LTS
Senior Applied AI Engineer
United States - Remote · Senior
Sponsorship not specifiedDetected 1 day ago
PythonVector DatabasesAWSAzureRESTMachine LearningData ScienceLLMsRAGAgentic AILangGraphA/B TestingCybersecurityZero TrustResearchCommunicationCollaborationProblem Solving
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16Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- Our engineering team is intentionally small giving every engineer meaningful ownership, and direct influence over product direction.
- Using LLMs, autonomous agents, AI-assisted development, parallel workflows, and model-driven engineering is simply how we work.
- LTS shares salary ranges to promote transparency.
Responsibilities
- Design, prototype, and implement production-ready AI capabilities that improve reasoning, accuracy, explainability, and developer productivity.
- Optimize Agent Performance
- Develop evaluation frameworks that measure accuracy, groundedness, explainability, latency, and overall AI effectiveness.
- Build benchmark datasets, automated evaluation pipelines, and performance metrics for production AI systems.
- Analyze AI failures, hallucinations, retrieval gaps, and reasoning errors to drive continuous improvement.
- Collaborate with software engineers to improve knowledge ingestion, document processing, semantic search, embeddings, and enterprise knowledge management.
- Design approaches that maximize retrieval quality across large technical documentation and source code repositories.
- Collaborate Across Engineer
- Partner closely with AI architects, platform engineers, software engineers, and front-end engineers to improve the overall intelligence of the platform.
Requirements
- Experience designing and optimizing Retrieval-Augmented Generation (RAG) systems.
- Experience with prompt engineering, embeddings, semantic search, vector databases, and knowledge retrieval.
- Experience evaluating AI model performance and implementing experimentation frameworks.
- Strong programming skills in Python and experience with modern software engineering practices.
- Experience with AI frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.
- Familiarity with REST APIs, cloud-native applications, and distributed software systems.
- Proven success with ownership of difficult technical challenges and collaboration across disciplines.
Nice to have
- Experience optimizing autonomous or multi-agent AI systems.
- Experience implementing automated AI evaluation frameworks.
- Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, or open-source LLMs.
- Experience with vector databases including Pinecone, Weaviate, Qdrant, Milvus, or Azure AI Search.
- Experience with Responsible AI, AI governance, safety, and explainability.
- Familiarity with software engineering tools, code intelligence platforms, or developer productivity solutions.
- What's In It for You?
- A culture that values innovation, growth, and collaboration
Compensation
- ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements.
Benefits
- LTS is committed to offering eligible employees comprehensive benefits that will provide them with options intended to meet their needs and the needs of their family.
Visa & Work Authorization
- The platform has executive sponsorship, committed users, and a customer investing in long-term modernization.
This listing is sourced directly from LTS's careers page and normalized into a canonical job model.