akirolabs

Security Engineer

• Support the implementation and improvement of security controls across our cloud and SaaS environment
• Help identify, assess, and track security risks, vulnerabilities, and remediation actions
• Contribute to application, infrastructure, and cloud security reviews
• Assist with security testing activities such as vulnerability validation, configuration reviews, and basic threat analysis
• Help maintain security documentation, standards, and internal procedures
• Support compliance and audit-related activities by gathering evidence and helping track security requirements
• Partner with cross-functional teams to raise security awareness and encourage security-by-design thinking
• Continuously learn, improve, and contribute ideas to strengthen the overall security program

Information Security Engineer

AI Engineer

• AI feature design & integration into product flows
• Own AI feature requirements jointly with Product
• Translate procurement logic into structured prompts, schemas, etc
• Work closely with other engineering teams
• AI infrastructure & orchestration (proxy, lambdas, streaming)
• Be able to follow existing architecture and design correct approaches for our current system
• Work comfortably with Python services, Fast API, REST APIs, streaming, and deployment constraints
• Collaborate on infra topics without being pure MLOps
• AI quality, evaluation & alignment with business logic (refinement, support, bug fixes, continuous improvements)
• Design and run evaluation pipelines for AI features, including continuous monitoring and quality upgrades
• Implement custom, business‑logic‑driven checks for LLM outputs
• Perform RAG / LLM evaluation (accuracy, consistency, hallucination controls)
• Write and maintain validation logic and guardrail code, not only “prompt tweaks”
• AI governance & EU AI Act compliance
• Work comfortably under EU AI Act constraints and internal governance
• Document model usage, data flows, and risks for each AI feature
• Define guardrails together with Product/Security teams
• Participate in training, documentation, and audits – owning building models and safe/secure AI operations
• Observability, monitoring & production robustness of AI features
• Read and interpret logs/metrics for AI components
• Specify and interpret monitoring for AI flows (latency, error rates, drift signals, usage patterns)
• Understand versioning and backwards compatibility of AI outputs and contracts with other services
• Cross‑team collaboration & stakeholder work
• Communicate clearly with Product, Engineering, Security, and Business teams
• Translate DS/ML decisions into clear Jira tickets and Confluence docs
• Walk customers/CS through AI issues, limitations, and upcoming improvements when needed
• Lead or co‑lead refinements, design reviews, and post‑mortems for AI features
• Research & exploration (models, methods, vendors)
• Research and deliver focused PoCs/MVPs based on product/tech roadmap
• Stay up‑to‑date with LLM / RAG / evaluation research (papers, blogs, open‑source) and translate relevant ideas into shippable solutions
• Justify why a specific model / architecture / vendor is chosen for our procurement use cases
• Maintain a research backlog, prioritise by product impact and feasibility, and document decisions/learnings
• Multi‑agent systems & advanced reasoning (agentic frameworks and tooling): Multi‑Agent Systems & Advanced Reasoning – Hands‑on experience with agentic frameworks (e.g., LangGraph, CrewAI, AutoGen) and advanced reasoning techniques (Chain‑of‑Thought, ReAct, Plan‑and‑Execute) to structure complex AI workflows
• Integration & Tool Management – Ability to define safe APIs, connect agents to external systems, and implement memory/state management (short‑term and vector‑based) along with RAG pipelines
• Programming & Infrastructure Expertise – Expert Python skills and deployment experience using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure) with monitoring via tools
• Evaluation, Safety & Ethics – Designing benchmarks to measure agent performance, ensuring reliability and cost‑efficiency, while implementing guardrails to prevent prompt injection and maintain ethical, legal compliance
• Strategic & Soft Skills – Translating business goals into agent workflows, critically evaluating AI outputs for errors or bias, and communicating complex AI reasoning effectively to stakeholders

Information Security Engineer

Senior AI Engineer