Senior Software Engineer, AI Platform
W
WeedmapsAI platform
Location: United StatesFull-TimeSenior
SalaryThe base pay range for this position is $196,984.00 - $222,000.00 per year, and a competitive bonus
Apply NowOpens the employer's application page
Job Details
- Experience
- Minimum of 6 years of professional software development experience
- Required Skills
- PythonTypeScript
Requirements
- Hold a bachelor's degree or have equivalent practical experience.
- Have at least 6 years of professional software development experience, including owning production services end to end.
- Have at least 1 year of hands-on experience shipping LLM-powered features or agents to production, not only prototypes.
- Have experience with tool or function calling, prompt design, structured outputs, and handling model failures gracefully.
- Have experience building retrieval systems, including embeddings, vector or hybrid search, chunking, ranking, and measuring retrieval quality.
- Be proficient in at least one of Python, TypeScript, or Ruby, and comfortable working across a polyglot codebase.
- Have experience with a major cloud platform, preferably AWS, as well as CI/CD and observability tooling.
- Have a track record of measuring work through evaluations, A/B tests, or clear before-and-after metrics.
Responsibilities
- Design, build, and operate production AI agents, including an autonomous coding agent that works from Jira and Slack, opens pull requests, fixes CI failures, and applies review feedback.
- Build the retrieval and context layer using embeddings, semantic search, knowledge-graph modeling, Snowflake semantic-layer integration, and internal documentation.
- Extend the internal MCP server with reusable skills, tools, and processes, and help product teams integrate agents into their workflows.
- Build offline test sets and online metrics to evaluate prompts, models, and retrieval changes, and gate releases on evaluation results.
- Reduce cost and latency by routing work to suitable models, using caching and structured outputs, and tracking spend per agent and task on AWS Bedrock.
- Harden agents against prompt injection, memory poisoning, and over-broad permissions using least-privilege tool access, auditable actions, and human approval where warranted.
- Instrument agents with tracing and logging, diagnose failures, and participate in on-call for owned systems.
- Evaluate new models and tools and adopt those that prove effective.
- Write design documents, review code, and mentor engineers on building with LLMs.
View Full Description & ApplyYou'll be redirected to the employer's site
