Gen AI Engineer
About Placeholderworks
Placeholderworks is an AI engineering firm focused on turning AI concepts into robust, production-grade systems.
We design, build, deploy, and support AI applications that integrate with real business systems, data, and workflows. Our work spans generative AI, AI agents, retrieval systems, conversational AI, enterprise integrations, and AI infrastructure.
We care about more than getting a prototype to work. We focus on reliability, evaluation, observability, security, cost, and latency so AI systems continue to perform in real-world production environments.
About the Role
We are looking for a Gen AI Engineer to design, build, and ship generative AI systems for client and internal projects.
You will work across the full lifecycle — from understanding a business problem and designing the technical solution to building, deploying, monitoring, and continuously improving the system.
This role is highly hands-on and involves writing production code, experimenting with models and AI tools, building prototypes, working with data and APIs, and turning successful experiments into reliable production systems.
What You’ll Do
* Build LLM-powered applications, AI agents, RAG systems, and conversational AI solutions.
* Integrate AI systems with APIs, databases, internal services, and existing client infrastructure.
* Design data flows, retrieval pipelines, evaluation frameworks, and AI application architectures.
* Experiment with different models, prompting strategies, tools, and agent architectures.
* Develop evaluation pipelines to measure quality, reliability, and model performance.
* Optimize AI systems for latency, cost, accuracy, and reliability.
* Deploy and maintain AI-powered services in production environments.
* Implement monitoring, observability, logging, and failure-handling mechanisms.
* Debug complex issues across application, model, data, and infrastructure layers.
* Collaborate with product, engineering, and client teams to translate business problems into technical solutions.
* Review code and contribute to engineering standards and best practices.
* Continuously improve deployed systems based on real-world usage and evaluation data.
What We’re Looking For
Required
* Strong software engineering skills, particularly in Python, TypeScript, or Go.
* Experience building applications using APIs, services, databases, and cloud infrastructure.
* Hands-on experience with LLMs and generative AI.
* Experience building at least one of:
* LLM-powered applications
* RAG systems
* AI agents
* Conversational AI
* AI automation workflows
* Understanding of prompt engineering, model selection, context management, and LLM application architecture.
* Strong problem-solving and debugging skills.
* Ability to take an ambiguous problem and turn it into a practical technical solution.
* Good written and verbal communication skills.
Good to Have
* Experience with models or platforms such as OpenAI, Anthropic, or Hugging Face.
* Experience with vector databases and retrieval technologies.
* Knowledge of SQL/NoSQL databases and data pipelines.
* Experience with LLM evaluation, observability, and experiment tracking.
* Experience with AWS, GCP, or Azure.
* Experience with Docker and Kubernetes.
* Familiarity with CI/CD and MLOps practices.
* Experience optimizing AI applications for production cost and latency.
* Experience working with clients or distributed engineering teams.
What You’ll Learn
At Placeholderworks, you’ll work on real AI systems rather than isolated demos.
You’ll gain exposure to:
* Production LLM architecture
* AI agents and tool use
* RAG and retrieval systems
* LLM evaluation
* AI observability
* Model and infrastructure optimization
* Enterprise AI integrations
* Cloud-native AI deployment
* Building AI systems that operate reliably at scale
Who You’ll Work With
You’ll work closely with engineers, product teams, and clients to understand real-world problems and turn them into production-ready AI systems.
If you enjoy building with AI, experimenting with new models and tools, and solving difficult engineering problems, we’d love to hear from you.
Apply to join Placeholderworks and help build AI systems that move from idea to production.