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Placer.ai

Principal Engineer, GenAI Solutions

Reposted 17 Days Ago
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Remote
Hiring Remotely in United States
Expert/Leader
Remote
Hiring Remotely in United States
Expert/Leader
Lead the development of GenAI solutions for an AI-powered location intelligence platform, overseeing full-stack architecture, LLM integration, and scalable deployments.
The summary above was generated by AI

ABOUT PLACER.AI: 

Placer.ai is transforming how organizations understand the physical world. Our location analytics platform provides unprecedented visibility into locations, markets, and consumer behavior. Placer empowers thousands of customers—from Fortune 500 companies, to local governments and nonprofits— to make smarter, data-driven decisions.

What sets us apart? We've built the most advanced location intelligence platform in the market while maintaining an uncompromising commitment to privacy, proving that powerful analytics and responsible data practices can coexist.

Our growth reflects the market's demand: we reached $100M in annual recurring revenue within just 6 years of launching, achieved unicorn status with a $1B+ valuation in 2022, and continue to expand rapidly as one of North America's fastest-growing tech companies. We're creating a $100B+ market opportunity, and we're just getting started.

Named one of Forbes America's Best Startup Employers and a Deloitte Technology Fast 500 company, we're building a culture where innovation thrives, collaboration is the norm, and every team member contributes to reshaping how the world understands location.

SUMMARY:

We are seeking an experienced Principal Engineer with deep GenAI expertise to lead our GenAI product solutions and development efforts. In this role, you will be responsible for driving the technical vision and architecture of our AI-powered location intelligence platform, building production-ready solutions that transform how businesses understand and leverage location data. You will oversee the full-stack development of our conversational AI system, from LLM integration and agentic workflows to real-time streaming interfaces, while establishing the technical foundation for our next-generation business intelligence tools. If you are a technical leader with 10+ years of software development experience, proven success in production GenAI environments, and a passion for building scalable AI platforms that deliver measurable business impact, we want to hear from you.

RESPONSIBILITIES:

  • Lead the technical vision and architecture decisions for our GenAI products, ensuring scalability and performance of the AI-powered location intelligence system.
  • Establish technical roadmaps aligned with business objectives and scalability requirements.
  • Design and implement end-to-end AI systems from prototype to production, including LLM integration, agentic architectures, and RAG implementations.
  • Build robust data pipelines and infrastructure supporting AI/ML workloads at scale.
  • Oversee model deployment, fine-tuning, and optimization for production environments.
  • Architect scalable microservices and cloud-native solutions supporting real-time AI applications.
  • Ensure responsible AI practices including guardrails, performance monitoring, and ethical considerations.

REQUIREMENTS:

  • Bachelor's degree or higher in Computer Science, Engineering, or a related field.
  • 10+ years of experience in software development, with 1+ years building production GenAI solutions in B2B SaaS environments.
  • Expert-level proficiency in backend engineering with Python, Java, Go, or Node.js; proven experience designing microservices architectures and deploying on cloud platforms (AWS, GCP, or Azure). Strong understanding of modern frontend technologies (React/Next.js, TypeScript) and experience architecting full-stack applications with real-time data streaming and WebSocket integrations.
  • Hands-on experience building and deploying LLM-powered applications using frameworks such as LangChain, LlamaIndex, and APIs from OpenAI, Anthropic, or open-source models.
  • Experience implementing agentic AI architectures with tool calling, memory systems, and multi-step reasoning capabilities for complex business workflows.
  • Demonstrated expertise in RAG (Retrieval-Augmented Generation) systems, vector databases (Pinecone, Weaviate, ChromaDB), and semantic search implementations.
  • Strong foundation in data engineering: designing and optimizing data pipelines, ETL processes, and data infrastructure to support AI/ML workloads.
  • Proven track record of taking GenAI models from prototype to production, including fine-tuning LLMs, prompt engineering, and implementing guardrails for responsible AI.
  • Experience with MLOps practices: model versioning, A/B testing, monitoring model performance, and managing the full ML lifecycle in production environments.
  • Skilled at translating business requirements into technical solutions and collaborating with cross-functional teams including product managers, data scientists, and stakeholders.

WHY JOIN PLACER.AI?

  • Join a rocketship! We are pioneers of a new market that we are creating.
  • Take a central and critical role at Placer.ai.
  • Work with, and learn from, top-notch talent.
  • Competitive salary.
  • Excellent benefits.

NOTEWORTHY LINKS TO LEARN MORE ABOUT PLACER

  • About Placer.ai
  • Placer.ai's $100M round C funding (unicorn valuation!)
  • See our data in action at The Anchor
  • Placer.ai in the news
  • Video: About Placer for Commercial Real Estate

Placer.ai is committed to maintaining a drug-free workplace and promoting a safe, healthy working environment for all employees.

Placer.ai is an equal opportunity employer and has a global remote workforce. Placer.ai’s applicants are considered solely based on their qualifications, without regard to an applicant’s disability or need for accommodation. Any Placer.ai applicant who requires reasonable accommodations during the application process should contact Placer.ai’s Human Resources Department to make the need for an accommodation known.

Top Skills

Anthropic
AWS
Azure
Chromadb
GCP
Go
Java
Langchain
Llamaindex
Next.Js
Node.js
Openai
Pinecone
Python
React
Typescript
Weaviate

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