Senior Software Engineer - Agentic AI

About SignNow team

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.

We are looking for a Senior AI Engineer to build AI capabilities from the ground up in a greenfield environment and shape 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 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. You will collaborate closely with cross-functional teams and senior engineers to define architecture, drive technical initiatives, and establish engineering standards for production AI systems.

What you will be working on

• Design and ship production AI features end-to-end, including RAG, agents, document understanding, and conversational interfaces, across LangGraph, LiteLLM, pgvector, and Langfuse.
• Drive technical architecture for the AI product line: LLM orchestration, evaluations, observability, and latency, cost, and reliability trade-offs.
• Own AI initiatives technically from specification through production, including rollout and post-launch evaluation improvements.
• Provide code review and architectural feedback across the team; mentor engineers on AI engineering practices.
• Build and evolve evaluation frameworks and quality measurement for AI features.
• Collaborate closely with Product Management, Design, and adjacent teams to shape AI features that work for real users at scale.
• Bring proven patterns from the LLM ecosystem, including frameworks, agent patterns, MCP, and tool use, into the team.

What we expect from you

• 8+ years of commercial software engineering experience; Python is strongly preferred.
• 3+ years of shipping LLM or GenAI features to production at scale.
• Strong LLM system design skills covering latency, cost, reliability, and evaluation-driven development.
• Hands-on production experience with RAG and agent orchestration using LangGraph or an equivalent.
• Experience with tool use/function calling and familiarity with MCP patterns.
• Experience with observability and evaluations for LLM systems using Langfuse, Arize, or an equivalent.
• Ability to own architectural decisions and review others’ designs.
• English at B2 (Upper-Intermediate) level.

What experience will help you

• Document understanding, OCR, or structured-extraction experience.
• Experience with Postgres and pgvector at scale.
• Experience with LLM proxy patterns using LiteLLM or similar tools.
• Mentoring or technical leadership experience; this role serves as an AI ambassador, with no plans to grow an AI team.

Ready to shape the future of AI in production?

Join a group of AI ambassadors helping define how AI is built, scaled, and embedded into products used by millions. This is a greenfield opportunity to architect production-grade AI systems for a mission-critical product.

What we offer

• Flexible working environment: work from offices in the United States, Poland, Romania, or Ukraine, or remotely from many countries.
• Competitive compensation, performance-based bonus system, and stock options.
• Professional growth and learning through courses, conferences, and learning resources, with support for career growth and internal mobility.
• Health and well-being benefits tailored to each country, including health coverage, wellness programmes, fitness options, and quarterly Mental Health Days.
• Family-friendly culture, including flexibility for parents, airSlate Junior Club for kids, company-wide family days, and a pet-friendly approach.
• Support for charitable initiatives through the airSlate Care programme, including humanitarian aid and employee donation matching.
• Open communication through team discussions and company-wide Q&A sessions with leadership.