LTS
LTS16h ago
New

Senior Applied AI Engineer

United StatesUnited StatesRemotesenior
OtherApplied Ai Engineer
1 views0 saves0 applied

Quick Summary

Key Responsibilities

Advance Applied AI Capabilities Design, prototype, and implement production-ready AI capabilities that improve reasoning, accuracy, explainability, and developer productivity. Evaluate emerging LLMs,

Requirements Summary

A

Technical Tools
OtherApplied Ai Engineer

Responsibilities

~1 min read
  • Design, prototype, and implement production-ready AI capabilities that improve reasoning, accuracy, explainability, and developer productivity.
  • Evaluate emerging LLMs, multimodal models, agent frameworks, and AI techniques to identify opportunities for platform advancement.
  • Rapidly prototype new AI capabilities and transition successful experiments into production.
  • Improve autonomous and multi-agent workflows through prompt engineering, reasoning optimization, memory strategies, tool selection, and context management.
  • Continuously refine Retrieval-Augmented Generation (RAG) pipelines, retrieval strategies, embeddings, reranking, and grounding techniques.
  • Improve AI response quality through experimentation, benchmarking, and iterative optimization.
  • 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.
  • Improve how AI agents discover, organize, and reason over enterprise knowledge.
  • Partner closely with AI architects, platform engineers, software engineers, and front-end engineers to improve the overall intelligence of the platform.
  • Share research findings, experimental results, and engineering recommendations with cross-functional teams.
  • Help establish best practices for experimentation, evaluation, and AI quality throughout the organization.
  • Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Engineering, Data Science, or a related technical discipline (or equivalent professional experience).
  • 5+ years of software engineering, applied AI, machine learning, or AI systems development experience.
  • Demonstrated experience developing production AI applications powered by Large Language Models (LLMs).
  • 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.
  • Experience with using AI coding assistants as part of your daily workflow.
  • Familiarity with REST APIs, cloud-native applications, and distributed software systems.
  • Strong analytical, problem-solving, and communication skills.
  • Intellect and curiosity for AI systems and how they behave.
  • Deep passion for experimenting with new AI techniques.
  • Background in evaluation, explainability, and continuous improvement.
  • Proven success with ownership of difficult technical challenges and collaboration across disciplines.

Nice to Have

~1 min read
  • 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.
  • Experience supporting healthcare, Federal Government, or other highly regulated environments.
  • Experience using AI coding assistants and autonomous agents as part of daily software development.
  • The Opportunity to support high-visibility federal missions
  • A culture that values innovation, growth, and collaboration
  • Access to cutting-edge tools and technologies
  • Comprehensive benefits for you and your family
  • A career path that rewards ambition and performance

If you’re ready to push boundaries, sharpen your skills, and join a team that is passionate about building what’s next, we’d love to meet you. Apply today and let’s build a future together!

LTS shares salary ranges to promote transparency. Compensation ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements.

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.

Location & Eligibility

Where is the job
United States
Remote within one country
Who can apply
US

Listing Details

Posted
July 30, 2026
First seen
July 30, 2026
Last seen
July 31, 2026

Posting Health

Days active
0
Repost count
0
Trust Level
76%
Scored at
July 30, 2026

Signal breakdown

freshnesssource trustcontent trustemployer trust
LTS
LTS
greenhouse
Employees
30
Founded
2002
View company profile
Newsletter

Stay ahead of the market

Get the latest job openings, salary trends, and hiring insights delivered to your inbox every week.

A
B
C
D
Join 12,000+ marketers

No spam. Unsubscribe at any time.

LTSSenior Applied AI Engineer