- Company Name
- Alcumus
- Job Title
- AI Engineer
- Job Description
-
Job title: AI Engineer
Role Summary
Design, develop, and maintain AI agents and Model Context Protocol (MCP) integrations for a cloud‑native platform that supports large language model (LLM) workflows. Collaborate with full‑stack teams in an agile environment to deliver scalable, secure, and testable AI‑enabled features.
Expectations
* 3–5+ years of professional software development in C#, Python, TypeScript, or Go.
* Proven experience building LLM‑based agents, orchestrators, or similar AI systems.
* Hands‑on knowledge of MCP concepts (context servers, standardization tool integration, protocol‑based communication).
* Ability to translate complex requirements into modular, shippable code and communicate trade‑offs to technical and non‑technical stakeholders.
* Familiarity with cloud‑native architectures, APIs, distributed systems, container orchestration (Docker, Kubernetes), and contemporary engineering tools (JIRA, Git, package managers).
* Comfort using AI‑assisted coding tools (e.g., Copilot) and writing meaningful unit/integration tests.
Key Responsibilities
1. Craft AI agents capable of reasoning, planning, and executing multi‑step actions to support user journeys.
2. Build and extend MCP servers and clients to enable structured, interoperable AI integrations.
3. Integrate LLMs with application APIs, databases, and third‑party services.
4. Decompose features into clear, reviewable, and testable units; manage implementation through sprint cycles.
5. Conduct peer code reviews, adhere to coding standards, and ensure security, performance, and maintainability.
6. Debug issues methodically, resolve root causes, and document findings.
7. Create efficient, comprehensive tests for critical application components.
8. Demonstrate prototype features to stakeholders for feedback and iteration.
Required Skills
* Programming: C#, Python, TypeScript, or Go.
* AI/ML: LLM agents, prompt engineering, embeddings, retrieval‑augmented generation (RAG).
* Protocols: MCP (context servers, standardized tool integration).
* Systems: APIs, distributed cloud‑native architecture, containerization (Docker, Kubernetes).
* Tooling: Agile SDLC, JIRA, GitHub/Bitbucket, package managers, build systems.
* AI‑assisted coding proficiency (Copilot, etc.).
* Testing: Unit, integration, and test‑driven development.
* Communication: Technical clarity to engineers and non‑technical stakeholders.
Required Education & Certifications
* Bachelor’s degree in Computer Science, Software Engineering, or related field (preferred).
* Industry certifications (e.g., AWS/Azure/GCP, Kubernetes, or AI/ML) are a plus but not mandatory.