, product managers, and software engineers to develop and deploy large language models. One common challenge is ensuring clear and consistent communication across different time zones and technical backgrounds, which can sometimes lead to misaligned project goals or delays. To overcome this, many teams rely on detailed documentation, regular virtual meetings, and collaborative project management tools. Building strong relationships remotely and proactively sharing updates can make collaboration smoother and more productive.

What are the key skills and qualifications needed to thrive as an LLM Engineer in a remote role, and why are they important?

To thrive as an LLM Engineer remotely, you need strong expertise in machine learning, natural language processing, and proficiency with programming languages such as Python, often supported by a degree in computer science or related fields. Familiarity with frameworks like PyTorch or TensorFlow, experience with cloud platforms (AWS, GCP), and knowledge of large language model architectures are commonly required. Excellent problem-solving skills, self-motivation, and effective remote communication make candidates stand out. These capabilities are crucial for developing, deploying, and maintaining advanced language models while collaborating efficiently with distributed teams.

What is an LLM Engineer (Remote)?

An LLM Engineer, or Large Language Model Engineer, is a professional who designs, develops, and optimizes applications using advanced AI language models such as GPT-4 or similar technologies. Working remotely, they are responsible for integrating these models into products, fine-tuning them for specific tasks, and ensuring their performance and reliability. LLM Engineers often collaborate with data scientists, software developers, and product managers to create solutions in areas like chatbots, content generation, and natural language processing. Their work requires a strong background in machine learning, programming, and cloud computing.
What are popular job titles related to Llm Engineer Remote jobs in Reston, VA? For Llm Engineer Remote jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Llm Engineer Remote jobs in Reston, VA look for? The top searched job categories for Llm Engineer Remote jobs in Reston, VA are:
What cities near Reston, VA are hiring for Llm Engineer Remote jobs? Cities near Reston, VA with the most Llm Engineer Remote job openings:
Llm Engineer Remote jobs near you
Infographic showing various Llm Engineer Remote job openings in Reston, VA as of June 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 100% Remote job distribution, with an average salary of $116,054 per year, or $55.8 per hour.

Gen AI / Agentic Engineer

Interon IT Solutions

Chantilly, VA • Remote

Contractor

Posted 21 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