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Company: Markitech
Type: Full-Time

About the Role:

Markitech is looking for a hands-on Solutions Architect / Prompt Engineer to join our growing AI team. In this role, you will design intelligent AI-driven solutions and use agentic AI coding platforms — such as Cursor, Claude Code, and OpenAI Codex — to generate, scaffold, and ship production-quality code. You understand how to get the most out of these tools because you have real development experience and know what good code looks like. This is not a theoretical role: you own architecture decisions and end-to-end delivery.

What You'll Do:

Use AI-powered coding platforms (Cursor, Claude Code, GitHub Copilot, OpenAI Codex, and similar) to rapidly design, generate, and iterate on software solutions.
Architect agentic AI workflows and multi-step pipelines, then drive them to working implementations using AI-assisted development tools.
Engineer, optimize, and evaluate prompts — including system prompts, chain-of-thought strategies, tool/function calling, and structured outputs — to get reliable, high-quality results from LLMs.
Review and own AI-generated code: validate correctness, refactor for production standards, and debug when things go wrong.
Translate business and client requirements into clear technical architectures and implementation plans.
Collaborate with stakeholders to scope AI solutions and communicate tradeoffs in plain language.
Build evaluation frameworks and testing strategies to ensure AI outputs are reliable and safe.
Stay ahead of the curve on emerging AI coding tools and bring best practices into the team.

What We're Looking For:

3+ years of software development experience — you must be able to write, read, debug, and review code independently (Python strongly preferred; JavaScript/TypeScript a plus).
Hands-on experience with AI-assisted coding platforms such as Cursor, Claude Code, OpenAI Codex, GitHub Copilot, or equivalent.
Strong prompt engineering skills: you know how to craft prompts that produce consistent, production-ready outputs across code generation, reasoning, and agentic tasks.
Ability to critically evaluate AI-generated code — catching errors, security issues, and suboptimal patterns before they reach production.
Experience working with LLM APIs (OpenAI, Anthropic, Azure OpenAI, Gemini, etc.) and integrating them into real applications.
Solid understanding of software architecture principles — APIs, microservices, data pipelines, and deployment patterns.
Strong communication skills — able to present solutions and tradeoffs to both technical teams and non-technical stakeholders.

Nice to Have:

Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, or CrewAI.
Familiarity with RAG patterns and vector databases (Pinecone, pgvector, Chroma, etc.).
Cloud platform experience (AWS, Azure, GCP) and containerized deployments (Docker, Kubernetes).
Background in a consulting or client-facing solutions role.
Exposure to AI evaluation tooling (LangSmith, PromptFlow, RAGAS, etc.).

Why Markitech:

At Markitech, we're at the forefront of applying AI to solve real business problems. You'll work on diverse, high-impact projects with a team that values technical depth, curiosity, and continuous learning.

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