Fullstack Utvecklare
The ideal candidate has strong hands-on experience with MERN, Python-based services, and ComfyUI-style pipeline integration, and can lead systematic engineering across multiple deployments.
Responsibilities
Backend Development
Design, build, and maintain production-grade REST APIs and service layers using Node.js (Express) and Python (FastAPI/Flask), with additional experience in PHP frameworks (Laravel/Yii2/CodeIgniter) where needed.
Architect scalable microservices for SaaS platforms, including service boundaries, async processing, rate limits, and reliability patterns.
Build and operate data layers across MongoDB, PostgreSQL, and MySQL, including schema design, migrations, indexing strategies, and query tuning.
Implement AI/LLM features in real systems: tool/function calling, streaming responses, conversation memory strategies, guardrails, evals, and safe fallback logic.
Build vector search and RAG pipelines(embeddings, hybrid retrieval, reranking, chunking strategies), using vector databases such as pgvector/Pinecone/Weaviate/Milvus/FAISS, plus monitoring and quality evaluation.
Improve performance via caching, background jobs/queues, profiling, and code-level optimization; include tokenization-aware prompt optimization, caching, and cost controls.
Frontend Development
Develop modern, responsive UIs using React.js, Next.js, and state patterns (Redux/Zustand), with strong component architecture and performance awareness.
Implement UI systems using Material UI / Bootstrap (or equivalent), and collaborate closely with product/design to improve UX consistency and reliability.
Build AI-facing interfaces: chat UIs, streaming/real-time updates, file+tool workflows, and admin panels for prompts, evals, and telemetry.
DevOps, Deployment & Platform Engineering
Deploy and operate applications in Docker-first environments across AWS and/or DigitalOcean, including environment separation, secrets management, and release workflows.
Production experience with Kubernetes: deployments, services/ingress, autoscaling, rollouts, observability, and incident-friendly operations.
Build and maintain CI/CD pipelines(GitHub Actions/GitLab CI), including test gates, build artifacts, migrations, preview deployments, and safe rollbacks.
Implement security and reliability controls: JWT/auth flows, RBAC, secure file processing, rate limiting, logging/auditing, and vulnerability hygiene.
AI, Automation & Workflow Systems
Integrate ComfyUI-based services/workflows (or similar graph/pipeline systems) into SaaS products, including job orchestration, asset management, and runtime controls.
Create automation pipelines for AI features: document ingestion, chunking, embedding refresh, scheduled tasks, event-driven processing, and monitoring.
Own real-time performance constraints: latency budgets, streaming stability, concurrency, and cost/throughput tradeoffs.
General Responsibilities
Participate in the full SDLC: planning, architecture, implementation, testing, deployment, and maintenance.Drive systematic development practices: coding standards, reviews, observability, runbooks, and engineering quality initiatives.
Work effectively with cross-functional teams and communicate technical decisions clearly.
Track and execute work using Linear-based workflows(or similar), with disciplined task breakdown and delivery cadence.
Required Skills
JavaScript/TypeScript, Node.js, Express; strong backend API design
React.js, Next.js, modern frontend architecture (state, routing, SSR/CSR tradeoffs)
Python services (FastAPI/Flask), background jobs/queues
AI/LLM production integration: RAG, tool calling, streaming, guardrails, evals
Vector databases / embeddings pipelines (pgvector/Pinecone/Weaviate/Milvus/FAISS)
Databases: MongoDB, PostgreSQL, MySQL (indexes, performance tuning)
Docker, CI/CD, Git (GitHub/GitLab), release management
Kubernetes fundamentals (deployments, services, ingress, scaling)
Security basics: JWT/auth, API security, secure file processing
Agile execution tools (Linear/Jira)
Preferred (Hard Filters / Highly Valued)
Proven experience shipping and operating AI-powered SaaS in production (not prototypes).
Tokenization/prompt cost optimization experience (caching, batching, prompt compression, eval-driven iteration).
Experience building multi-tenant systems (authz boundaries, billing/limits, per-tenant configs).
Strong observability practice: metrics, tracing, structured logs, SLOs, and incident response.
Experience integrating workflow/graph-based AI systems (e.g., ComfyUI pipelines) into customer-facing products.
Comfortable leading architecture decisions and mentoring engineers across projects.