Senior Software Engineer (AI Solutions)

Role

You will build and evolve Animus, an internal AI agent that converts scattered GTM data into clear answers and usable workflows for Sales, Success, Product, and Marketing. The work centers on designing, shipping, and refining LLM-based workflows and integrations on a TypeScript-backed AWS stack, with attention to accuracy, observability, cost, and deployment readiness.

Key Responsibilities

• Design and implement AI workflows on top of existing data pipelines (product feedback extraction, customer update generation, onboarding plans, win/loss summaries, CRM enrichment).
• Extend and refine a TypeScript-based agent: tooling, tool schemas, routing logic, error handling, and observability.
• Improve transcript and account matching across Zoom, Granola, and Salesforce using entity resolution, heuristics, and LLM-assisted matching.
• Integrate new data sources (Slack, Zendesk, Google Drive, Nexus/telemetry, email) into the AWS stack.
• Define and consume pre-aggregated account/opportunity summaries in S3 for fast, reliable queries.
• Optimize Lambda-based data processing jobs for cost, reliability, and performance.
• Iterate on model strategy (cheap routing vs. higher-quality response models) and evaluate prompts, tool selection, and response accuracy with metrics.
• Collaborate with GTM stakeholders (Sales, SE, CS, Product, Marketing) to define, test, and refine AI-assisted workflows.
• Partner with infra engineering (Terraform, Kubernetes) to ensure secure, observable, production-ready deployments.
• Contribute to simple UI/UX surfaces (Slack bot flows, simple web UI/dashboards) to expose workflows to end users.

Requirements

• 5+ years in software engineering, including 1–2+ years building LLM-based applications or agents.
• Strong experience in TypeScript/Node.js (preferred) or Python for backend and data processing.
• Hands-on experience with LLM tool calling/agents (custom frameworks, LangChain, or equivalent).
• Practical RAG expertise: chunking, metadata schemas, retrieval, relevancy, and evaluation.
• Solid AWS experience: Lambda, S3, IAM, CloudWatch. Exposure to Amazon Bedrock is a plus.
• Background in data integration/pipelines and consuming APIs/webhooks (Salesforce, Slack, Zendesk, Zapier, etc.).
• Skill designing JSON schemas, pre-aggregated summaries, and metadata models for query.
• Familiarity with Salesforce data structures or willingness to ramp quickly.
• Comfortable working in a partially “vibe-coded” codebase and refactoring for testing, structure, and observability.
• Experience with prompt engineering and evaluation for business workflows.

Nice-to-haves / Bonus

• Amazon Bedrock knowledge bases.
• Terraform and/or Kubernetes experience.
• Slack bot development and slash commands.
• CRM enrichment, sales tooling, or GTM analytics experience.
• GDPR/data privacy experience for AI systems.
• Prior work on sales/revops intelligence tools, conversation intelligence, or human-in-the-loop review flows.

Location & Compensation

• Location: Remote (United States).
• Employment: Full-time.
• Compensation (US): ranges shown by tier: $165,000–$249,000 depending on tier and location; equity and bonus are offered.