Senior Software Engineer (AI Solutions)

**Location** ------------ United States **Employment Type** ------------------- Full time **Location Type** ----------------- Remote **Department** -------------- Revenue **Compensation** ---------------- * US Tier 1$184K – $249K • Offers Equity • Offers Bonus * US Tier 2$171K – $231K • Offers Equity • Offers Bonus * US Tier 3$165K – $223K • Offers Equity • Offers Bonus Coder determines compensation based on the level, role, and location you live in. For more information, please see our Compensation Philosophy. This job is leveled as P4\. Please feel free to ask any questions about compensation and levels during your initial interview. You'll help build Project Animus — our internal AI agent for revenue and customer intelligence. Your work turns scattered GTM data (call transcripts, CRM records, support tickets, telemetry) into clear answers and usable workflows for Sales, Success, Product, and Marketing. This role is for someone who has genuinely internalized AI as a force multiplier — not just as a product to build, but as the primary way they work. You direct agents, review their output critically, run multi\-step sub\-agent review pipelines, and embed tools like Claude Code, Cursor, or similar agent tooling throughout your development lifecycle (AI\-DLC — AI\-native Development Lifecycle). You build faster and at a higher quality because AI is part of every step of your process. You'll work closely with our AI Solutions lead, implementing and iterating on AI workflows on a Python/FastAPI \+ AWS foundation, partnering with GTM stakeholders to test and refine, and helping keep the system accurate, observable, and cost\-aware. **What you’ll do here** * Implement and iterate on AI workflows on top of existing data pipelines — product feedback extraction, customer update generation, onboarding plans, win/loss summaries, CRM enrichment * Extend and improve the FastAPI \+ LangGraph agentic loop: tool definitions, routing logic, prompt strategy, error handling, and observability * Integrate new data sources (Zendesk, Google Drive, telemetry, email) into the existing AWS Lambda pipeline architecture * Define and consume pre\-aggregated account/opportunity summaries in S3 for fast, reliable structured query * Optimize Lambda\-based data processing jobs for cost, reliability, and performance * Iterate on model strategy: cost\-efficient routing (e.g., Claude Haiku) vs. higher\-quality responses (e.g., Claude Sonnet/Opus) — knowing when to spend tokens and when not to * Evaluate prompts, tool selection quality, and response accuracy with clear metrics; build toward measurable quality in an agentic system * Collaborate with GTM stakeholders (Sales, SE, CS, Product, Marketing) to define, test, and refine AI\-assisted workflows * Contribute to the web UI layer (React/TypeScript) as needed — leveraging agent tooling to execute frontend work efficiently * Contribute to the long\-term evolution of the integration layer, includi