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About This Role
Overview:
Weedmaps is hiring a Senior Software Engineer to build the AI systems our company runs on: the agents that do real engineering and operational work, and the "AI brain" that gives them trustworthy context about our business. You will work on an autonomous coding agent that picks up Jira tickets, opens pull requests and responds to review feedback; a shared platform (an internal MCP server) that gives every agent common skills, tools and processes; and a knowledge layer that connects our Snowflake semantic layer, internal documentation and a growing knowledge graph so agents and people get consistent answers. Success means agents that are measurably useful, cheap enough to run at scale, and safe to trust with production systems. This role sits on the AI Platform team and partners closely with Developer Experience, Data and product engineering teams across the company.
The impact you'll make:
- Design, build and operate production AI agents, including an autonomous coding agent that works from Jira and Slack, opens PRs, fixes its own CI failures and applies review feedback.
- Build the retrieval and context layer behind our "AI brain": embeddings and semantic search, knowledge-graph modeling, and integration with our Snowflake semantic layer and internal docs, so agents pull the right context in one pass instead of several.
- Extend our internal MCP server with shared skills, tools and processes that other teams can reuse, and help product teams bring agents into their own workflows.
- Own evaluation: build offline test sets and online metrics that show whether a change to a prompt, model or retrieval step made an agent better or worse, and gate releases on them.
- Drive cost and latency down: route work to the cheapest model that can do it, use caching and structured outputs, and track spend per agent and per task on AWS Bedrock.
- Harden agents against prompt injection, memory poisoning and over-broad permissions: least-privilege tool access, auditable actions, human approval where the risk warrants it.
- Instrument agents with tracing and logging so failures can be diagnosed and fixed quickly, and take part in on-call for the systems you own.
- Evaluate new models and tools with a practical eye, adopting what holds up and passing on what doesn't.
- Write clear design docs, review code, and mentor other engineers on building with LLMs.
What you've accomplished:
- Bachelor's degree or equivalent practical experience.
- Minimum of 6 years of professional software development experience, including owning production services end to end.
- At least 1 year of hands-on experience shipping LLM-powered features or agents to production (not only prototypes): tool/function calling, prompt design, structured outputs, and handling model failures gracefully.
- Experience building retrieval systems: embeddings, vector or hybrid search, chunking and ranking, and measuring retrieval quality.
- Strong proficiency in at least one of Python, TypeScript or Ruby, and comfort working across a polyglot codebase.
- Experience with a major cloud platform (AWS preferred), CI/CD, and observability tooling.
- A track record of measuring what you build: evals, A/B tests or clear before/after metrics.
Bonus points:
- AWS Bedrock, and experience managing model cost and latency at scale.
- Model Context Protocol (MCP) servers or other agent tool frameworks.
- Knowledge graphs or semantic layers (for example, Snowflake semantic views, dbt metrics or graph databases).
- Agents that act on developer workflows: GitHub Actions, Jira and Slack integrations, automated code review or code generation.
- LLM security: prompt-injection defenses, sandboxing, permission models and red-teaming.
- Entity matching or classification at large scale (millions of records) using ML combined with LLM reasoning.
- Experience with Ruby on Rails, Elixir or Node.js services.
- Experience at a marketplace, e-commerce or regulated-industry company.
The base pay range for this position is $196,984.00 - $222,000.00 per year, and a competitive bonus
2026 US Benefits for Full Time, Regular Employees:
- Physical Health (Medical, Dental & Vision)
- + 100% employer-paid premium for employees + Up to 80% coverage for dependents + Company HSA contribution with the High Deductible Health Plan
- 401(k) Retirement Plan (employer will match contribution up to 3.5% of employee contribution)
- Basic Life, Voluntary Life and AD&D Insurance options
- Supplemental, voluntary benefits
- + Student Loan Repayment/529 Education Savings with a monthly company contribution + FSA (Medical, Dependent, Transit and Parking) + Voluntary Life and AD&D Insurance + Critical Illness Insurance + Accident Insurance + Short- and Long-term Disability Insurance + Pet Insurance + Identity theft protection + Legal access to a network of attorneys
- PTO, paid sick leave, and company holidays (including a 2026 holiday shutdown)
- Paid parental leave
Why Work at Weedmaps?
Life at Weedmaps means innovation and heart. Come join us if you care about the plant, the people who love it, and are ready to let your talent shine. We foster a bustling and collaborative culture that revolves around an environment that focuses on the benefits of weed, and the community that supports it.
You too can have a hand in shaping the industry’s future; ready to roll with us?
See how we’ve grown—our journey, leadership team, and what’s next atWeedmaps.com/corporate
About Weedmaps:
Founded in 2008, we’ve grown from a small startup to a global leader in the cannabis industry. Our dedication to transparency, education, and community has set us apart, and today, we proudly serve cannabis to consumers and businesses in the U.S. and worldwide.
“Freedom to choose. Freedom to access. Freedom to enjoy.”
Notice to prospective Weedmaps job applicants:
Our team has been made aware of incidents involving LinkedIn, Telegram, and Facebook accounts impersonating Weedmaps recruiters. These individuals are attempting to use our company name to solicit payment from prospective candidates interested in applying for jobs at our company. Our team is actively working to combat these attempts, but in the meantime, please be mindful of the following:
- Our recruiters will always communicate with candidates through an @weedmaps.com email address.
- CORRECT: [email protected]
- INCORRECT: [email protected]
- Our recruiters will NEVER ask for or attempt to solicit payment from applicants in order to apply, interview, or work for Weedmaps.
- If you are interested in a role at Weedmaps, please apply through our established channels.
- Weedmaps Careers Page or LinkedIn
If you are unsure if a communication is legitimate, please contact our recruitment team at [email protected] and they will happily confirm for you. Thank you for your vigilance and we appreciate your interest in working with us!
Weedmaps is an equal opportunity employer and makes employment decisions on the basis of merit. The Company prohibits unlawful discrimination against employees or applicants based on race (including traits historically associated with race, such as hair texture and protective hairstyles), religion and religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, military status, veteran status, uniformed service member status, sexual orientation, transgender identity, citizenship status, pregnancy, or any other consideration made unlawful by federal, state, or local laws. The Company also prohibits unlawful discrimination based on the perception that anyone has any of those characteristics, or is associated with a person who has or is perceived as having any of those characteristics. Our company uses E-Verify to confirm the employment eligibility of all newly hired employees.
Applicants are entitled to reasonable accommodations under the terms of the Americans with Disabilities Act and applicable state/local laws, unless the accommodation presents undue hardship. Please email us at peopleoperations at weedmaps.com if you would like to confidentially discuss a potential accommodation during the interview process.
Salary Context
This $196K-$222K range is above the median for AI Software Engineer roles in our dataset (median: $192K across 198 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Weedmaps, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,601 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($209K) sits 5% below the category median. Disclosed range: $196K to $222K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Weedmaps AI Hiring
Weedmaps has 1 open AI role right now. They're hiring across AI Software Engineer. Based in US. Compensation range: $222K - $222K.
Remote Work Context
Remote AI roles pay a median of $188,000 across 2,316 positions. About 6% of all AI roles offer remote work.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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