Senior AI Engineer

akirolabs

9d • Remote

About The Position

akirolabs is building the AI-powered platform for strategic procurement. Our mission is to elevate procurement from a tactical, cost-focused function into a true strategic value creator. By combining world-class methodology, advanced AI, and intuitive collaboration into our category management platfrom, akirolabs empowers procurement teams to deliver 4–5× higher business value beyond savings - driving innovation, sustainability, resilience, and growth. Headquartered in Berlin, akirolabs was founded in 2021 by a team of procurement and consulting veterans from Siemens, Vodafone, KPMG, and Roland Berger, and is backed by top-tier investors and European innovation grants. Recognized by leading analysts such as Kearney, Spend Matters, and the appliedAI Institute, akirolabs is shaping the next generation of strategic procurement technology. Today, akirolabs serves leading enterprises across industries - from energy and life sciences to financial services and manufacturing - helping them transform procurement into a data-driven, collaborative, and future-ready strategic function. What You’ll Do 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

Requirements

• 5+ years of experience in Data Science, Computer Science, or a related field
• Bachelor+ degree in Computer Science, Information Technology, or a related field
• 3+ years in NLP is a must
• Main direction is agents and agentic orchestration

Nice To Haves

• Having published scholarly papers is a big plus

Responsibilities

• 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 – 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

Benefits

• Be part of a recognised leader in AI-driven procurement technology company, creating innovative services that have a substantial impact on our enterprise customers
• Remote-first – work where you work best, whether from home or in a hybrid mode from our office in a great location in Berlin
• 30 days of vacation
• Working in an international team and context, official language is English
• Business trips within Europe might be expected on demand (3-4 per year)
• Team building company events, social activities

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 1-10 employees