About SignNow team:
We are a passionate and ambitious team of 100+ people on a mission to succeed with our award-winning signature solution – SignNow.
SignNow empowers over 28 million people at companies across the world to move fast with everything they need to send and eSign their documents. Increase productivity with document workflows, impress customers, and save money while maximizing ROI with SignNow.
And now we are looking for a Senior AI Engineer to focus on building AI capabilities from the ground up in a greenfield environment, helping shape the foundations of how intelligence is embedded into the product. You will design and implement production-grade agentic workflows, pipelines, and AI-powered product experiences, going beyond simple model usage to create reliable systems that can deliver real business value.
This role requires strong ownership in evaluating frameworks, orchestrating deterministic and non-deterministic flows, and turning emerging AI technologies into scalable product capabilities. Will collaborate closely with cross-functional teams and senior engineers across the organization to define architecture, drive technical initiatives, and help establish the engineering standards for AI systems in a production environment.
What you will be working on:
Design and ship production AI features end-to-end — RAG, agents, document understanding, conversational interfaces — across LangGraph / LiteLLM / pgvector / Langfuse.
Drive technical architecture for the AI product line: LLM orchestration, evals, observability, latency / cost / reliability tradeoffs.
Own AI initiatives technically — from spec through production, including rollout and post-launch eval improvements.
Code review and architectural feedback across the team; mentor engineers on AI engineering practices.
Build and evolve eval frameworks and quality measurement for AI features.
Collaborate closely with PM, Design, and adjacent teams to shape AI features that work for real users at scale.
Bring proven patterns from the LLM ecosystem (frameworks, agent patterns, MCP, tool use) into the team.
What we expect from you:
8+ years of commercial software engineering experience (Python strongly preferred).
3+ years of shipping LLM / GenAI features to production at scale
Strong LLM system design: latency, cost, reliability, eval-driven development.
Hands-on with RAG in production and agent orchestration (LangGraph or equivalent).
Tool use / function calling, familiarity with MCP patterns.
Experience with observability and evals for LLM systems (Langfuse, Arize, or equivalent).
Ability to own architectural decisions and review others’ designs.
English: B2 (Upper-Intermediate).
What experience will help you:
Document understanding / OCR / structured extraction domain.
Postgres + pgvector at scale.
LLM proxy patterns (LiteLLM or similar).
Mentoring / tech-leading experience - only as an ambassador, no plans to grow AI team
