Mid/Senior AI engineer with networking experience

CodiLime is a software and network engineering industry expert and the first-choice service partner for top global networking hardware providers, software providers and telecoms. The company has 250+ employees and has been operating since 2011. They create proofs-of-concept, help clients build new products, nurture existing ones, and provide services in production environments. Their clients include tech startups and large companies across the US, Japan, Israel, and Europe. The project involves building software for modern platforms and operating systems supporting leading networking equipment manufacturers, cloud-native solutions, and infrastructure projects, with AI/ML as a core tool to address complex engineering and networking challenges.

• Hands-on experience with LLM-driven workflows, agentic frameworks such as LangChain and LangGraph, and tool-calling patterns
• Experience designing structured tools with clear descriptions, input/output schemas, validation logic, and integration with external APIs or command-based systems
• Experience with semantic search, vector databases, RAG patterns, prompt engineering, and structured LLM outputs
• Experience creating golden queries, automated tests, regression checks, and chatbot/agent response evaluations, including LLM-as-a-judge approaches
• Proven experience developing production-quality Python code, including automated tests and maintainable integration logic
• CCNA certificate or equivalent knowledge in networking platforms, device commands, and troubleshooting
• English language proficiency at B2 level minimum, preferably C1 or C2

Nice to have:

• Experience with AI-assisted coding tools such as Codex, GitHub Copilot, Cursor, or similar
• Familiarity with Model Context Protocol, MCP server design, tool discovery, tool permissions/scopes, and emerging agent-to-agent communication patterns such as A2A
• Understanding of routing agents, supervisor/planner patterns, multi-agent workflows, guardrails, and architectures combining deterministic logic with LLM-based reasoning
• Experience with LLM evaluation tooling frameworks such as DeepEval, LangSmith, OpenAI Evals, TruLens, BenchLLM, or similar
• Practical knowledge of classification, clustering, anomaly detection, time-series analysis, or statistical methods applied to telemetry, syslog, events, alerts, or operational data
• Experience deploying AI/LLM-based solutions in production environments, including Docker, Kubernetes, CI/CD, monitoring, MLOps, or cloud/hybrid infrastructure
• Experience building dashboards, notebooks, or lightweight applications for analysis and validation using tools such as Jupyter, Streamlit, Plotly, Altair, matplotlib, or similar

• Developing MCP-like tools that expose network device APIs and CLI commands with clear descriptions, structured inputs/outputs, validation logic, and error handling
• Managing tool metadata and supporting semantic search over available tools using a vector database
• Creating golden user queries, expected answers, and query variations for specific tools, intents, and network-operation scenarios
• Building automated tests to verify correct tool selection, tool parameterization, output structure, and end-to-end agent responses
• Designing evaluation workflows combining deterministic checks, human review, and LLM-as-a-judge techniques, for example using DeepEval or custom evaluation prompts
• Refining prompts, tool descriptions, schemas, and agent workflows while monitoring regressions when new tools or changes are introduced
• Developing production-quality Python code and tests using frameworks such as LangChain and LangGraph
• Collaborating with software engineers, network domain experts, and DevOps teams to deliver reliable, testable, and maintainable agentic workflows