GenAI Engineer (US)

Latitude

Seattle (WA)

In loco

USD 130.000 - 210.000

Tempo pieno

14 giorni+

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

Supera i filtri ATS

Vantaggi offerti da questo lavoro

Medical, dental, vision insurance
401(k) retirement benefits
Paid time off and holidays
Professional development
Flexible or hybrid work options
High-impact GenAI products

Descrizione del lavoro

Latitude is seeking a GenAI Engineer in Seattle to design, develop, and deploy Generative AI applications powered by LLMs, RAG, Python, and LangChain. You will work across the full AI application lifecycle, from prototyping to production deployment and optimization.

Collaborate with software engineers, data scientists, product managers, and stakeholders to deliver production-ready AI solutions and improve performance, reliability, and cost efficiency.

Competenze

  • 2–5 years in software or ML engineering.
  • Strong Python programming experience.
  • Hands-on experience building LLM-based applications.
  • Experience developing RAG-based workflows.
  • Familiarity with LangChain or similar frameworks.
  • Understanding embeddings, vector databases, and info retrieval.
  • Experience with APIs and production software development.
  • Good debugging and problem-solving skills.

Mansioni

  • Design production-ready Generative AI applications using LLMs.
  • Build and optimize RAG pipelines for accurate, context-aware responses.
  • Develop AI workflows and components with Python and LangChain.
  • Integrate commercial and open-source LLMs into applications.
  • Develop document ingestion, embedding, retrieval, and reranking workflows.
  • Implement prompt engineering, tool calling, and AI agents.
  • Evaluate model quality, latency, and reliability with appropriate metrics.
  • Optimize applications for performance, scalability, and cost.
  • Build APIs and services that integrate GenAI with existing platforms.
  • Collaborate with software engineers, data scientists, PMs, and stakeholders.
  • Monitor production AI systems and continuously improve performance.
  • Follow responsible AI, security, privacy, and software engineering best practices.

Conoscenze

Python
LLMs
LangChain
RAG
Vector databases
APIs

Strumenti

LangGraph
LlamaIndex
Pinecone
Weaviate

Descrizione del lavoro

GenAI Engineer

Experience: 2–5 Years

Locations: San Francisco, CA | New York, NY | Seattle, WA | Austin, TX

Salary: $130,000–$210,000+ annually

Employment Type: Full-Time

About The Company

We are building next-generation AI products that use large language models and intelligent automation to solve complex business problems. Our engineering teams combine modern AI technologies with scalable software engineering practices to deliver reliable, secure, and production-ready Generative AI solutions.

About The Role

We are seeking a GenAI Engineer to design, develop, and deploy Generative AI applications powered by LLMs, Retrieval-Augmented Generation (RAG), Python, and LangChain. You will work across the full AI application lifecycle, from prototyping and experimentation to production deployment and optimization.

Key Responsibilities

  • Design and develop production-ready Generative AI applications using LLMs.
  • Build and optimize RAG pipelines for accurate, context-aware responses.
  • Develop AI workflows and application components using Python and LangChain.
  • Integrate commercial and open-source large language models into enterprise applications.
  • Develop document ingestion, chunking, embedding, retrieval, and reranking workflows.
  • Implement prompt engineering, structured outputs, tool calling, and AI agents.
  • Evaluate model quality, relevance, latency, and reliability using appropriate evaluation techniques.
  • Optimize applications for performance, scalability, cost, and response quality.
  • Build APIs and services that integrate GenAI capabilities with existing software platforms.
  • Collaborate with software engineers, data scientists, product managers, and business stakeholders.
  • Monitor production AI systems and continuously improve model and application performance.
  • Follow responsible AI, security, privacy, and software engineering best practices.
Required Qualifications
  • 2–5 years of professional experience in software engineering, machine learning, AI engineering, or a related field.
  • Strong programming experience with Python.
  • Hands-on experience building applications with LLMs.
  • Practical experience developing RAG-based applications.
  • Experience with LangChain or similar LLM application frameworks.
  • Understanding of embeddings, vector databases, semantic search, and information retrieval.
  • Strong understanding of prompt engineering and LLM application architecture.
  • Experience working with APIs and production software development.
  • Strong debugging, analytical, and problem-solving skills.
Preferred Qualifications
  • Experience with LangGraph, LlamaIndex, or similar frameworks.
  • Experience with vector databases such as Pinecone, Weaviate, Milvus, or pgvector.
  • Familiarity with OpenAI, Anthropic, Google, Meta, or other foundation models.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Knowledge of Docker, Kubernetes, CI/CD, and MLOps practices.
  • Experience with LLM evaluation, observability, guardrails, and AI safety.
  • Familiarity with NLP, machine learning, or deep learning concepts.
What We Offer
  • Competitive compensation of $130K–$210K+, based on experience and qualifications.
  • Medical, dental, and vision insurance.
  • 401(k) and retirement benefits.
  • Paid time off and company holidays.
  • Professional development and learning opportunities.
  • Flexible or hybrid work options, depending on location.
  • Opportunity to work on high-impact Generative AI products.

Equal Opportunity

We are committed to creating an inclusive workplace and providing equal employment opportunities to qualified candidates in accordance with applicable laws.

Skills: python,rag,langchain,llm

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