AI Engineer

About the Role :

As an AI Engineer at Solverminds, you’ll build LLM-powered features and agents that bring AI

into our maritime software products, working with experienced AI engineers to take ideas from

prototype to production.

Responsibility:

• Build and integrate LLM-powered features and agents using LangChain/LangGraph,

including tool use, memory, and multi-agent workflows (MCP, A2A).

• Implement and maintain evaluation and regression tests for non-deterministic LLM outputs,

working with senior engineers on eval design.

• Take AI features from prototype to production, covering implementation, testing,

deployment, and monitoring.

• Keep up with new models, agent frameworks, and tooling; run small experiments and share

findings with the team.

• Write clean, maintainable, well-tested Python and take part in code review.

• Document system designs, prompt/context strategies, and evaluation results.

Required Skills & Experience :

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or

equivalent practical experience.

• A couple of years of professional software engineering experience in Python, including at

least 1 year building LLM-powered applications.

• Hands-on experience with FastAPI, Pydantic, and async Python.

• Experience building with LangChain/LangGraph or a comparable agent framework.

• Working understanding of how LLMs work (tokenization, context windows, embeddings,

transformer basics) and familiarity with both frontier and open-source models.

• Familiarity with common agent design patterns: ReAct, planning, reflection, tool use,

memory, and multi-agent handoff.

• Daily use of AI coding assistants (e.g. Cursor, Claude Code).

• Clear communication and the ability to work with product and engineering teams.

Desired :

• MCP server/client integration; exposure to the A2A protocol.

• LLM testing and QA experience, including regression testing, red-teaming, and safety

evaluation.

• Prompt and context engineering, and RAG pipeline design and optimization (chunking,

retrieval, reranking, vector databases).

• Azure AI services (Azure AI Foundry, Prompt Flow, Azure OpenAI Service).

• LLM observability tools (e.g. LangSmith, Langfuse)