Software Engineer; AI​/Agentic Systems

TL;

DR

Synscribe is building the next-generation SEO agency as a service — not tools for consultants, but AI systems that replace the consultant layer entirely.

We’re hiring a software engineer to help us design and build AI agents that:

• Plan, execute, and iterate on SEO strategies autonomously
• Learn from outcomes over time
• Deliver measurable revenue impact for high-growth B2B startups

This is not a traditional SaaS role.

This is “SEO tooling.”

This is applied AI, agents, evals, and real-world feedback loops
, deployed directly into customer production environments.

If you want to work on problems like long-horizon agent planning, human-in-the-loop design, LLM evals, and AI systems that actually ship and make money, keep reading. Application only accepted on our career page (not MCF).

Synscribe is a fast-growing B2B service company at the forefront of AI-driven content marketing and AI search (LLMs / GEO).

We partner with Series A–B B2B SaaS companies (typically $500k+ ARR, global) to ensure their ideal customers find them across:

• Traditional search engines (Google)
• AI-native search and discovery surfaces (ChatGPT, etc.)

• Results in days, not months

  Clients often see inbound leads within 3 days of publishing.

• LLM-native impact

  AI search regularly drives:

  • ~2× the leads of traditional search
  • 2–4× higher conversion rates

• 10× operational efficiency vs traditional SEO agencies

• Engineering-led agency model

  We build and operate proprietary AI systems instead of hiring armies of consultants.

See case studies:

You’ll be working on (and extending) a production system that already includes:

• AI-powered keyword & content planning
• Deep competitor research
• Social listening → content ideation
• Automated, high-quality content pipelines
  Multi-step research
  
  Citation + FAQ generation
  
  Structured outputs
• Programmatic landing page generation
• Automated link building & outreach
• End-to-end planning → execution → reporting loops

These systems are used daily to drive revenue for real companies.

We are building AI systems that replace humans, not just assist them
.

That means:

• Encoding the skills of the best SEO consultants into scalable AI agents
• Planning and executing work over weeks and months
  , not single prompts
• Learning from past outcomes to improve future strategies
• Owning customer outcomes, not just providing tools

You’ll work directly with:

• Startup founders
• In-house engineers
• Growth teams

You won’t just ship features — you’ll:

• Implement changes directly in customer environments
• Close feedback loops fast
• Discover real constraints early
• Use production data to inform system design

• Output quality at scale - LLM evals, human-in-the-loop systems that don’t overwhelm humans
• Formalized agent “skills” - Long-horizon planning
  
  Tool useSelf-improvement from historical results
• AI model collapse / ouroboros problems - Avoiding AI consuming AI-generated trash. Designing robust RAG and core knowledge boundaries
• Agency → self-service transition - Lowering the education barrier
  
  Making complex systems usable without SEO expertise
• Ecosystem-level effects - Cross-portfolio link building
  
  Network effects across customers
• Human-as-trainer loops - Systems that learn from expert operator behavior. Continuous improvement without prompt spaghetti

• Type Script (real Type Script, not any)
• Next.js
• Trigger.dev (durable execution / workflows)
• Lang Chain
• Lang Graph / Mastra
• Internal orchestration layer for agent + human-in-the-loop workflows

• AI agents & agent orchestration
• LLM evals and quality measurement
• RAG and structured knowledge systems
• Human-in-the-loop system design
• Longitudinal learning and feedback loops

This is a culture-defining hire
.

We are a small team (currently
3) moving very fast. You will help set the bar.

• High ownership

  You care deeply about your work, your craft, and the customer.

• Independent learning

  You don’t wait to be taught. You bring net-new knowledge into the team.

• Experimentation over ego

  Hypothesize → test → validate →…