Applied Methods
~The MetaEngineeringApplied AI Engineer

Applied AI Engineer

Applied AI Engineers build intelligent features into products by integrating LLMs, retrieval systems, and AI APIs to solve real business problems. Day-to-day, they prototype and productionize AI-powered workflows—from designing agent architectures and evaluation frameworks to implementing retrieval pipelines and optimizing inference costs at scale. They sit between product and infrastructure teams, combining hands-on engineering with deep customer collaboration to ship features that work reliably in production. Unlike ML Engineers who train models or Forward Deployed Engineers who embed at customer sites, Applied AI Engineers own the full stack of AI integration within their own organization's products, from architecture decisions to code contributions and technical mentorship.

$ titles --canonical
Applied AI EngineerAI EngineerAI Deployment EngineerProduct Engineer, AI
Open Jobs41
Companies Hiring24
$02

Skills

What companies are looking for in this role.

$ skills --core

Developing and deploying generative AI features and large language model integrations into production systems

95%

Designing and architecting full-stack AI applications from frontend to backend systems

95%

Building and evaluating AI agents with complex tool use, orchestration, and workflow automation

90%

Building prototypes and proof-of-concepts to validate AI solutions and architectures

85%

Creating evaluation frameworks and benchmarks to measure model performance and product quality

85%

Designing scalable APIs, microservices, and backend services for AI-powered applications

85%

Implementing prompt engineering and context management strategies for language models

80%

Optimizing AI system performance including latency, cost, and resource utilization

80%

Integrating multiple data sources and building data pipelines for AI systems

75%

Implementing security, compliance, and reliability standards for regulated and critical environments

75%

Building end-to-end data architectures that aggregate and normalize information across systems

70%

Troubleshooting and debugging AI systems in production environments across customer codebases

70%
$ skills --emerging

Building infrastructure and tooling for agent-driven autonomous systems

75%

Developing human-in-the-loop systems with transparency and inspectability for complex workflows

70%

Designing user interfaces and experiences for AI-native productivity tools and agents

70%

Implementing intelligent routing, prioritization, and alert systems for operational workflows

65%

Implementing multimodal AI capabilities and vision-language model integration

60%
$ skills --soft

Conducting hands-on pair programming and code reviews with technical partners

85%

Translating business requirements into technical AI solutions and product specifications

85%

Leading technical discovery and workshops to understand customer workflows and constraints

80%

Collaborating across product, engineering, and research teams to define technical roadmaps

80%

Creating technical documentation, tutorials, and reusable frameworks for developer adoption

75%

Operating with high autonomy to make architectural and design decisions independently

75%

Identifying technical patterns and contributing product insights across multiple customer engagements

70%

Designing and shipping product-led growth features with seamless onboarding and shareability

60%
$03

Technology

The tools and technologies that define this role.

$ tech --language
Pythonvery high
TypeScripthigh
HTML/CSSmoderate
$ tech --framework
LangChainhigh
Reacthigh
Model Context Protocol (MCP)moderate
$ tech --platform
Claude APIvery high
AWShigh
Kuberneteshigh
Node.jshigh
Azuremoderate
Databricksmoderate
GCP (Google Cloud Platform)moderate
GitHubmoderate
PostgreSQLmoderate
Slackmoderate
Salesforcelow
ServiceNowlow
$ tech --tool
Dockermoderate
Gitmoderate
$ tech --concept
Agentic workflowsvery high
Generative AIvery high
Large Language Models (LLMs)very high
Prompt engineeringvery high
Model evaluationhigh
REST APIshigh
Retrieval-Augmented Generation (RAG)high
Tool use / Function callinghigh
Vector embeddingshigh
Multimodal modelsmoderate
$04

Open Jobs

41 open Applied AI Engineer jobs across 24 companies.

Anthropic1w
Applied AI Engineer, Beneficial Deployments
San Francisco, CA | New York City, NY·Engineering
Fundamental1w
Applied AI Engineer
Europe·Engineering
OpenAI1w
Software Engineer, Enterprise AI Platform
San Francisco·Engineering
Klarity1w
Technical Product Manager
San Francisco (Klarity HQ)·Engineering
Writer1w
Software engineer, generative AI
San Francisco, CA·Engineering
Writer1w
Software engineer, generative AI (UK)
London, UK·Engineering
Writer1w
Senior software engineer, enterprise AI platform (UK)
London, UK·Engineering
Writer1w
AI engineer
San Francisco, CA·Engineering
Writer1w
AI engineer (UK)
London, UK·Engineering
Abnormal Security1w
AI Product Builder
Remote - Canada·Engineering
Nscale1w
AI Product Engineer
APAC; Singapore·Engineering
Cerebras Systems1w
AI Engineer, Model Quality and Performance
Sunnyvale, CA·Engineering
Figma2w
Sales AI Engineer
San Francisco, CA • New York, NY • United States·Engineering
Intrinsic2w
Senior Software Engineer, GenAI Frontend
Mountain View, California·Engineering
Nebius2w
AI Full-Stack Developer
Amsterdam, Netherlands; Germany; Tel Aviv, Israel; United Kingdom·Engineering
Databricks2w
Senior Staff Applied AI Engineer - Context Retrieval
Mountain View, California; San Francisco, California·Engineering
OpenAI2w
Revenue Strategy & Operations - Central Cadence
San Francisco·Engineering
Mistral AI3w
Applied AI, Fullstack Software Engineer, Critical and Sovereign Institutions, Paris
Paris·Engineering
Taktile4w
Sr. Applied AI Engineer
London Office·Engineering
Taktile4w
Sr. Applied AI Engineer
New York Office·Engineering