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

Tata Consultancy Service Limited

Engineer

Mclean, VA · On-site

$100K - $120K/yr

Build, fine-tune, and optimize LLM-based applications, ensuring high accuracy, reliability, and ... Work with APIs, microservices, and backend systems to embed GenAI features into applications at ...

Expression

Senior AI Platforms Engineer

Washington, DC

$180K - $210K/yr

Architect, deliver, and optimize production-grade LLM services, agent workflows, orchestration ... Develop high-performance Python APIs and scalable backend services using FastAPI, asynchronous ...

Trilagen

Agentic AI Engineer

Bethesda, MD · On-site

We need engineer's who can own the entire agent stack: a production frontend, a robust backend, a properly secured API and identity layer, a memory architecture that scales, and LLM integrations that ...

Expression

Senior AI Platforms Engineer

Washington, DC · On-site

$180K - $210K/yr

Architect, deliver, and optimize production-grade LLM services, agent workflows, orchestration ... Develop high-performance Python APIs and scalable backend services using FastAPI, asynchronous ...

Trilagen

Agentic AI Engineer

Bethesda, MD · On-site

We need engineer's who can own the entire agent stack: a production frontend, a robust backend, a properly secured API and identity layer, a memory architecture that scales, and LLM integrations that ...

Trilagen

Agentic AI Engineer

Mclean, VA · On-site

We need engineer's who can own the entire agent stack: a production frontend, a robust backend, a properly secured API and identity layer, a memory architecture that scales, and LLM integrations that ...

Trilagen

Agentic AI Engineer

Bethesda, MD · On-site

We need engineer's who can own the entire agent stack: a production frontend, a robust backend, a properly secured API and identity layer, a memory architecture that scales, and LLM integrations that ...

Trilagen

Agentic AI Engineer

Mclean, VA · On-site

We need engineer's who can own the entire agent stack: a production frontend, a robust backend, a properly secured API and identity layer, a memory architecture that scales, and LLM integrations that ...

Carlyle

Forward Deployed Product Engineer

Washington, DC · On-site

$210 - $220/hr

The Vice President owns a portfolio of products end-to-end--across backend services, modern frontends, data pipelines, and LLM-based workflows--and sets the technical direction, engineering standards ...

InterImage

AI/ML Software Developer

Arlington, VA · On-site

... LLM/GenAI technologies into production environments. Key Responsibilities Full Stack Development ... Build scalable backend services using Python frameworks (e.g., Flask, FastAPI, Django) * Develop ...

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

Llm Backend Engineer information

See Reston, VA salary details

$62.9K

$153.6K

$207K

How much do llm backend engineer jobs pay per year?

As of Aug 12, 2026, the average yearly pay for llm backend engineer in Reston, VA is $153,620.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,000.00 and $178,900.00 per year, depending on experience, location, and employer.

What are some common challenges faced by LLM backend engineers when deploying large language models in production?

LLM Backend Engineers often encounter challenges such as optimizing inference latency, managing high resource consumption, and ensuring scalability for production workloads. Balancing model performance with cost efficiency requires careful selection of hardware, batching strategies, and model quantization techniques. Additionally, they must address security and privacy concerns associated with handling sensitive data processed by the models. Collaboration with data scientists and DevOps teams is essential to streamline model updates and monitor system health.

What is an LLM backend engineer?

LLM Backend Engineers are software engineers who specialize in designing, building, and optimizing the backend infrastructure that supports large language models (LLMs) like GPT-4. They focus on integrating LLMs into products and services, ensuring scalable APIs, managing data pipelines, and optimizing inference performance. Their work often involves deploying models in cloud environments, monitoring system reliability, and collaborating with AI researchers to bring advancements into production. LLM Backend Engineers play a critical role in making AI-powered applications robust, efficient, and accessible to end users.

What are the key skills and qualifications needed to thrive as an LLM backend engineer?

To thrive as an LLM Backend Engineer, you need a solid foundation in software engineering, backend architecture, and experience working with large language models, typically supported by a degree in computer science or a related field. Proficiency with programming languages like Python or Java, cloud platforms (AWS, GCP, Azure), and machine learning frameworks such as TensorFlow or PyTorch is essential, along with familiarity with APIs and containerization tools like Docker or Kubernetes. Strong problem-solving, collaboration, and communication skills distinguish top performers in this role. These skills ensure robust, scalable, and efficient deployment of LLM-powered applications while enabling effective teamwork and innovation.
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Llm Backend Engineer jobs near you
Infographic showing various Llm Backend Engineer job openings in Reston, VA as of August 2026, with employment types broken down into 86% Full Time, 9% Part Time, and 5% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $153,620 per year, or $73.9 per hour.

Gen AI / Agentic Engineer

Interon IT Solutions

Chantilly, VA • Remote

Contractor

Re-posted 24 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