AI-Agentic Development

• Daily Orchestration: Use AI tools (ChatGPT, Claude, Cursor, etc.) to generate and refine code, create tests and technical specs, debug complex issues, refactor legacy systems.
• Harness Engineering: You will design and implement robust agent harnesses to manage the lifecycle of your autonomous agents.
• Validation and Integrity: Act as a quality gate, validate AI outputs, prevent "AI slop", ensure production-grade systems.

Product and Operational Leadership

• Operate as an Architect: You scope ambiguous problems, align stakeholders, and unblock things without being asked. You autonomously design patterns and coding standards for integrating LLMs — prompt management, output validation, context budgeting, and cost control.
• Stay at the Frontier: Evaluate and adopt emerging frameworks (LangGraph, CrewAI, custom) with a critical eye toward production reliability, not hype.
• Balance velocity with rigour: You are comfortable shipping imperfect v1s and systematically improving them.

What you bring

General profile

• Product owner mindset — you can take ambiguous requirements for your domain and turn them into a clear, prioritized roadmap without needing middle-management alignment.
• Startup and Builder DNA — you have a track record of shipping your own projects and working in high-accountability environments.
• Strong full-stack expertise across modern web ecosystems, Python /Node / Go / Ruby
• Fluent in Prompt engineering and LLM API integration
• Deep experience with RAG pipelines: chunking strategies, embedding models, vector DBs (Pinecone, Weaviate, pgvector)
• Shipped production-grade agentic systems using tool/function calling, orchestration, and multi-agent coordination
• Hands-on with guardrails, output validation, and safety patterns for LLM-generated content
• Proven track record in Latency and cost optimization for token-heavy workloads at scale
• Strong English communication skills

Modern AI tools (daily use expected)

• Cursor, GitHub Copilot, or equivalent AI coding assistants
• Claude, GPT-4, and open-weight models (Llama, Mistral) — you know when to use which
• LangChain / LlamaIndex for orchestration, with the judgment to go custom when needed
• Weights & Biases, LangSmith, or equivalent for experiment tracking and eval pipelines

Strong differentiators

• Experience designing LLM evaluation frameworks: benchmarks, regression suites, human eval pipelines
• Familiarity with fine-tuning workflows and RLHF data preparation
• Streaming and async patterns for real-time AI UX (SSE, WebSockets)
• Cloud deployment (AWS / GCP) with containerised AI services

What we offer

• Competitive compensation, paid in USD
• Fully remote work with flexible hours
• 30 paid days off annually, plus sick days as needed
• Health & well-being support
• Learning & development budget to support your professional growth
• English lessons reimbursement
• Co-working space reimbursement
• Company-provided equipment
• A high level of autonomy and ownership in your work
• The opportunity to make a real impact in a fast-growing global SaaS company
• A collaborative, international team with a strong product mindset