AI-augmented Software Developer

This is a fully remote position, open to applicants in Poland.

📋 Description

• Design and execute integrations for the Model Context Protocol (MCP) and agent orchestration layers.

• Develop and sustain AI Software Development Life Cycle (SDLC) pipelines, tools, and automation processes throughout the development lifecycle.

• Apply agentic AI methodologies, multi-agent workflows, and intelligent task automation solutions.

• Collaborate with Claude Code, Cursor, Microsoft Copilot, and various AI engineering platforms.

• Assess new agentic AI models, frameworks, and toolsets.

• Create proofs of concept (POCs) and prototypes to evaluate scalability, reliability, and architectural compatibility.

• Suggest optimal designs based on practical research and analysis of trade-offs.

• Partner with product teams, architects, and clients to establish requirements and refine AI SDLC solutions.

• Articulate complex technical ideas in a clear manner to non-technical stakeholders.

• Advise clients on the adoption of AI tools for both greenfield and brownfield initiatives.

⛳️ Requirements

• 3–5+ years of experience as a Software Engineer, including at least 1 year focused on AI SDLC.

• Strong hands-on development experience; proficiency in JavaScript/TypeScript is preferred, with skills in Python, Java, Go, and other programming languages being acceptable.

• Practical experience in implementing AI orchestration frameworks.

• Proven track record in the implementation of autonomous agents and multi-agent systems.

• Hands-on experience with MCP integrations.

• Solid grasp of the AI model lifecycle, including prompting, evaluation cycles, and continuous enhancement.

• Capability to work autonomously and manage end-to-end technical delivery.

• Experience in consulting or strong client-facing communication abilities.

• A curious and experimental mindset, coupled with a readiness to develop greenfield AI solutions.

• Familiarity with executing POCs, conducting technical evaluations, or benchmarking methodologies.

• Experience with vector databases, retrieval-augmented generation (RAG), and embeddings is a plus.

• A background in backend engineering, MLOps, or system design is beneficial.

• Knowledge of fine-tuning large language models (LLMs) or customizing models is advantageous.

• Experience in integrating AI into production-level applications is a plus.

🏝️ Benefits

• Option for remote work.