About The Position
You’ll build the AI behind Animus, our internal agent for revenue and customer intelligence. Your work turns scattered GTM data into clear answers and usable workflows for sales, success, product, and marketing. You design, ship, and improve AI workflows on a proven AWS and TypeScript base. You partner with GTM leaders, product, and infra to test, measure, and refine while keeping the system accurate, observable, and cost-aware.
Requirements
- 5+ years in software engineering, including 1-2+ years building LLM-based applications or agents
- Strong experience in TypeScript/Node.js (ideal) 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 Bedrock is a plus
- Background in data integration/pipelines: consuming APIs and webhooks (Salesforce, Slack, Zendesk, Zapier, etc.)
- Skill in designing JSON schemas, pre-aggregated summaries, and metadata models for query
- Familiarity with Salesforce data structures (accounts, opportunities, leads, activities) or willingness to ramp quickly
- Comfortable working in a partially “vibe‑coded” codebase and refactoring toward higher quality (testing, structure, observability)
- Experience with prompt engineering and evaluation for business workflows (accuracy, reliability, user trust)
Nice To Haves
- Amazon Bedrock knowledge bases.
- Terraform and/or Kubernetes.
- Slack bot development and slash commands.
- CRM enrichment, sales tooling, or GTM analytics.
- GDPR/data privacy considerations for AI systems.
- Prior work on sales/revops intelligence tools, conversation intelligence (Zoom/Granola/Gong‑style), or human‑in‑the‑loop review flows.
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 the current 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/or LLM-assisted matching
- Integrate new data sources (Slack, Zendesk, Google Drive, Nexus/telemetry, email) into the existing AWS stack
- Define and consume pre-aggregated account/opportunity summaries in S3 for fast, reliable query
- Optimize Lambda-based data processing jobs for cost, reliability, and performance
- Iterate on model strategy: cheap routing (e.g., Claude Haiku) vs. higher-quality response models (e.g., Claude Sonnet/Opus)
- Evaluate prompts, tool selection quality, and response accuracy with clear 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 deployment, security, and observability are production-ready
- Contribute to future UI/UX (Slack bot flows, simple web UI/dashboards) to expose workflows to end users
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
Upload and Match Resume
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
101-250 employees
