Promenade
SaaS
Sr.SoftwareEngineer,InternalApps
Neural analysis suggests this role is
optimal for Senior candidates.
“Sr. Software Engineer, Internal Apps at Promenade. Skills: Software engineering, LLM API integration, AI-assisted development, SQL. Talk to business teams. Understand slowdowns”
What You'll Achieve.
Shipped multiple internal tools that teams actually use; Identified and fixed real workflow bottlenecks; Helped set pragmatic standards for how engineering uses AI; People trust you to build things that work
Industry & Context.
Understand what's slowing them down; Figure out whether the fix is traditional software, an AI integration, or some combination; Turn vague requirements into something you can actually build; Debug a failing deploy; Read a stack trace; Reason about why something broke; Understand what models are good at; Understand where models fall apart; Turn business questions into lightweight data tools
What They're Looking For.
Must Have
5+ years of professional software engineering, Shipped production systems used by real people, Solid backend skills, Hands-on experience integrating LLM APIs into real applications, Fluent with AI-assisted dev tools, SQL, Comfortable with ambiguity, Talk to stakeholders directly
Nice to Have
Snowflake experience, Javascript or Python preferred
What You'll Do.
Talk to business teams
Turn requirements into buildable software
Review AI-generated code
Design prompt strategies
Design evaluation methods
Write maintainable code
Establish secure AI patterns
Contribute to standards
Build internal dashboards
Turn business questions into data tools
How You'll Work.
Team & Collaboration
Work directly with business teams; Work with engineering teams; Talk to stakeholders directly
Communication Scope
Talk to people; Talk to stakeholders directly
Process & Methodology
Own the whole thing, Take ownership from idea through production
Full Job Description
## What you'll do Talk to people, then build things. You'll work directly with business and engineering teams to understand what's slowing them down. You'll figure out whether the fix is traditional software, an AI integration, or some combination. Then you'll turn vague requirements into something you can actually build. Own the whole thing. Prototype it, harden it, deploy it, monitor it. These are internal tools, so you move fast, but they still need to work reliably. Build fast with AI-assisted development. We use tools like Claude Code to move quickly. You should be comfortable using them to scaffold, iterate, and ship. But you also need to read what they produce, catch what they get wrong, and know when to write it yourself. These tools make good engineers faster. They don't replace knowing how software works. Use AI where it actually helps. Integrate LLM APIs (OpenAI, Anthropic, Gemini, etc.) when language understanding or probabilistic reasoning genuinely improves the outcome. Design prompt strategies and evaluation methods when you do. Skip the model call when a conditional statement would work better. Keep an eye on cost, latency, and reliability. Write code other people can maintain. Build clean systems. Establish practical patterns for secure AI usage. Contribute to standards around observability, safety, and data handling. Work with data. Write SQL against MySQL/ Snowflake, build internal dashboards, and turn business questions into lightweight data tools. ## What we're looking for 5+ years of professional software engineering. You've shipped production systems used by real people. That foundation matters here. We're not looking for someone who learned to code last year through prompting. Solid backend skills: APIs, data modeling, system design. You can debug a failing deploy, read a stack trace, and reason about why something broke without asking a model to explain it. Hands-on experience integrating LLM APIs into real applications. You understand what
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