Senior Ai Engineer / Data Scientist

The Incubate Team explores and implements cutting‐edge applications in Agentic AI and Machine Learning. The team is currently building a platform for the safe execution of AI agents: an environment where autonomous agents can run, call tools, and act on data with isolation, policy enforcement, observability, and human oversight built in.

You will join a small, hands‐on team that moves from research idea to working prototype to production‐grade component, and you will be expected to own significant parts of that journey. Experience: 4–5+ years in product development Location / Work model: Rome (Italy) / Hybrid Mandate Skills Education: Bachelor's or Master's degree in Computer Science, Statistics, or a related quantitative field ML architectures: Deep Learning, Generative AI / LLMs, predictive models Agentic AI: proven experience designing and shipping LLM-based agents (tool/function calling, multi‐agent orchestration, RAG, memory) integrated with external systems via APIs or protocols such as MCP Scripting & OS: Bash shell scripting on Linux/Unix What you will do Own the design and delivery of core components of the agent execution platform: agent runtime, tool/function-calling layer, sandboxing and isolation, policy and guardrail enforcement, and audit/observability.

Build and evaluate Gen AI solutions using state‐of‐the‐art and proprietary models; prototype quickly, measure rigorously, and harden what works into production‐quality services. Define and implement evaluation pipelines and datasets to measure agent correctness, safety, robustness, and cost (e.g., red‐teaming, prompt‐injection resistance, regression suites).

Apply data science methods — experiment design, statistical analysis, predictive modelling — to understand agent behaviour and drive product decisions with evidence. Package and deploy services as containers on Kubernetes; contribute to CI/CD, monitoring, and operational tooling.

Provide technical leadership: lead design reviews, set engineering standards for the team, and mentor less experienced engineers. Collaborate with product, security, and platform teams; document designs and share findings through demos and technical write‐ups.

Track the agentic/LLM ecosystem and bring relevant techniques, tools, and research into the team's roadmap. What we are looking for: BE/BTech or above in Computer Science, Statistics, or related stream; 4–5+ years of product development experience, with a track record of shipping AI/ML features to production Extensive experience in AI/ML technologies and professional software development practices (testing, code review, version control, CI/CD) Expert‐level Python Experience developing cutting‐edge Gen AI solutions, exploring advanced AI models, and working with proprietary generative models Hands‐on experience with agent frameworks (Lang Chain, Lang Graph, Llama Index) and vector/retrieval stacks Deep knowledge of Kubernetes and container‐based deployment; Docker proficiency Bash shell scripting in Linux/Unix environments Solid understanding of secure‐by‐design principles for AI systems: least privilege, sandboxing, input/output validation, secrets handling, auditability Ability to take ambiguous problems from concept to working solution with limited supervision Excellent written and verbal communication skills; able to explain complex technical trade‐offs to mixed audiences Nice to have Java (or another JVM language) for integration with existing services Experience with MLOps/LLMOps tooling (model serving, experiment tracking, evaluation frameworks) Familiarity with agent interoperability protocols (e.g., MCP, A2 A) and tool/plugin ecosystems Exposure to cloud platforms (AWS, Azure, GCP) and infrastructure‐as‐code Knowledge of AI governance, safety, or responsible‐AI frameworks (e.g., NIST AI RMF, OWASP Top 10 for LLM Applications) Contributions to open‐source AI projects or publications Candidate Data Privacy Notice

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