Job description

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 Software Engineer, with deep GenAI expertise to lead our AI 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: Work closely with product, design, and customers. Bring an engineer's view of what to build and how, not just take tickets. Turn vague requirements into clear technical plans, and adjust as you learn. Design, build, and ship production features across the full stack: APIs, data models, services, and UI. Make architecture decisions that balance speed now against maintainability later. Build AI-powered capabilities into the product: LLM features, retrieval, agents, and tool-calling flows (including MCP), with scoped permissions and failure recovery. Build evals from real user questions so every prompt or model change is measured before it ships. Protect AI features against prompt injection, personal-data leaks, and made-up answers. Keep production healthy: monitoring and tracing (including AI cost and latency), debugging from real traces, and fixing what breaks. Use AI coding tools (Claude Code, Cursor, or similar) as a core part of how you work, and own the quality, tests, and reliability of what ships. Raise the engineering bar through code review, sharing what works with AI tools, and improving the team's workflow. REQUIREMENTS: 10+ years of software engineering, shipping customer-facing products in production. Strong full-stack fundamentals: Python (FastAPI or similar), React and TypeScript, relational databases and SQL, and shipping containerized services to the cloud. Strong system design: data modeling, API design, and production systems that stay reliable, fast, and secure as they grow. You can explain the trade-offs behind your choices. Hands-on experience shipping LLM-powered features: context engineering (prompts, retrieval, tools, memory), evals, handling model failures, and AI system architecture. An AI-native workflow: you plan before prompting, work in small reviewable steps, give your agents good context, use tests as the safety net, and can tell when their output is wrong. Strong product sense: you understand the user's problem, care about the experience, and push back when something doesn't feel right. High EQ: you listen well, read what stakeholders really need, and can disagree while keeping trust. Clear communicator with both technical and non-technical people. Comfortable with ambiguity: you work independently and know when to ask for help. NICE TO HAVES: Demonstrated use of AI tools to work more efficiently—whether professionally or personally—and a curiosity for finding new ways to apply them. Comfort integrating generative AI into day-to-day workflows to boost productivity, quality, and output. 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 Fully remote The U.S. annualized pay range for this position is $160,000 - $190,000 USD. In addition, certain roles have the opportunity to earn sales-based commissions. Base pay offered within the stated range may vary depending on multiple individualized factors, including job-related skills, professional experience, education and licenses (if applicable), work location and compensation market data. Base pay is just a part of our total rewards program. Placer provides medical, dental and vision coverage as well as flexible time off, 401K and equity awards for certain roles. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. 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.

Requirements

Must-haves

Work closely with product, design, and customers. Bring an engineer's view of what to build and how, not just take tickets.
Turn vague requirements into clear technical plans, and adjust as you learn.
Design, build, and ship production features across the full stack: APIs, data models, services, and UI.
Make architecture decisions that balance speed now against maintainability later.
Build AI-powered capabilities into the product: LLM features, retrieval, agents, and tool-calling flows (including MCP), with scoped permissions and failure recovery.
Build evals from real user questions so every prompt or model change is measured before it ships.
Protect AI features against prompt injection, personal-data leaks, and made-up answers.
Keep production healthy: monitoring and tracing (including AI cost and latency), debugging from real traces, and fixing what breaks.
Use AI coding tools (Claude Code, Cursor, or similar) as a core part of how you work, and own the quality, tests, and reliability of what ships.
Raise the engineering bar through code review, sharing what works with AI tools, and improving the team's workflow.
10+ years of software engineering, shipping customer-facing products in production.
Strong full-stack fundamentals: Python (FastAPI or similar), React and TypeScript, relational databases and SQL, and shipping containerized services to the cloud.
Strong system design: data modeling, API design, and production systems that stay reliable, fast, and secure as they grow. You can explain the trade-offs behind your choices.
Hands-on experience shipping LLM-powered features: context engineering (prompts, retrieval, tools, memory), evals, handling model failures, and AI system architecture.
An AI-native workflow: you plan before prompting, work in small reviewable steps, give your agents good context, use tests as the safety net, and can tell when their output is wrong.

Nice-to-haves

Demonstrated use of AI tools to work more efficiently—whether professionally or personally—and a curiosity for finding new ways to apply them.
Comfort integrating generative AI into day-to-day workflows to boost productivity, quality, and output.
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
Fully remote

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmpythonreacttypescriptsqlapi

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k