Senior Software Engineer, AI Platform (Remote)

weedmaps77

United States

Remote

USD 197,000 - 222,000

Full time

5 days ago
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Benefits offered by this job

Health insurance
Paid time off
401(k) plan
Paid parental leave

Job summary

Weedmaps is seeking a Senior Software Engineer to design and operate production AI agents and the AI brain powering our platform. You will work on autonomous coding agents that interact with Jira and Slack, and build the retrieval and context layer behind our AI brain, including embeddings and semantic search.

You will own evaluation, optimize cost and latency on AWS Bedrock, and contribute to a shared MCP server so teams can reuse common skills and tools.

Qualifications

  • 6+ years of professional software development experience, including owning production services end to end.
  • 1 year hands-on experience shipping LLM-powered features or agents to production.
  • Experience building retrieval systems: embeddings, vector/hybrid search, ranking.

Responsibilities

  • Design, build and operate production AI agents and the AI brain for Weedmaps.
  • Extend MCP server with shared skills, tools and processes for reuse across teams.
  • Own evaluation, including offline test sets and online metrics, and gate releases based on results.
  • Drive cost and latency down by selecting the cheapest model and tracking spend on AWS Bedrock.
  • Write design docs, review code, and mentor engineers on building with LLMs.

Skills

Python
TypeScript
Ruby
Cloud (AWS)

Education

Bachelor's degree or equivalent practical experience

Tools

Jira
Slack
Snowflake

Job description

Senior Software Engineer, AI Platform (Remote)
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 m

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