ai systems engineer

Enpal

<div>
 At Enpal, we are not just a company; we are a movement. As a leading European greentech unicorn, we are on a mission to make clean energy simple, accessible, and scalable for homeowners across the continent.
 
 
 Through solar panels, heat pumps, home batteries, and EV charging, we are redefining residential energy. With Enpal Energy, we are building Europe&rsquo;s leading platform to manage and orchestrate millions of distributed energy assets &mdash; laying the foundation for the largest Virtual Power Plant (VPP) in Europe.
 
 
 Our vision: power Europe&rsquo;s transition to a fully decentralized, intelligent, and clean energy system.
 
 
 
 Job Description
 
 
 
 As a
 
 Senior AI Platform Engineer
 
 , you will design and build the internal AI Engine that powers all AI capabilities across Enpal Energy. This is not about wrapping APIs &mdash; it is about building the core infrastructure that makes AI reliable, scalable, and production-grade.
 
 
 We are looking for a systems thinker with strong engineering fundamentals and a deep understanding of modern AI systems. You care about reliability, observability, and building platforms that enable other engineers to move fast with confidence.
 
 
 What you will do
 
 
 <ul>
 <li>
 Own the design and development of the internal AI platform powering all AI features.
 </li>
 <li>
 Build a robust Agent Runtime to orchestrate complex AI workflows in production.
 </li>
 <li>
 Design scalable backend services and developer-facing APIs for AI systems.
 </li>
 <li>
 Build internal tooling for evaluation, observability, tracing, and debugging (latency, cost, quality, reliability).
 </li>
 <li>
 Define standards for AI quality, including evaluation frameworks, versioning, and reproducibility.
 </li>
 <li>
 Collaborate closely with product and engineering teams to enable fast, safe, and deterministic AI feature delivery.
 </li>
 <li>
 Own CI/CD pipelines, infrastructure as code, and production readiness of AI systems.
 </li>
 <li>
 Continuously improve performance, reliability, and cost efficiency.
 </li>
 <li>
 Contribute to architectural decisions shaping the long-term AI strategy.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 5&ndash;7+ years of software engineering experience (mid to senior level).
 </li>
 <li>
 Strong background in backend systems, platform engineering, or internal developer platforms.
 </li>
 <li>
 Strong proficiency in TypeScript and Node.js (JavaScript ecosystem).
 </li>
 <li>
 Solid understanding of modern AI system design, including agentic architectures vs. chains, tool use and function calling, and orchestration patterns.
 </li>
 <li>
 Experience in LLM APIs (e.g. OpenAI, Anthropic, DeepSeek) and AI infrastructure.
 </li>
 <li>
 Experience building observability, logging, tracing, and evaluation systems.
 </li>
 <li>
 Strong focus on reliability, determinism, and production-grade engineering.
 </li>
 <li>
 Experience building APIs and integrating complex systems.
 </li>
 <li>
 Familiarity with CI/CD tools (GitHub Actions, Azure DevOps, or similar).
 </li>
 <li>
 Strong commitment to clean, testable, and scalable code.
 </li>
 <li>
 (Senior level) Experience mentoring engineers and driving technical decisions.
 
 
 </li>
 </ul>
 Additional Information
 
 
 <ul>
 <li>
 Join Germany&rsquo;s leading green unicorn and help shape the energy transition.
 </li>
 <li>
 Work in a diverse team of 65+ nationalities united by one mission.
 </li>
 <li>
 Hybrid work model: office or remote &mdash; your choice.
 </li>
 <li>
 Our Berlin HQ offers a fully equipped startup environment (rooftop, gym, lounges, events).
 </li>
 <li>
 Structured onboarding, including a welcome session with our founder.
 </li>
 <li>
 Regular company updates, technical deep dives, and knowledge sharing sessions.
 </li>
 <li>
 Strong team culture, ownership mindset, and frequent team events.
 </li>
 <li>
 A strong feedback culture that values continuous improvement.
 
 
 </li>
 </ul>
 At Enpal, diversity and inclusion are core values. Hiring decisions are made without discrimination of any kind.
</div>

AI Platform Engineer (f/m/d)

Cortea

<div>
 
 About Us
 
 
 
 We&rsquo;re
 
 Cortea
 
 , a Berlin startup
 
 transforming audits with AI
 
 . Manual, document-heavy audits waste expert time while demand keeps rising. Our
 
 AI-powered software and specialized AI agents
 
 remove the repetitive work so auditors can focus on judgment.
 
 
 Backed by top-tier VCs with &gt;15m funding, with a working product and paying customers, we&rsquo;re rapidly scaling.
 
 
 We value
 
 first-principles thinking, speed, trust, and kindness
 
 . We build side by side
 
 in our Berlin office
 
 .
 
 
 
 Your Role
 
 
 
 We are looking for an
 
 Engineer with strong data engineering and AI systems experience
 
 to build the data, evaluation, and observability foundation for production-grade LLM agents used in complex audit workflows.
 
 
 This role sits at the intersection of
 
 backend engineering, data engineering, AI infrastructure, and LLM operations
 
 . You will work hands-on in our backend and agent architecture, building the systems that help us evaluate, monitor, debug, optimize, and continuously improve AI agents in production.
 
 
 This is
 
 not
 
 a traditional analytics, BI, or dashboarding role. You should expect to write production code, design infrastructure, work inside backend systems, and directly improve the quality, cost, reliability, and performance of LLM-based agents.
 
 
 
 What You&rsquo;ll Do
 
 
 
 You will help building and operating the technical infrastructure around our AI agents, with a focus on data infrastructure, evaluation, observability, and optimization. Your work will include:
 
 
 <ul>
 <li>
 Building online and offline evaluation systems for LLM agents, including pipelines that use golden datasets, ground-truth data, human review workflows, and experiment results.
 </li>
 <li>
 Creating automated quality gates so changes to prompts, context, models, or agent logic can be tested before reaching production.
 </li>
 <li>
 Analyzing large volumes of agent traces and executions to identify failure modes, quality regressions, latency issues, reliability gaps, and cost optimization opportunities.
 </li>
 <li>
 Working with columnar data stores and analytical databases such as BigQuery, ClickHouse, or similar technologies.
 </li>
 <li>
 Building reliable data retention and replay mechanisms for long-term analysis of production agent behaviour.
 </li>
 <li>
 Creating observability tooling for trace analysis, experiment monitoring, production dashboards, logging, tracing, and debugging.
 </li>
 <li>
 Working inside our core backend and agent architecture, including building new agents or improving existing agents when needed.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 You will fit into this role if you:
 
 
 <ul>
 <li>
 Have strong Python and/or backend engineering experience.
 </li>
 <li>
 Have strong SQL skills and are comfortable working with large datasets.
 </li>
 <li>
 Have deployed and operated systems in the cloud, ideally on GCP.
 </li>
 <li>
 Have practical experience designing data pipelines, ETL/ELT workflows, event-processing systems, or feedback loops for production data.
 </li>
 <li>
 Are comfortable working with analytical databases, data warehouses, columnar stores, and high-volume event or trace data.
 </li>
 <li>
 Understand system design, reliability, observability, monitoring, logging, debugging, and operational trade-offs.
 </li>
 <li>
 Can work in complex existing systems and quickly build a mental model of how they operate.
 </li>
 <li>
 Bring senior-level engineering judgment: you can make architectural decisions, communicate trade-offs, and build systems that other engineers can extend.
 </li>
 <li>
 Are comfortable with ambiguity, able to reason from first principles, and excited to build infrastructure for AI systems that are actively used in production.
 
 
 </li>
 </ul>
 Nice-to-haves that are a plus:
 
 
 <ul>
 <li>
 Building infrastructure around LLM-based products or agentic systems, including optimizing LLM usage, context windows, reasoning tokens, or model selection.
 </li>
 <li>
 Working with production traces from complex distributed systems.
 </li>
 <li>
 Building internal platforms for engineers, domain experts, or operations teams.
 </li>
 <li>
 Using workflow orchestration systems such as Temporal or similar.
 </li>
 <li>
 Familiarity with audit, finance, compliance, or other high-accuracy domains.
 </li>
 <li>
 Experience in an early-stage startup or fast-moving engineering environment.
 
 
 </li>
 </ul>
 
 No one checks every box. If you&rsquo;ve shipped retrieval systems and like owning evaluations and pipelines, let&rsquo;s talk.
 
 
 
 
 What we offer
 
 
 
 <ul>
 <li>
 High impact &amp; growth: Shape strategy at a scaling AI startup from day one
 </li>
 <li>
 Mission-driven culture: Ambitious team valuing first-principles thinking and bold ideas
 </li>
 <li>
 Attractive compensation: competitive salary plus significant equity
 </li>
 <li>
 Personal development: Learning budget for courses and conferences
 </li>
 <li>
 Startup perks: Flexible vacation, team lunches, retreats, central Berlin office
 
 
 </li>
 </ul>
 
 Interview process
 
 
 
 <ul>
 <li>
 First Call &mdash; Intro to Cortea with our Talent Partner Adriana
 </li>
 <li>
 Second Call &mdash; Technical interview with Jendrik
 </li>
 <li>
 Third Call &mdash; Deep dive into our culture with our Co-Founder Philipp
 </li>
 <li>
 On-site Day (Berlin) &mdash; Meet the team and work on a real problem together
 
 
 </li>
 </ul>
 
 We&rsquo;re an equal-opportunity team and encourage women and underrepresented groups to apply.
 
 
 
</div>

Software Engineer, Data & AI Platform (m/f/x)

Cortea AI

<div><h1 class="jobSectionHeader">About us</h1>
We&rsquo;re Cortea, a Berlin startup transforming audits with AI. Manual, document-heavy audits waste expert time while demand keeps rising. Our AI-powered software and specialized AI agents remove the repetitive work so auditors can focus on judgment.
Backed by top-tier VCs with &gt;15m funding, with a working product and paying customers, we&rsquo;re rapidly scaling.
We value first-principles thinking, speed, trust, and kindness. We build side by side in our Berlin office.<h1 class="jobSectionHeader">
Your Role</h1>
We are looking for an Engineer with strong data engineering and AI systems experience to build the data, evaluation, and observability foundation for production-grade LLM agents used in complex audit workflows.
This role sits at the intersection of backend engineering, data engineering, AI infrastructure, and LLM operations. You will work hands-on in our backend and agent architecture, building the systems that help us evaluate, monitor, debug, optimize, and continuously improve AI agents in production.
This is not a traditional analytics, BI, or dashboarding role. You should expect to write production code, design infrastructure, work inside backend systems, and directly improve the quality, cost, reliability, and performance of LLM-based agents.<h1 class="jobSectionHeader">
What you&rsquo;ll do</h1>
You will help building and operating the technical infrastructure around our AI agents, with a focus on data infrastructure, evaluation, observability, and optimization. Your work will include:<ul><li>
Building online and offline evaluation systems for LLM agents, including pipelines that use golden datasets, ground-truth data, human review workflows, and experiment results.</li><li>
Creating automated quality gates so changes to prompts, context, models, or agent logic can be tested before reaching production.</li><li>
Analyzing large volumes of agent traces and executions to identify failure modes, quality regressions, latency issues, reliability gaps, and cost optimization opportunities.</li><li>
Working with columnar data stores and analytical databases such as BigQuery, ClickHouse, or similar technologies.</li><li>
Building reliable data retention and replay mechanisms for long-term analysis of production agent behaviour.</li><li>
Creating observability tooling for trace analysis, experiment monitoring, production dashboards, logging, tracing, and debugging.</li><li>
Working inside our core backend and agent architecture, including building new agents or improving existing agents when needed.</li></ul><h1 class="jobSectionHeader">
Qualifications</h1>
You will fit into this role if you:<ul><li>
Have strong Python and/or backend engineering experience.</li><li>
Have strong SQL skills and are comfortable working with large datasets.</li><li>
Have deployed and operated systems in the cloud, ideally on GCP.</li><li>
Have practical experience designing data pipelines, ETL/ELT workflows, event-processing systems, or feedback loops for production data.</li><li>
Are comfortable working with analytical databases, data warehouses, columnar stores, and high-volume event or trace data.</li><li>
Understand system design, reliability, observability, monitoring, logging, debugging, and operational trade-offs.</li><li>
Can work in complex existing systems and quickly build a mental model of how they operate.</li><li>
Bring senior-level engineering judgment: you can make architectural decisions, communicate trade-offs, and build systems that other engineers can extend.</li><li>
Are comfortable with ambiguity, able to reason from first principles, and excited to build infrastructure for AI systems that are actively used in production.</li></ul>
Nice-to-haves that are a plus:<ul><li>
Building infrastructure around LLM-based products or agentic systems, including optimizing LLM usage, context windows, reasoning tokens, or model selection.</li><li>
Working with production traces from complex distributed systems.</li><li>
Building internal platforms for engineers, domain experts, or operations teams.</li><li>
Using workflow orchestration systems such as Temporal or similar.</li><li>
Familiarity with audit, finance, compliance, or other high-accuracy domains.</li><li>
Experience in an early-stage startup or fast-moving engineering environment.</li></ul>
No one checks every box. If you&rsquo;ve shipped retrieval systems and like owning evaluations and pipelines, let&rsquo;s talk.<h1 class="jobSectionHeader">
What we offer</h1><ul><li>
High impact &amp; growth: Shape strategy at a scaling AI startup from day one</li><li>
Mission-driven culture: Ambitious team valuing first-principles thinking and bold ideas</li><li>
Attractive compensation: competitive salary plus significant equity</li><li>
Personal development: Learning budget for courses and conferences</li><li>
Startup perks: Flexible vacation, team lunches, retreats, central Berlin office</li></ul><h1 class="jobSectionHeader">
Interview process</h1><ul><li>
First Call &mdash; Intro to Cortea with our Talent Partner Adriana</li><li>
Second Call &mdash; Technical interview with Jendrik</li><li>
Third Call &mdash; Deep dive into our culture with our Co-Founder Philipp</li><li>
On-site Day (Berlin) &mdash; Meet the team and work on a real problem together</li></ul>
We&rsquo;re an equal-opportunity team and encourage women and underrepresented groups to apply.</div><div></div>

Recare Gmbh

<div>About Recare 
As one of the leading German HealthTech companies, we are reshaping discharge management &ndash; technology-driven, patient-centered, and free from bureaucracy. In addition to our market-leading SaaS platform, we develop AI solutions that radically simplify processes in hospitals and for aftercare providers, relieve healthcare professionals, and refocus attention on patients. Today, we already connect two-thirds of all German hospitals with over 650 rehabilitation clinics and 25,000 nursing and homecare providers. With currently around 100 employees, we continue to grow &ndash; and we are looking for people with character who want to help us improve the healthcare system and solve administrative complexity across care journeys in Europe. 
What you'll own as our Tech Lead (Computer Use &amp; Integrations) 
 
You'll lead building Recare's Operator, our agent that gets AI-generated clinical output into hospital systems by operating their existing software the way a person would, no bespoke interface required. It's the sharp end of our integration strategy: where a clean interface exists we use it, and where one doesn't, the agent bridges the gap. You own that bridge end to end: the agentic, computer-use automation at the front and the integration backbone behind it. 
<ul><li>
You set the technical direction for computer-use automation and integrations end to end: architecture, standards, and roadmap.</li><li>
You ensure data flows between the hospital systems and Recare products, regardless of the interface.</li><li>
You will be the team's technical backbone and escalation point, setting the bar for clarity, speed, and shipping.</li><li>
You push the frontier of agentic, computer-use automation: deciding where model-driven approaches beat deterministic ones, and making them fast, reliable, and cheap enough for production.</li><li>
You make it run in the real world, robust across the messy reality of hospital IT, even if that means being close to the customer. This is the hard part, and the most satisfying.</li><li>
You build full-stack and hands-on, from the desktop agent to the APIs and telemetry around it, and you stay close to the code.</li><li>
You partner with product teams to turn ambiguous problems into shippable plans, and you go on-site with customers when that's what it takes to get it working.</li><li>
You invest in the observability foundations that make production trustworthy.</li></ul> 
How we work: 
<ul><li>
We're AI-native. Our engineers reach for frontier coding agents every day to move fast across the whole stack, and we want strong, opinionated views on how to wield them well.</li><li>
We build on the best models available and adopt new capabilities as they ship, not a release later.</li><li>
Human-in-the-loop by default. This is healthcare: AI proposes, people stay in control, and we design the approval and validation loops that make that real.</li><li>
We invest in the unglamorous foundations. Engineers get the time to build the eval harnesses, guardrails, and observability that make AI trustworthy in production, not just the feature on top.</li><li>
We ship and observe: always deployable, telemetry-driven, fix in the open.</li></ul> 
Here's how we picture you as our Tech Lead (Computer Use &amp; Integrations) 
 
<ul><li>You've led technical direction for a team or a significant system and driven it end to end into production, and you can point to what you actually shipped.</li><li>
You're a full-stack builder who's comfortable jumping across the stack (a TypeScript/Electron desktop one day, a Golang API or data layer the next), and you default to building rather than waiting.</li><li>
You're genuinely AI-pilled: you use AI coding agents daily, have real opinions about them, and you're excited (not nervous) to build agentic, computer-use systems.</li><li>
You're ambitious but frustration-tolerant. Hospital IT is complicated and progress is hard-won; you stay relentless, get your hands dirty, and work directly with customers when that's what moves things forward.</li><li>
You understand how to design and operate scalable backend systems, including APIs, data models, and integration-heavy architectures.</li><li>
You think in systems and trade-offs, and you actively drive for robust, maintainable, and simple solutions.</li><li>
You take ownership of your domain end-to-end &ndash; from conception to production and ongoing operations.</li><li>
You're fluent in German and English. German matters here because the clinical systems and the on-site hospital work happen in it.</li><li>
You are willing to travel (very) occasionally to hospitals together with a Technical Product Manager to work hands-on on integration challenges and iterate directly on site.</li><li>
You are based in Germany.</li><li>
You care about security, reliability, and data protection, especially in healthcare environments.</li><li>
Nice to have: experience with healthcare IT systems (HIS, KIS, PVS) and interoperability standards such as HL7 v2 or FHIR; Go experience is a plus.</li></ul> 
What we offer:<ul><li> 
Purposeful work &ndash; your role will have a positive impact on patients, their families, and healthcare professionals.</li><li>
Company culture &ndash; we believe in flat hierarchies that promote high performance and strong team dynamics. We foster an environment characterized by mutual respect, loyalty, and recognition. Together, we strive for our goals &ndash; and expect the same from you.</li><li>
Flexibility &ndash; want to pick up your child from daycare? Like to exercise during lunch? We'll support you. We are a remote-friendly company offering flexible working hours. Workations are also possible by arrangement.</li><li>
Edenred card &ndash; which you can use according to your needs.</li><li>
Extra vacation day &ndash; so you can celebrate your birthday with your loved ones, you'll have the day off.</li></ul></div>

Tech Lead (Computer Use & Integrations) (m/w/d)

CLERA

<div><h3 class="jobSectionHeader">About the Role</h3>
Join a lean, high-impact engineering team at a Series A PropTech startup building agentic AI systems that observe, decide, and act on real-world property operations &mdash; with humans in the loop. This is a full-stack, end-to-end ownership role: you'll modernize legacy systems, design autonomous workflows, and turn messy operational processes into clean, production-ready software. If you thrive in small teams, think like a founder, and want your work to matter immediately, this role is for you.<h3 class="jobSectionHeader">
What You'll Do</h3><ul><li>
Own features end-to-end, learning the business deeply enough to drive solutions independently.</li><li>
Design and build agentic AI workflows for guest communication (chat and voice), operational decisions, and property management tasks.</li><li>
Modernize legacy systems and redesign data structures to meet evolving product requirements.</li><li>
Shadow real operational workflows to uncover inefficiencies, workarounds, and hidden steps &mdash; then turn them into reliable software.</li><li>
Scope, ship, and iterate on problems rather than just working through a ticket queue.</li><li>
Collaborate closely with internal teams to align product and engineering direction.</li><li>
Operate with high agency and ownership, delivering results rapidly and safely.</li></ul><h3 class="jobSectionHeader">
What We're Looking For</h3>
Required:<ul><li>
Demonstrable engineering experience you can showcase during the hiring process.</li><li>
Strong proficiency in TypeScript and React for full-stack development.</li><li>
Fluent spoken and written English with excellent communication skills &mdash; including asking the right questions to unblock work.</li><li>
Proven track record of shipping quickly while exercising sound judgment about acceptable trade-offs.</li><li>
Ability to self-manage: plan work, communicate progress, and flag blockers proactively.</li><li>
Comfort working in an agentic engineering style (e.g., running multiple AI coding agents and terminals in parallel).</li><li>
Familiarity with Express, PostgreSQL, MongoDB, and AWS; experience with Linear and Notion for tracking and documentation.</li><li>
Strong product taste &mdash; attention to user experience down to messaging and interaction wording.</li><li>
Willingness to relocate to Berlin, Germany and work from the office regularly.</li><li>
Eligibility to work in Germany without visa sponsorship (sponsorship is not available).</li></ul>
Nice to Have:<ul><li>
Experience with agentic AI or AI agent systems.</li><li>
Prior startup experience or a founder mentality.</li><li>
Background in hospitality or PropTech domains.</li><li>
Strong product sense and product-minded approach to engineering.</li></ul><h3 class="jobSectionHeader">
Compensation &amp; Benefits</h3><ul><li>
Salary: $90,000 &ndash; $110,000 USD annually</li><li>
Small, accountable team focused on outcomes over meetings</li><li>
High-impact work in a fast-growing AI-native platform</li><li>
On-site role in Berlin with a collaborative, startup environment</li></ul><h3 class="jobSectionHeader">
Location</h3>
This is an on-site role based in Berlin, Germany. Candidates must be willing to relocate to Berlin and work from the office regularly. Visa sponsorship is not available &mdash; candidates must already be eligible to work in Germany.</div>

Product Engineer (Full-Stack / Agentic AI)

develop

<div>
 
 
 AI/ML Engineer | B2 German + English | AI Transformation | Global Scale-Up
 
 
 
 
 
 
 I am working with an incredibly well-funded, establishing global company that is reinventing the future of work by acquiring services businesses and transforming them from the inside out using frontier AI.
 
 
 
 
 
 My client are expanding their team globally and looking for a Senior ML/AI Engineer to design, deploy, and scale real-world AI systems that turn complex, legacy workflows into production-grade business value.
 
 
 
 
 
 
 
 Skills:
 
 
 
 <ul>
 <li>
 AI/ML System Design
 </li>
 <li>
 Production-grade Python
 </li>
 <li>
 LLMs &amp; Agentic AI
 </li>
 <li>
 Retrieval-Augmented Generation (RAG)
 </li>
 <li>
 Computer Vision
 </li>
 <li>
 Cloud &amp; ML Ops
 </li>
 <li>
 Reinforcement Learning
 </li>
 <li>
 Data Engineering (Messy/Legacy Data)
 </li>
 <li>
 Commercial and Product Mindset
 </li>
 </ul>
 
 
 
 
 
 
 Information:
 
 
 
 
 4/5 stage interview process
 
 
 Berlin based ideal (Hybrid) &ndash; 2 days on-site ideal,
 
 
 B2 German &amp; English speaking
 
 
 Salary: &euro;100,000 &ndash; &euro;150,000
 
 
 
 
 
 If this sounds interesting and you would like to learn more, please apply and or reach out to me on LinkedIn and we can set up a call!
 
</div>

Senior Machine Learning Engineer

BIT Capital

<div>
 
 
 Your role &amp; How we work
 
 
 
 
 
 
 We are hiring an AI Engineer (m/f/d) to holistically develop BIT Capital's LLM and agentic Artifical Intelligence capabilities: from the data science that turns data into investment signals, to the engineering that powers our financial intelligence agents. A strong initial focus is the build-out of &ldquo;Aion&rdquo; - our agentic research platform - that has first-class access to our data, models, and tools and is already in mainstream production, used by the investment team every day. Beyond, your mandate covers everything LLM- and agent-related across BIT, from research products for the investment team to internal tools in Sales, Marketing, Operations, and client-facing experiences.
 
 
 
 
 
 You work autonomously, from first scoping to shipping, and you self-select the use cases and projects where you can have the most impact. You report to our Carlos Bielsa (Chief AI Officer &amp; Managing Partner) and work side by side with Vlad Gheorghe, our second AI Engineer, acting as our internal expert as the frontier of AI moves. Our stack is Python, SQL, AWS, and Databricks, with models and agentic frameworks from the leading AI labs (Anthropic Managed Agents, Codex).
 
 
 
 
 
 Your priorities in this role will thus include:
 
 <ul>
 <li>
 
 Investment signal pipelines.
 
 Design and ship LLM-based extraction pipelines (prompts, retrieval, model selection, evaluations) that turn text and data into investment scores, alerts, signals, and insights reliable enough to drive decisions.
 </li>
 <li>
 
 Agentic systems behind &ldquo;Aion&rdquo;.
 
 Build and evolve the agentic systems that power Aion, along with the research skills and Python sidecars that agents execute.
 </li>
 <li>
 
 Data and tool integrations.
 
 Build the integrations that give agents performant, safe access to BIT's data and capabilities.
 </li>
 <li>
 
 Evaluations and model selection.
 
 Build automated and human-in-the-loop evaluations, regression tests, and monitoring that track accuracy, hallucination rates, latency, cost, and model uncertainty. Benchmark and select the right model per task, including open-source options.
 </li>
 <li>
 
 LLMOps at scale.
 
 Establish the LLMOps practices that keep these systems reliable at scale: versioning of prompts, configs, and models; CI/CD; error handling; fallbacks; and cost control.
 </li>
 <li>
 
 Frontier into production.
 
 Stay at the frontier of LLM and agentic AI techniques and bring new ideas into production rather than leaving them as experiments.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 The experience you bring
 
 
 <ul>
 <li>
 You have a solid data science and engineering background, with at least 2 years building software, data systems, or ML in production.
 </li>
 <li>
 You adopt the mindset of a product-minded software engineer. You have shipped your own apps and agents and can point us to a public project, repo, or product.
 </li>
 <li>
 You are fluent with the current LLM and agentic frontier, with hands-on experience using leading agentic systems (Claude Code, Anthropic Managed Agents, Codex, open-source agentic loops).
 </li>
 <li>
 You have strong Python and SQL skills with clean engineering practices, plus cloud infrastructure experience (AWS strongly preferred).
 </li>
 <li>
 You bring production discipline for probabilistic systems: evaluations, regression tests, monitoring, reproducibility, and cost awareness. A scientific approach to turning LLMs into signals and scores (ground-truth datasets, train/test/iterate) is a plus; a data science or ML background helps but is not required.
 </li>
 <li>
 You have a genuine interest in investing, or at minimum a strong drive to learn about our domain quickly and deeply, paired with sharp general intelligence and clear systems thinking.
 </li>
 </ul>
 
 
 
 
 
 2 reasons why you should not apply
 
 
 <ul>
 <li>
 You mainly use AI tools for your own productivity and have not yet taken systems into production. This role is about building and shipping AI that the whole firm relies on, so prior production experience matters here.
 </li>
 <li>
 You are looking for a finished, stable AI stack to operate and maintain. Our systems evolve quickly as the frontier moves, so you will spend much of your time building and reshaping them rather than keeping a fixed setup running.
 </li>
 </ul>
 
 
 
 
 
 Your mindset
 
 
 <ul>
 <li>
 You're an "AI Native": you use agentic AI as core infrastructure in how you work, not as a novelty.
 </li>
 <li>
 You're a "Builder": you ship working systems and improve them continuously rather than leaving ideas as experiments.
 </li>
 <li>
 You blend data science rigor with engineering pragmatism, with care for correctness, reliability, and cost.
 </li>
 <li>
 You're passionate about AI, emerging technology, and investing, and you pair technical depth with strong product judgment.
 </li>
 <li>
 You manage for outcomes, own problems end-to-end, and communicate clearly on progress, tradeoffs, and risk.
 </li>
 </ul>
 
 
 
 
 
 What we offer
 
 
 <ul>
 <li>
 Work at the frontier of applied AI in asset management, with petabytes of data and the most cutting-edge tools.
 </li>
 <li>
 Real technical direction and ownership from day one, as the internal expert while the frontier moves.
 </li>
 <li>
 Contribute to a unique success story in European asset management, surrounded by the most knowledgeable experts in the industry.
 </li>
 <li>
 A motivated, highly international team (15 nationalities) that enjoys getting together in person in Berlin and strongly supports each other.
 </li>
 <li>
 Flat hierarchies and direct interaction with our management team.
 </li>
 <li>
 Competitive compensation, relocation, and visa support if needed.
 </li>
 </ul>
 
 
 
</div>

AI Engineer (m/f/d)

Explore 366+ Ai systems engineer in Berlin this July. Find roles across top companies and apply now to boost your career.

366 ai systems engineer jobs In Berlin

AI Platform Engineer (f/m/d)

Software Engineer, Data & AI Platform (m/f/x)

Software Engineer, Data & AI Platform (m/f/x)

Tech Lead (Computer Use & Integrations) (m/w/d)

Product Engineer (Full-Stack / Agentic AI)

Senior Machine Learning Engineer

AI Engineer (m/f/d)