Вакансии

Location: Warszawa, Poland; Almaty, Kazakhstan; Belgrade, Serbia; Yerevan, Armenia; Sofia, Bulgaria; Larnaca, Cyprus; Tbilisi, Georgia; Berlin, Germany; Tallinn, Estonia; Rīga, Latvia; Vilnius, Lithuania; Lisboa, Portugal; Madrid, Spain Workplace: fully We are looking for a Senior Python Engineer: Language Proficiency: Upper-Intermediate Employment type: Full time Candidate Location: Poland, other EU countries, Kazakhstan, Serbia, Armenia, Georgia Working Time Zone: CET Start: asap Planned Work Duration: 4 months with possible prolongation 👥 Customer Description: A global mobility and urban services platform enabling users to book rides and other services while negotiating fares directly with service providers. 🧩 Project Description: The BI Analytics team develops internal analytics products powered by LLM agents.The initial scope includes a natural-language data assistant and a service for generating management presentations with AI-driven insights. ⚙️ Project Phase: Ongoing 🤝 Soft Skills: • Proactive approach • Ability to work independently 💡 Hard Skills / Must Have: • Russian language is a must • 4+ years of commercial Python backend development • Production experience with LLM agents, tool use, MCP, evaluations, and LLM APIs or agent frameworks • Strong SQL and cloud DWH experience, preferably BigQuery • OAuth, IAM, Docker, and CI/CD • Daily use of coding agents and ability to review their output ✨ Hard Skills / Nice to Have: • BigQuery and GCP • Claude Agent SDK, Anthropic API, or Strands Agents • React 📌 Responsibilities and Tasks: • Build product features from prototype to production • Develop AI agents and web services for internal analytics use cases • Integrate agents with data sources and internal systems • Set up user access, authorization, cloud deployment, and service maintenance • Build evaluations and monitoring for LLM components • Fix defects and improve solutions based on user feedback 🧪 Technology Stack: Python, Strong SQL, experience with a cloud DWH (BigQuery preferred), Docker, CI/CD, AI tools 📞 Interview stages: • English check (15 minutes) • internal technical interview (1-1,5 hour) • client interview (1 hour) • client interview – cultural fit (45 minutes) What we offer Model: B2B contract with Bonapolia - one contract, one monthly invoice Rate: negotiated per candidate seniority and client budget Payment: monthly invoice, paid on the same schedule the client pays us (30 days) Contract written under your country's law We handle the client-side paperwork: MSA, NDA, invoicing 🏢 About Bonapolia Bonapolia is a family-owned IT staff augmentation team based in Lisbon. We build engineering teams for product companies and IT consultancies across Europe and the US. More at bonapolia.com 📩 Ready to Join? We look forward to receiving your application and welcoming you to our team!

Responsibilities: — Define and own product strategy across Distru ERP, Distru Commerce, Order Agent, Distru Analytics, and the AI product suite with accountability for revenue and growth. — Lead the AI product suite development including unified data layer, agent builder, workflow builder, MCP, and headless experience. — Evangelize AI vision internally and externally, identifying product-market fit and new market opportunities. — Grow the product team from 4 to 8+ members, structuring it to serve existing ERP and Commerce customers and build new AI-first product lines. — Manage the product timeline as the company's source of truth for shipping schedules. — Implement AI-first product processes for planning, specification, design, and shipping. — Collaborate closely with CEO, VP of Engineering, Head of Sales, Head of Go-to-Market, and product team. — Own product hiring pipeline, set hiring standards, manage and coach the product team including performance management. — Set PRD standards, review PRDs, designs, mockups, and lead adoption of AI-first product processes. — Establish operating cadence with engineering, defining clear ownership between product and engineering. — Work with GTM on launches, feature enablement, AI-forward content, and maintain high-quality MCP, API docs, and knowledge base. — Run feedback loops from customers, CS, and Sales, build key customer relationships, and track feature adoption company-wide. Requirements: — 10+ years in product management with at least 4 years leading product teams. — Proven product leadership including building and running product organizations, hiring, coaching, and making tough personnel decisions. — Experience shipping AI product lines such as MCPs, Agent Builders, Workflows, Copilots in production. — Deep technical knowledge of modern SaaS and AI stacks including infrastructure, data, AI models, full-stack development, and production concerns like reliability and observability. — Outcome-oriented with ability to measure product decisions by revenue impact. — Hands-on approach including writing PRDs and working closely with engineers. — Strong AI fluency: building with AI tools, setting AI-first processes, evaluating AI workflows with observability and feedback loops. — Experience in ERP, accounting, cannabis, or supply chain software is a strong plus. — Experience leading product at a B2B SaaS company at a similar stage. — Founder experience is a plus. Benefits: — Fully remote position across 4 continents. — Competitive salary range $250,000 - $400,000 per year depending on experience and skills. — Equity included. — Employee-friendly option terms with a 10-year exercise window after 2 years. — 18 days PTO plus 11 holidays (sick days excluded). — Medical, dental, vision, and 401(k) for US employees. — Access to best AI tools and a generous AI stipend. — Yearly in-person team offsites. — Company-wide AI growth initiatives including classes, workshops, demo days, and hackathons. Interview process includes application questions about AI experience, leadership interview, AI product-market fit discussion, co-building session, technical leadership interview, take-home assignment, team meetings, and references. For full details and benefits visit distru.com/careers.

Location: Berlin Office; Bosnia; Romania; Norway; Estonia; Latvia; Slovenia; Netherlands; Hungary; Moldova; Kosovo; Portugal; Poland; Serbia; Germany; Austria; Finland; Montenegro; London Office; Albania; Lithuania; Slovakia; Ireland; Bulgaria; Denmark; Belgium; Czech Republic; United Kingdom; Croatia; Spain; Greece Workplace: Remote The AI orchestration of your wildest imagination. n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we’re changing the way people bring systems together and scale ideas for impact. Since our founding in 2019, we’ve grown into a diverse team of over 260 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we’ve: - Cultivated a community of more than 650,000 active developers and builders - Earned 190K+ GitHub stars, making us one of the world’s Top 40 most popular projects - Backed by top investors, from Sequoia’s first German seed to our SAP's recent strategic investment - bringing us to a $5.2bn valuation That’s the company we’ve built. Now we’d love to see what you can build. If you’re applying, try n8n out - whether you’re technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register http://app.n8n.cloud/register. We’re in a defining moment of an incredible journey. Come and build with us. STAFF PLATFORM ENGINEER, AGENTIC ENGINEERING Developer Productivity · AI Coding Agents · Developer Platform Our ambition: an engineering organisation where humans and agents work as one continuously learning system, turning frontier AI capabilities and real-world feedback into more ambitious product development. We want n8n to be the reference for how this is done, without compromising quality, resilience or trust. Your main goal is to make that real. This is a Staff individual contributor role in Developer Platform and the technical driving force behind ACDC (Agent-centric Development Cycle), our engineering-wide initiative for agentic development. Nobody has a playbook for this yet. You'll write ours. You won't start from zero. Agents wired into Linear already automate around 80% of the development cycle on one of our developer platform projects, alongside pilots for insight, feature-flag and PR-review agents and a shared agent harness. Your job is to take this from promising experiments to the way n8n builds software. This role is for someone who thinks about this problem constantly. You run agents all day, rebuild your own workflow every time the frontier moves, and have more ideas than time. You'll stay hands-on, building the first versions yourself, and shape how the work grows beyond one person. WHAT YOU'LL DO SET DIRECTION AND OWN THE OUTCOME - Identify where agentic development can make the greatest difference, using developer feedback, existing experiments and engineering performance data. - Set the strategy and priorities across agent execution, repository readiness, CI, security and developer workflows. - Make build, buy or pass decisions on tools and vendors, and own the cost and value trade-offs, including AI spend. - Make decisions where requirements are incomplete and the trade-offs between autonomy, reliability, security and review effort are still emerging. - Build alignment through technical proposals, clear decisions and working software, and report progress and impact to engineering leadership. BUILD THE FOUNDATIONS - Design and build isolated execution environments where agents can work with the right access to code, tools and context, without exposing secrets or sensitive systems. - Own the safety model: which task categories agents may attempt, what they must never touch, and where human review is required, partnering with Security on sensitive areas like auth, billing, permissions and data handling. - Make n8n's monorepo agent-ready, working with Architecture and senior engineers on repo structure, testability, boundaries and the context agents need. INTEGRATE AGENTS INTO HOW WE WORK - Build repeatable workflows that take Linear issues through agent execution, self-verification and review to merged PRs, across a growing range of task types. - Integrate agentic workflows with GitHub, CI, test infrastructure and code review, so the agentic path becomes the easiest path for engineers. - Extend the loop beyond coding: connect earlier signals like product research and customer requests, and later ones like production metrics, so agents contribute across the whole cycle. - Open it up beyond engineering, so PMs, designers and others can turn a well-defined issue into a reviewed, mergeable change. - Shape review practices, such as PR evidence that shows what changed, what ran, what risks remain and where human judgment is needed. MEASURE WHAT WORKS - Build benchmarks from real historical engineering tasks to evaluate output quality, failure modes, review burden and production risk. - Define and track quality and adoption signals, such as reviewer acceptance rate, CI pass rate, rework rate and developer satisfaction. - Use data and feedback to change course, retire what doesn't work, and build trust across engineering. REQUIREMENTS MUST-HAVES - 🔥 Frontier obsession: You live at the frontier. You try new models and tools as they land, and you have strong, evidence-backed opinions on what's real and what's hype. - 🧭 Staff-scope ownership: You’ve led complex platform, DevEx or engineering productivity initiatives across teams, from defining the problem to sustained adoption and measurable impact, where there was no established approach to follow. - 🤖 Agentic depth: You use coding agents daily as a power user, and you've built infrastructure around them, such as repo context and instructions, tool or MCP integrations, sandboxed execution or agent workflows in CI, that other engineers rely on. - 🎯 Product mindset for internal platforms: You treat engineers as your customers. You start from real friction, prioritise by impact, make build-vs-buy calls, weigh cost against value, and let adoption tell you whether something works. - 🤝 Direction without authority: You've set technical direction that multiple teams followed, through proposals, design reviews and credibility with senior engineers across Platform, Product Engineering, AI, Security and Architecture. - 🔐 Safety judgment: You've made real decisions on permissions, secrets, sandboxing, sensitive code paths and human-in-the-loop review, and can explain the trade-offs. - 📊 Measurement that drives decisions: You've built evaluations, benchmarks or quality metrics and used them to change course or retire things that didn't work. You care about outcomes, not lines of AI-generated code. - ✍️ Writing that changes decisions: Your technical proposals and documentation have shifted what teams did. NICE-TO-HAVES - 📦 TypeScript monorepos: You have worked in a large TypeScript, Node.js or JavaScript monorepo. - ⚙️ Developer platforms: You have experience with GitHub Actions, Linear, test infrastructure, preview environments or internal developer platforms. - 🧑‍🤝‍🧑 Growing a team: You've mentored engineers or helped shape a new team as an initiative grew beyond one person. - 🌍 Open-source communities: You have contributed to open-source or source-available projects with active developer communities. - 🏢 B2B SaaS context: You understand environments where reliability, permissions, data handling and customer trust are central. - 🔗 Workflow automation: You're familiar with workflow automation, integration platforms, AI orchestration or developer-facing products. WHY JOIN US? At n8n, you'll define how autonomous AI agents become a trusted part of engineering inside one of Europe's fastest-growing AI-native infrastructure companies. Your work will shape the platform foundations, safety model, evaluation framework and developer workflows that decide whether agents can contribute meaningfully to production engineering without lowering the quality bar. You'll join a remote-first team with high autonomy, high visibility and a strong builder mindset. Because this is a first-of-its-kind role, you'll set direction, influence engineering culture, and create learnings that may inform both our internal engineering and n8n's product thinking. Sound like a challenge you're excited to take on? Apply now, and help us build the future of automation. n8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status. We can sponsor visas to Germany; for any other country, you need to have existing right to work. Our company language is English. You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n https://www.notion.so/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35?pvs=21 (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35). Location disclaimer: If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future. BENEFITS - Competitive compensation 💸 – We offer fair and attractive pay. - Ownership 💪 – Our core value is to “empower others,” and we mean it—you’ll get a slice of n8n with equity. - Work/life balance 🏖️ – We work hard but ensure you have time to recharge: - Europe: 30 days of vacation, plus public holidays wherever you are. - US: 20 vacation days, 8 sick days, plus public holidays wherever you are. - Health & wellness 🩺 – - Europe: We provide benefits according to local country norms.* - US: Multiple low-premium, low-deductible medical plans with coverage for individuals and families—plus a no-cost premium HDHP option with a pre-seeded HSA—along with dental and vision coverage. - Future planning 💰 – - Europe: We provide pension contributions according to local country norms.* - US: 401(k) retirement plan with a 4% employer match. - Financial security 🛡️ – - Europe: We provide benefits according to local country norms.* - US: Company-paid short-term and long-term disability insurance, plus life insurance to support you and your loved ones. - Career growth 📈 – We hire rising stars who grow with us! You’ll get €1K (or equivalent) per year to spend on courses, books, events, or coaching to level up your skills. - A passionate team 🤩 – We love our product, and we prove it with regular hackathons where we see who can build the coolest thing with it! - Remote-first 🌏 – Our team works remotely across Europe, with regular off-sites for team bonding. Some roles, like sales in the US, are hybrid—please check the job description. - Giving back 🤝 – We're big fans of open source, and you'll get $100 per month to support projects you care about. - Transparency 🙏 – We all know what everyone’s working on, how the company is doing—the whole shebang. *Country and/or State specific details provided in your employment agreement.

Location: Tel Aviv-Yafo, Tel Aviv District, Israel About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. Senior Application Security Engineer Join our existing R&D Security team as Aidoc's first dedicated Application Security Engineer. You will shape how application security works across R&D: choosing effective controls, building useful security tooling, and helping engineers adopt secure practices. You will work with security leadership, SecOps, product teams and engineers. Our products span Python services, web applications, desktop applications, mobile apps, and Aidoc servers in hospitals. What you will do? Lead threat modeling and security reviews across services, web, desktop, mobile and hospital applications. Focus on customer and hospital data isolation and medical-file handling. Review Python and JavaScript/TypeScript code and test applications and APIs. Turn findings into practical requirements, help developers resolve them, and verify fixes, including testing for bypasses. Improve SAST, DAST, SCA and secrets controls across the development workflow. Work with DevOps and developers to reduce noise and make results actionable. Build security automation, CI integrations and validation tests. Create reusable guidance and help teams adopt standards through design discussions, code reviews and developer coaching. Define security requirements and verify controls for clinical inference, training pipeline code and model artifacts with AI and Data Engineering. Assess developer AI tools, including coding assistants, AI agents and Model Context Protocol (MCP) integrations, for sensitive-data exposure, excessive tool permissions and untrusted inputs. Validate application risks, recommend remediation priorities, track agreed work and measure adoption and recurring defects. Support SecOps investigations and provide technical evidence to Quality and Regulatory partners. Responsibilities 5+ years of relevant experience in Application Security, Product Security, or a combination with software engineering. Built or substantially improved an AppSec program: selected priorities, introduced or improved tooling, gained developer adoption without formal authority, and measured results. Confident security review of Python and JavaScript/TypeScript, especially authorization and tenant isolation; hands-on web and API testing. Experience threat modeling and assessing systems you did not design, and translating findings into changes engineers can implement. Ability to write security automation, CI integrations and validation tests. Working knowledge of security risks in LLM applications, AI agents and MCP integrations, including prompt injection, sensitive-data exposure and tool permissions. Clear communication in English and sound judgment when explaining security trade-offs and guiding engineering teams. Requirements Electron, mobile or Windows-hosted application security; C#/.NET, PowerShell or Go. Deeper security experience with ML training pipelines, model artifacts or inference systems. Healthcare integrations, patient-data protection or regulated product development. You can develop expertise in our additional platforms and healthcare domain here. Your AppSec judgment and record of making a program work matter most. Our Perks: Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. Amazing and healthy breakfasts and lunches prepared daily by our personal chef! Stocked up kitchen & meal card Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. Amazing culture - collaborative, transparent & fun! Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

-Ежедневная работа с кодовым AI-агентом: например, Claude Code, Codex, Cursor и другие в агентском режиме. -Умение последовательно проводить задачу по агентскому пути: декомпозировать работу, управлять контекстом и сессиями, задавать ограничения и критерии готовности.

What you'll do Agentic engineering Architect and build a production multi-agent system that can safely take actions across Distru and our customer’s core systems Iterate and maintain the MCP that connects Distru to Claude & Codex. Own reliability, observability, and durable execution end to end.

Location: Montevideo, Uruguay; Remote.AR, Remote.LATAM-country; Remote.CO, Colombia; Rosario, Remote.LATAM-country We are looking for a hands-on Data Engineer (Middle/Senior) to design, build, and maintain reliable, scalable pipelines that keep information timely, clean, secure, and well-structured for downstream consumers. This is an execution-focused role combining pipeline development, query and cost optimization, data governance, and production monitoring. The engineer will work closely with business, analytics, and data science teams to make data available and trustworthy across the organization. The Data & AI chapter of the Passenger Journey builds and operates the data foundation that turns raw data into trusted, strategic assets for analytics, product, and business teams. The team works on Google Cloud Platform (GCP) under Agile and DataOps practices, with a tech stack centered on BigQuery and SQL, Dataform (including assertions) for transformation, and Python (Pandas) for processing and automation. Pipelines run on Cloud Run, Cloud Run Jobs, Dataflow, Pub/Sub, Cloud Storage, Cloud SQL, and Cloud Scheduler, with Git/GitLab, CI/CD, and Terraform for delivery, and IAM and policy tags for access control. Data is organized under a medallion architecture (Bronze, Silver, Gold), with cost and performance optimization (FinOps) treated as a first-class concern. Design, implement, and maintain reliable, scalable ingestion and transformation pipelines that ensure data quality, integrity, and availability for business and analytics. Optimize processing and storage by reducing execution time and costs (FinOps) across pipelines and queries to maximize the value of data. Apply data governance standards, including quality, naming conventions, cataloging, and a medallion architecture (Bronze, Silver, Gold), to ensure consistency and traceability. Protect sensitive data through role-based access control (IAM) and policy tags, ensuring compliance with applicable regulations and standards (GDPR, LGPD, ISO, and local regulations). Monitor pipelines, respond to incidents, and adapt them to new business requirements while meeting availability and performance SLAs. Enable controlled, cross-functional access to data for broad consumption. 3+ years of proven experience as a Data Engineer or in a similar role. Strong SQL skills and hands-on experience with BigQuery, including query optimization, partitioning, and clustering. Experience building and maintaining ELT/ETL pipelines and data models with Dataform (or a similar framework, such as dbt, with skills readily transferable to Dataform), including assertions. Experience with Python for data processing and automation (Pandas). Solid GCP experience across Cloud Run / Cloud Run Jobs, Dataflow, Pub/Sub, Cloud Storage, Cloud SQL, and Cloud Scheduler. Knowledge of medallion architecture (Bronze/Silver/Gold) and sound data-modeling fundamentals. Knowledge of data governance and compliance, including IAM, policy tags, and regulatory awareness (GDPR, LGPD, ISO). Experience with Git/GitLab, CI/CD, and Terraform for delivery and infrastructure as code. Experience with pipeline monitoring and observability (Cloud Monitoring; Grafana is desirable). Exposure to GenAI-assisted development and tooling, including prompt engineering, OpenAI API/SDK, Vertex AI, and MCP (desirable). Experience with API development using FastAPI / REST services (desirable). Experience with BI and data visualization tools such as Looker Studio or Google Data Studio (desirable). Ability to communicate effectively with technical and non-technical stakeholders, and experience working in Agile environments. Fluency in Spanish (the team's working language) and intermediate English proficiency for documentation and international collaboration.

Location: Belgrade, Serbia; Cluj-Napoca, Romania; Krakow, Poland; Larnaca, Cyprus; Lodz, Poland; Lublin, Poland; Remote.BG, Bulgaria; Remote.PL, Poland; Riga, Latvia; Sofia, Bulgaria; Varna, Bulgaria; Warsaw, Poland; Wroclaw, Poland We are looking for a Senior AI Engineer to help build an AI Coding Factory and shape an AI driven engineering environment for the software development lifecycle. In this role, you will design and implement AI agents, automation workflows, and orchestration frameworks while collaborating with technical and non technical stakeholders. The Education Platform is a global digital product used by millions of people across more than 180 countries. It is investing in technology modernisation, AI adoption, and new product development, with a focus on improving engineering efficiency through AI driven solutions. Design and build AI agents Design and build multi agent systems Design and build agent harnesses Develop AI powered automation workflows across the software development lifecycle Integrate LLMs with APIs tools and external services Define scalable architecture for AI driven development Establish best practices for AI driven development Collaborate with engineering teams managers and business stakeholders Communicate technical concepts to technical and non technical audiences Present technical recommendations clearly to technical and non technical audiences Strong software engineering background with hands on AI and LLM experience Proven experience building AI agents Proven experience building automation workflows Good understanding of LLMs Good understanding of prompt engineering Good understanding of RAG Good understanding of agent orchestration Experience with API integrations Experience with tool integrations Strong architectural skills Strong problem solving skills Excellent communication skills Excellent stakeholder management skills Ability to work independently Ability to influence technical direction Experience with AI coding agents Experience with software development lifecycle automation Familiarity with LangGraph Familiarity with AutoGen Familiarity with CrewAI Experience with MCP Experience with AWS

Location: Remote, Worldwide Workplace: remote About Distru Distru is the #1 ERP in the cannabis industry with $15B in sales processed through our platform. We've built a battle-tested ERP and B2B eCommerce platform that powers inventory, manufacturing, sales, and logistics, and we're now building AI infrastructure on top of it to give commercial businesses their all-in-one AI stack. We're growing and profitable, with 5/5 stars on Glassdoor. Our investors include Felicis Ventures, Global Founders Capital, Poseidon Asset Management, and Village Global, who have funded companies such as Shopify, Cruise, HelloFresh, Facebook, Slack, and Opendoor. Get to know the team, our culture and our full benefits at distru.com/careers! The Role AI is at an inflection point for enterprise use, and AI assistants like Claude, Codex, and Grok are seeing record adoption at work. We believe the system of record has never been more valuable for organizing the data AI acts on. We started with our AI Order Agent, now rolled out across our customer base, which lets buyers submit orders from any source in any format. It's the first piece of a much bigger agentic ecosystem we’re building, and we're moving most of our engineering effort to AI-first work to build it. You'll work directly with our Director of AI Engineering to own the technical buildout of our AI product suite, including: Agentic harness: a multi-agent system that safely operates across a business's core tools (ERP, CRM, spreadsheets, calendars, email, analytics, compliance systems) MCP: our MCP that connects Distru to external AI harnesses Context Layer: our context layer that ingests customer data, builds memories and profiles, and feeds back into our harness to create more personalized AI experiences for our customers Evals: the eval suites that make our agents reliable in production And more… You’ll be working directly on the AI system from the ground up and make strong, opinionated calls on the agentic stack and where it goes next. The AI space moves fast and the specifics will change, so this technical vision is something you'll mold. You'll report to the VP of Engineering and the Director of AI Engineering, and work closely with the rest of the product team, eng team, and our customers. What you'll do Agentic engineering Architect and build a production multi-agent system that can safely take actions across Distru and our customer’s core systems Iterate and maintain the MCP that connects Distru to Claude & Codex. Own reliability, observability, and durable execution end to end. The harness takes real actions on customers' data, so the bar is high. Write evals to improve our agentic systems from real customer use cases Build a unified data system that pulls data from multiple sources into a singular data layer that can be exposed to Claude & Codex via an MCP Build a contextual memory system that ingests our customers' data and improves how our agents work for them Set the architectural standards for how agents are built, tested, and shipped at Distru, and bring the rest of eng along AI research & experimentation Keep pace with the latest agentic frameworks, harnesses, toolkits, models, and bring in better approaches as they emerge Rapidly prototype new ideas to present to our team and our customers Engineering workflow Build hands-on with Claude Code and similar tools as part of your own workflow Improve our agentic coding workflow and bring new discoveries to the team What success looks like at 6 months You've shipped core improvements to our harness in production that our customers use daily, with clear observability and iteration for improvement You’ve shipped and iterated on many MCP tools and improvements Every agent you own has an eval suite and observability, so the team catches regressions before customers do You own the architecture of the agentic stack, and other engineers build against patterns you set You’ve built prototypes on how our agentic infrastructure can improve (i.e. a new way to retrieve memories, an agentic onboarding process for our customers) You’ve raised the technical bar on at least one thing the team was doing the slow way What we look for AI fluency For every AI role, we look for three things: Tool fluency: you build with Claude Code or similar every day, you've built your own skills, agents, or workflows, and you can explain why your setup looks the way it does. Workflow fluency: you write evals before you trust a prompt, and you know when a model is the wrong tool and plain code is the right one. Build fluency: you've put agents in front of real users, with guardrails, observability, and a way to roll back. You use AI tools daily and can tell us specifically where your fluency is strong and where you're still building it. Must have 7+ years in full-stack development, ideally on B2B SaaS applications Multi-agent harnesses: hands-on experience building multi-agent harnesses in production, not just prototypes or personal projects MCPs: you've built MCPs that are used in production Production systems: a strong grasp of reliability, observability, permissions, and safe workflow execution Product and engineering: you've operated as both, and you're comfortable owning scoping and decisions, not just implementation Modern stack: proficiency in React, TypeScript, Node, PostgreSQL, GraphQL, and LangGraph, and you pick up new tools and frameworks quickly Startup agility: you've worked at an early-stage startup (under 20 engineers) and you’ve been the one setting direction in that ambiguity, not waiting for it Low ego: you're team-first and measure success by what shipped and whether it worked, not by internal politics Influence : you’ve shaped roadmap, not just executed it Clear communication: you raise concerns and propose solutions before being asked Strong signal Background building supply chain, ERP, CRM, B2B marketplace, or accounting software UX design experience Agentic systems work beyond the must-haves, such as evaluation frameworks or agent-to-agent protocols Experience using Claude Code (or similar) to build products on your own Cannabis industry experience How we work We love building with AI. Trying new models the week they drop, building agents for fun, and forming strong opinions on what works. We invest in it with company-wide AI growth with classes and workshops, AI demo days, AI hackathons, and access to best-in-class models and tools. Taste in building. A lot of this role comes down to knowing what to build, what to cut, and what a great agentic experience feels like for the user. We stay close to the customer. You'll talk to customers and our GTM team directly, not through a chain of tickets. You'll build on what we've learned. You'll have access to the team's combined AI knowledge and the processes and skills we've built. For the full picture of our culture and who thrives here, see distru.com/careers . Benefits Our careers page is the best way to get to know us: the full benefits, our yearly offsites, who thrives here, and what the team says about working at Distru. Here are a few highlights (exact benefits vary by country and employment type): Fully remote across 4 continents Employee-friendly option terms: after 2 years, a 10-year window to exercise if you leave 18 days PTO + 11 holidays (sick days don't count toward PTO) Medical, dental, vision + 401(k) for US employees The best AI tools available and a generous AI stipend for everything else Yearly in-person team offsites Interview process Application questions: three short written questions in Lever on how you build with LLMs Recruiter screen (30 min): your background, the most complex AI product you've worked on, and your personal AI tool stack Technical interview (45–60 min): a deep dive into a complex product you've built, a live harness design discussion, and a screen-share walkthrough of your day-to-day setup Harness take-home (3–4 hours): spec a real feature on our agentic harness across product and UX, system design, and implementation details Take-home review (60 min): a technical deep dive into your submission with two engineers, including how your design holds up when a constraint changes References and offer Distru was formed by an environment of mutual respect and trust made up by people working together without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by law. We believe that diversity and inclusion among our team members is critical to our success and we proactively strive to recruit, develop and retain the best and brightest people from the most diverse candidate pools we can find all over the world. Where you land in the range depends on your experience and skills.

Location: Remote Workplace: Remote Kit https://kit.com/ is the email marketing platform experts choose to grow their audience, deepen their relationships, and build a business around the work they love. For coaches, YouTubers, authors, podcasters, and other creatives, there isn't a better marketing hub to rely on to grow audiences, automate email marketing, and sell digital products — all within one platform. More importantly, there isn't a team more committed to helping creators earn a living. We're on a mission to help creators earn $1 billion using our creator marketing platform. We have always been 100% independent and 100% remote. We are proud to have built a product that our customers love, and we look for people who have enthusiasm and belief in our mission, vision, and values to join our team. We're also embracing AI thoughtfully — both in how we build and how we hire to ensure our team is adaptable, innovative, and ready for what's next. THE ROLE Our Sales team needs a dedicated data partner, and creator commerce https://kit.com/features/commerce (how creators monetize by selling digital products) is becoming a bigger part of how Kit and our creators scale. Kit is growing, so we're looking for a Senior Analytics Engineer to own Kit's sales and commerce data from end to end. Accurate sales data gives our team a clear picture of the pipeline and the confidence to make informed decisions. That’s what makes this role so important. Your primary focus will be Sales: the dbt models that turn our CRM data into trusted pipeline, deal, and funnel metrics, and the Omni dashboards our sales leader and Senior Revenue Operations Manager use to run the business. You'll also model creator commerce data, so we understand what creators sell and earn through Kit, and you'll pick up reporting work with our Product team, such as feature usage reporting. On a small data team, we step outside our usual lanes when the need is there, so the mix will shift over time. You'll build for two kinds of consumers: people and AI. Teammates increasingly answer their own questions by querying our semantic layer through Omni's AI and MCP connections to AI tools. That means your models, metric definitions, and documentation need to be clear and correct enough for an AI agent to use them without a data teammate in the loop. This is a full-time individual contributor role for someone who likes being close to the business, enjoys turning messy operational data into numbers people trust, and is happy to work on both the models and the dashboards that sit on top of them. When Sales and Product have clear, reliable data, we help more creators build more valuable businesses with Kit.   YOUR SUPPORT SYSTEM You'll report to Sam Umachi, Head of Data (Linkedin https://www.linkedin.com/in/samuelumachi/). Sales and RevOps are your primary partners, who will rely on the models and reporting you own. You'll also partner with our Product team on reporting for features like Visual Automations https://kit.com/features/automations and on how creators use Kit. Within our data team, you'll work alongside a Staff Analytics Engineer who owns org-wide semantic layer governance and modeling standards, a Senior Data Engineer who owns ingestion and pipelines, and a Senior Business Analytics Partner focused on revenue opportunities. This role has no direct reports.   WHAT YOU'LL DO - First Week: Work through our onboarding curriculum in Notion and meet the data team, our Senior Revenue Operations Manager, the sales team, and your product partners. Get set up in our core tools: dbt Cloud, GitHub, Amazon Redshift, Omni, HubSpot, Linear, Hightouch and Slack. Set up your AI-assisted development environment and learn the shared AI workflows our data team uses. Open and merge your first small pull request so you learn our review and deployment flow early. - First Month: Map how HubSpot objects (deals, pipelines and stages, companies, contacts, and owners) flow into our dbt models, and document the gaps. Take over day-to-day ownership of the sales models and Omni dashboards that teammates have been covering. Audit current sales reporting and list where definitions differ or numbers don't reconcile. Get familiar with how commerce data (products creators sell and the revenue they earn through Kit) lands in the warehouse today. Agree with RevOps and Sales on the most important questions they need answered. Review teammates' pull requests and contribute to our shared SQL, dbt, and documentation standards. Share a written reflection with the team on what you've learned and where you'd focus first. - First Six Months: Ship and maintain well-tested, documented dbt models for core sales metrics, such as pipeline, deal velocity, stage conversion, win rates, and the sales-led funnel. Expose those metrics through the Omni semantic layer, working within the team's governance standards. Rebuild or refresh the core sales dashboards so pipeline reviews and forecasting conversations run on numbers that don't need manual reconciliation. Resolve competing sales metric definitions by writing down the options and tradeoffs, aligning with Sales and RevOps, and documenting the outcome. Model creator-level commerce data, such as products sold, revenue earned through Kit, and conversion, in partnership with data engineering. Write semantic layer descriptions, metric definitions, and documentation that let Omni's AI and MCP-connected AI tools answer routine sales questions correctly, and test them against real questions from Sales, RevOps and Product. Get Sales to the point where routine questions are answered through self-serve, whether in Omni dashboards, Omni's AI, or AI tools connected over MCP, rather than one-off requests. - First Year: Be the recognized owner of Kit's sales data, the person Sales and RevOps go to first and trust without second-guessing. Give our revenue analysis work the sales and commerce models it depends on, so deeper questions about pipeline health and creator earnings can be answered quickly, thereby enabling us to make creators more successful. Leave your domains well documented and well tested, legible to new teammates, stakeholders, and the AI agents that query our semantic layer. Help raise the team's modeling quality through code review, pairing, and sharing what you learn.     WHAT WILL S.E.T. YOU UP FOR SUCCESS   Skills - Deep dbt experience. You build modular, tested, documented dbt projects, and you're comfortable with incremental models, snapshots, macros, CI, and scheduled jobs in dbt Cloud or similar. - Advanced SQL. You reason carefully about grain, joins, and window functions, and you write queries that are readable and performant on a cloud warehouse. - Data modeling for sales and GTM. You can model deals, pipeline stages and their history, ownership changes, and funnel conversion into clean, reusable structures. You are opinionated on Kimball standards and when a concept should be a fact or dimension. - CRM data fluency. You know how sales data behaves in a CRM, including stage changes, backdated edits, and custom properties. HubSpot is preferred, but other CRM experience (e.g. Salesforce) applies just as well. We care most that you recognize common CRM patterns. - AI-assisted development. You use AI code editors and agents (such as Cursor, Claude Code, Codex, or similar) every day, and you validate their output with tests, query results, and review before anything ships. - Clear written communication. You explain metric definitions, tradeoffs, and data caveats in plain language that Sales, RevOps, and Product partners understand. - BI and semantic layer experience. You can build dashboards and semantic models in Omni, Looker, or a similar BI tool, and you design metric definitions that people and AI tools can both query correctly. - Git-based workflows. You keep pull requests small and well described, and you give thoughtful code review. - Nice to have: Redshift performance tuning (sort and distribution keys), Python for scripting or API pulls, reverse ETL, and experience with product event, billing, payments, or ecommerce data. Experiences - Around 7 or more years in analytics engineering or data engineering where you personally shipped production data models. - Several years of hands-on work building and maintaining production dbt projects. - Working directly with sales teams and RevOps, and owning reporting they relied on to run the business. - Owning a data domain over time and evolving its models as the business and its questions changed. - Working at a SaaS company, ideally one with both a self-serve and a sales-led motion. Commerce, payments, or creator economy experience is a plus, not a requirement. - Working on a small or remote team where you were trusted to make decisions independently. Traits - Ownership and follow-through. You treat your data domains as yours. You notice problems before stakeholders do, close the loop on requests, and finish what you start. - Judgment. You match rigor to the decision at hand, know when a quick answer is enough and when a request should become a durable model, and say so clearly. - Flexibility. You're glad to step outside your primary area when another team needs help, and you balance that work against your core commitments openly. - Teach everything you know. You document as you go, pair generously, and help stakeholders understand the data well enough to use it on their own. - Work in public. You share progress, open questions, and decisions in writing where the team can see them, including what didn't work. - Creator success is our success. You remember who's on the other end. A wrong number in a pipeline review means Sales spends time on the wrong creators, and that shapes how carefully you work. - Do it with excellence. You test your work, review it carefully, and don't ship a number you can't defend. - Candor with care. You're comfortable pushing back when a request won't answer the real question, and you do it in a way that builds trust.   WHAT WON'T SET YOU UP FOR SUCCESS - Needing detailed specs or a highly structured environment before you can start. - Discomfort with ambiguity. Some of our sales and commerce definitions are still evolving, and you'll help settle them. - Needing several layers of approval to make modeling decisions within your domain. - Wanting to work only on dashboards, or only on pipelines, rather than across the transformation and BI layers. - Wanting a strictly fixed scope. Sales comes first, but you'll pick up Product or other work when the business needs it. - Wanting mostly greenfield work. Much of this role is improving sales models and dashboards that already exist. - Preferring to take tickets as written rather than partnering with stakeholders on what they need. - Being skeptical of AI's capabilities, or using AI without good judgment and accountability. - Expecting a large data team with dedicated specialists for every part of the stack.   WORKING HOURS AND LOCATION We're 100% remote with team members across the globe. We work mostly on East Coast time - so if you're based on the West Coast of the United States, Europe, or Asia, you might have a few early mornings or late evenings. We do our best to keep things reasonable, but a little time zone juggling comes with the territory.   COMPENSATION + PERKS + BENEFITS Kit has standardized salaries based on position, no matter where you live. For this role, we're hiring at our level 4 ($172,000). Level is determined based on experience and our interview process.   PERKS + BENEFITS INCLUDE: - Profit Sharing https://www.linkedin.com/feed/update/urn:li:activity:7454911054947688448/ - Kit equity - 401k with a 5% match - We cover up to $2,280 per month toward medical premiums, with dental and vision premiums fully covered. We offer Health Insurance plans through Aetna - $2,000 equipment allowance for your first two years, $1,000 budget every following two years. Company-provided laptops are issued to every Kit team member and are not included in the equipment budget - Individual learning + development budget ($3,500/year) - Creator meetup budget ($50/month) to connect with creators over coffee, lunch, or other in-person meetups - Gender affirming benefits - Childcare benefit up to $3,000 annually through JOON - Twenty (20) days of paid time off during each year of employment - Paid paid vacation: An after-tax bonus of $1,000 for taking five consecutive days of vacation where you’re fully unplugged from work - Ten (10) paid holidays a year - Two weeks of paid sick time each year, including mental health + well being days - Twelve (12) weeks paid parental leave and flexible scheduling in your child’s first year - Up to six weeks of paid bereavement leave, medical leave, and disaster after six months of employment, two weeks of each paid leave in your first six months - Winter Break Closure: Kit closes for a week at the end of December, giving everyone a collective break to enjoy the holiday season. Essential support services remain available, with teams coordinating to ensure coverage during this period - Four-week, paid sabbatical after five years with the team - Fantastic in-person or virtual retreats with the team twice a year   HOW TO APPLY We usually receive a large number of applications, and our goal is to follow up with you within two weeks. You’ll hear from us either way. Here’s what you can expect from the rest of our hiring process: 1. A phone screen with our recruiter (30 min) 2. Hiring manager interview (45 min) 3. Take-home assignment 4. Technical interview (60 min)   We’ll keep you informed through every step. To get started, complete this application, including a cover letter and answers to the questions on the next page. We read every single application, and your cover letter and responses help put your experience into context. Kit is an equal opportunity employer We value diversity in all of its forms. Research tells us that applicants who are female or non-binary, as well as applicants who are people of color, are less likely to apply for roles they do not feel 100% qualified for. If you think you meet more than 50% of our requirements but fewer than 100% of them, please apply. We’re imperfect communicators, so think of our job postings as the starting point for discussion rather than proof that you shouldn’t apply. Kit does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.

Location: United States; San Francisco; Canada; New York; Ottawa; Toronto; Montreal Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! WHY THIS ROLE? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most driven, and most curious people to help us do it. As the founding lead of Agentic Analytics, a new team in our Analytics and Data Insights organization, you'll own how Cohere gets answers from its own data: an agentic analytics system that answers business questions over governed data, shows the source, query, and freshness behind every answer, and asks for clarification or declines when the evidence is insufficient. Agentic analytics is far from a solved problem, and correctness is the hard part. A query that runs can still answer the wrong question. Agents go wrong when a business term maps to more than one table, when data goes stale, and when the right context never reaches the model. The worst failures are silent and plausible: a join that double-counts, a wrong denominator, missing data read as zero. Getting this right takes governed definitions, context an agent can use, and an evaluation bar that decides what ships. You'll build on work already in motion: an internal analytics agent in pilot on our BigQuery warehouse, which is fed by tested ingestion pipelines and modeled in dbt. In your first year, you'll take it to production for teams across Cohere, one domain at a time, and make it replicable: each new domain stands up with configuration, a fresh evaluation set, and very little new code. This is a hands-on staff engineering role reporting to our Senior Director of Data Analytics. You'll write production code and evaluation sets yourself while managing a small founding team that grows as the system proves itself. You may have held the title software engineer, AI engineer, or data scientist; what matters is that you've built a system like this and run it in production. RESPONSIBILITIES As the lead of Agentic Analytics, you will: - Own the system end to end. Set the architecture for how a business question becomes a governed query and a verifiable answer: interpreting the question, retrieving the right context, applying approved definitions and joins, enforcing the asking user's permissions, and attaching the evidence (source, query, freshness) to every answer. - Build and run it in production. Design the core services and write much of the first version yourself: agent-facing data tools (MCP or equivalent), context retrieval, agent skills for analytics, and the APIs that serve answers. Hold them to production standards for reliability, latency, cost, security, and observability. Put it where people already work: Slack, North, IDEs, and other agents. - Hold every release to the evaluation bar. Build and run the evaluation harness, and define what correct means in each domain: ground-truth question sets, including held-out cases and questions the agent should clarify or decline; result-level scoring, correct-or-decline rates, coverage, and error severity; and regression tests on every change to context, skills, or models. Nothing ships below the bar, and the call on when a domain is ready for production is yours. - Engineer the context layer. Turn metric definitions, approved joins, documentation generated from the code that builds each table, a business glossary, and worked examples into context the agent can use. Every correction becomes a reviewed definition and a regression test. - Roll it out across Cohere. Bring domains such as marketing, revenue, finance, and product onto the system one at a time, each with named owners, certified definitions, and its own evaluation set. Measure adoption, accuracy, turnaround, and correction effort against how those teams work today. - Make it replicable. Package the tools, skills, context templates, and evaluations, and document them well enough that other teams at Cohere can run the system without you. - Hire and lead the team. Bring on the team's first engineers, set the technical bar, review the work, and develop the people doing it. - Partner across Cohere. Work with our data platform team on the warehouse and semantic models, our model evaluation team on evaluation methodology, our security team on access, and each domain's owners on definitions and rollout. QUALIFICATIONS You may be a good fit, if you have: - 10+ years building and operating production analytics or software systems, including technical leadership of a team or of systems that span teams - Experience shipping LLM agents to production: tool use, MCP or similar, retrieval and context engineering, guardrails, and observability, with firm opinions on where they fail - Hands-on experience building natural-language or agentic analytics (text-to-SQL, analytics agents, question answering over a semantic layer) that real users relied on, and evidence that it was right - Depth in evaluating LLM systems: golden sets, result-level comparison, abstention metrics, error taxonomies, and regression testing in CI, plus the judgment to tell a good demo from a system you'd put in front of a CFO - Strong Python and SQL, and experience designing and running production services and APIs on a major cloud (Google Cloud is a plus) - Fluency with data: cloud warehouses (BigQuery, Snowflake, or similar), dbt, and semantic layers (MetricFlow, LookML, Cube, or similar). You think in grain, metric definitions, and approved joins, and you can tell when a number is wrong before it reaches a decision - Experience building identity-aware access for agents, where the agent acts with the asking user's permissions and every query leaves an audit trail - Experience hiring and developing engineers, with a leadership style grounded in empathy as much as in data - Genuine excitement about AI: you follow the research, have opinions, and enjoy being in the weeds - Comfort operating in ambiguity, leading through partners you don't manage, and writing design docs and eval reports that settle decisions across teams If some of the above doesn't line up perfectly with your experience, we still encourage you to apply! FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Intellias Meet your recruiter Katarzyna Sankowska katarzyna.sankowska@intellias.com https://www.linkedin.com... Vacancy details Software Engineering Python Engineering Lead Senior Lead Bulgaria, Colombia, Croatia, Poland, Portugal, Spain, Ukraine, United States Remote APPLY NOW REFER A FRIEND Intellias is looking for an Engineering Lead to join a large-scale Digital Health initiative building a FHIR-based healthcare platform that connects providers, payers, clinical systems, and external healthcare networks. This is a hands-on leadership role that combines strong engineering expertise with team leadership. You will set technical direction, grow engineers, and ensure delivery of secure, reliable, and HIPAA-compliant healthcare solutions. What project we have for you We’re helping a US digital-health platform make patients’ medical data accessible, consistent, and trustworthy. The platform brings together data from many clinical and administrative sources: lab results, diagnoses, medications, visits, claims and more. It standardizes this data into FHIR and exposes it through secure, standards-based APIs used by internal products and external partners. You’ll lead the engineering team that builds it. This is a player-coach role to start. While your number of direct reports is smaller and growing, you’ll write production code across the stack, sharing ownership of the API and public surfaces with our full-stack engineer, and you’ll stay close to the data integration work. You’ll own the platform’s technical direction, delivery, and team, and you’ll represent engineering to partners, product, and clinical advisors. What you will do Lead onshore/nearshore and offshore teams: hire and level accurately, run 1:1s and performance conversations, and develop leads into stronger managers. Grow the organization, with clear boundaries and a bench of future leaders. Write production code across the API, embeddable widgets, preview app, SDKs, and MCP server, with ownership that shifts with priorities. Step off the critical path as the team grows while staying close enough to the code to judge quality firsthand. Set the technical direction for an API-first platform, where every surface is a client of one OpenAPI-defined API. Own partner authentication, tenant scoping, per-partner configuration and branding, rate limiting, idempotency, and audit logging. Design configurable, rules-based questionnaire matching that clinical staff can change without code, and that clinical advisors review. Guide the integration of provider schedule inventory from health systems and telehealth networks through batch and real-time API feeds, with a booking path that confirms availability or fails gracefully. Own the roadmap, commitments, SLOs, and incident follow-through. Build HIPAA and minimum-necessary PHI boundaries into every surface, including what reaches an LLM through the MCP server, working with our security and compliance team. Set how the team employs AI to build, with the review and testing practices that keep the work correct and safe. What you need for this 8+ years of software engineering experience, including 4+ years managing engineering teams. Experience managing other managers or team leads, including leads of outsourced, vendor, or nearshore teams. Hands-on full-stack skills with Python (FastAPI or similar) on the backend and TypeScript and React on the frontend. You’ve shipped partner-facing APIs or embedded products to production. Experience leading data integration with external partners through both batch file feeds and APIs. Strong API design judgment across REST (OpenAPI) and GraphQL: contracts, versioning, idempotency, OAuth 2.0, tenant isolation, and rate limiting. Experience working with PII and/or PHI under HIPAA. Daily use of AI coding tools like Claude Code in your own work, and experience leading a team’s adoption of them. You keep a team moving when plans, staffing, or vendors change, and you give people a clear plan even when big questions are still open. You hold every lead, onshore or outsourced, to one consistent bar, and you make good calls quickly with the information you have. Nice to have: Experience in healthcare technology, working with PHI under HIPAA. Strong working knowledge of FHIR models, APIs, and implementation guides such as US Core or Bulk FHIR, including mapping to and from FHIR, profiling, and extensions. Experience with FHIR platforms and tools, whether commercial or open-source (e.g., HAPI, Smile, Medplum), or having built your own. Participation in the FHIR community, such as HL7 or non-HL7 working groups, Connectathons, IG contributions, or presentations at events like DevDays or HIMSS. FHIR training or certifications, such as FHIR Implementer or Advanced Developer. Domain knowledge in specialized FHIR areas such as clinical reasoning, analytics, FHIRPath, search, terminology, or AI. Experience with scheduling standards and APIs such as the IHE ITI Scheduling IG, SMART Scheduling Links, or Epic Open Scheduling. Experience building products for payers or employers. Experience building MCP servers or other LLM tool integration What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. Responsibilities Design and implement solutions for user incentives, experience improvements, and business automation in support of retention goals. Independently drive requirements analysis, technical design, development, testing, production rollout, ongoing operation, and post-launch evaluation for your modules. Develop and maintain user incentive and financial benefit modules. Strengthen rule execution, monetary calculations, disbursement, state transitions, idempotency, consistency, failure compensation, reconciliation, and auditing to ensure accuracy and traceability. Contribute to the engineering and productionization of AI applications and AI-powered user experiences, continuously improving output quality, responsiveness, system stability, and operating costs. Bring AI into real-world use cases by designing, developing, and iterating on AI Agents and agentic workflows. Integrate models, tools, and internal systems to support knowledge retrieval, troubleshooting, operational assistance, and business automation. Establish evaluation, execution observability, and safety controls for AI workflows. Improve context and state management, failure recovery, budget controls, and human intervention mechanisms. Enforce data access permissions, sensitive information protection, and boundaries on fund-related operations. Ensure that critical monetary calculations and writes are governed by deterministic rules and authorized execution paths. Help build team-wide AI-assisted engineering workflows. Develop reusable Skills, tools, context conventions, and validation mechanisms to enable effective AI use in requirements analysis, development, testing, code review, and troubleshooting, improving delivery efficiency while maintaining engineering quality. Required Qualifications A bachelor’s degree or above in Computer Science or a related field, with at least four years of backend development experience. Either Go or Java is acceptable. Strong programming fundamentals, including knowledge of the concurrency model, memory management, and performance optimization of at least one mainstream backend language. Ability to independently troubleshoot complex issues. Experience developing distributed systems and contributing to the design of core business modules or systems. Hands-on experience handling concurrency conflicts, idempotency, duplicate message consumption, cross-service consistency, timeouts, and failure recovery. Proficiency with common backend technologies, including RPC frameworks, caches, message queues, and relational databases, with an understanding of their appropriate use cases and reliability limitations. AI-assisted engineering capability — a core requirement: Proficiency in using AI coding tools for requirements decomposition, system analysis, coding, testing, and code review. Ability to validate outputs and maintain engineering quality rather than relying solely on generated code. AI application engineering capability — a core requirement: Hands-on experience developing and deploying AI/LLM capabilities in real-world scenarios. Ability to clearly explain the problem definition, personal contribution, technical trade-offs, and outcome validation. Experience must extend beyond basic tool usage or demonstration-only projects. Fund-related business experience — a mandatory requirement: Hands-on development experience with systems involving funds or monetary value, such as commission rebates, settlement, reconciliation, payments, accounting ledgers, vouchers, promotional credits, or subsidies. Experience addressing monetary precision, duplicate disbursements, failure compensation, or financial reconciliation, with the ability to explain the stages you owned and the mechanisms used to ensure correctness. Proactivity, business understanding, and cross-functional collaboration skills. Ability to translate business goals into technical problems and acceptance criteria. Commitment to testing, code review, observability, permission boundaries, and data security, with ownership of delivery and production outcomes. Preferred Qualifications AI Agent / agentic workflow development experience — a key priority: Hands-on experience designing, developing, and continuously iterating on Agent workflows involving tool calling, workflow orchestration, context and memory management, state persistence, failure recovery, or human intervention. Projects may include business products, internal tools, or actively used and maintained personal projects. Experience evaluating Agent performance and improving reliability. Ability to identify issues through evaluation datasets, failure cases, execution traces, or business metrics, and validate the impact of improvements. Experience building team-wide AI-assisted engineering workflows, such as custom Skills, Rules, context conventions, automated testing, or AI code review pipelines that have been adopted by the team. Experience independently owning complex business modules or driving cross-system projects, including proposing solutions, coordinating dependencies, and delivering outcomes. Familiarity with complex rule systems, microservices, and asynchronous task orchestration. Ability to determine when to use traditional workflows versus Agents based on cost, determinism, and error risk. Additional Advantages Experience developing retention, user incentive, lifecycle engagement, or growth platforms, including collaboration with Product and Operations to evaluate outcomes using business data and experiments. Practical experience with RAG, vector retrieval, knowledge bases, MCP, AI translation, search, or Agent orchestration frameworks, with the ability to explain technology choices and their limitations. Engineering experience at a cryptocurrency exchange or fintech company, or actively maintained and used personal projects and open-source contributions. Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building large-scale entertainment products for a global audience. Our platforms serve millions of users worldwide and rank among the top-50 most visited websites globally. For more than 10 years, we’ve been creating reliable, high-performance solutions at the intersection of product, engineering, and entertainment. We build production agentic systems that read from and write to internal resources. You will design, ship, and measure them. What you’ll do Ship end-to-end: Take agentic workflows from prototype to production, build user interfaces around them. Design agent architecture: Define tools, memory, retrieval strategies, and human-in-the-loop handoffs. Integrate systems: Expose internal tools and data via MCP servers and APIs with least-privilege access. Evaluate performance: Build trace-based evals and golden datasets to catch regressions across full agent runs. Operate in production: Implement tracing, token budgets, cost controls, and safety guardrails. Scope problems: Work with domain owners to identify where agents add value —and push back when a simpler solution is better. Requirements Proven experience shipping production LLM agents or automations. Strong Python and/or TypeScript skills (clean code, automated testing, code reviews). Deep familiarity with current frontier models: cost, latency, capabilities, and trade-offs. Hands-on experience with tool calling, MCP, and modern retrieval (agentic/hybrid search, long-context vs. vector stores). Strong system design skills covering failure modes, latency, cost, and security. A passion for upskilling others — running demos, sharing workflows, and helping teams across the company adopt AI practically. Nice to have Docker and Kubernetes / OKD (OpenShift). LLM gateways, observability tools, and eval frameworks. Experience integrating legacy or enterprise systems. Conditions We know that great talent deserves great conditions, so here’s what you can expect when joining us: EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family. EU passport. Opportunity to obtain an EU passport after 4 years of residence Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free. Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. Private medical insurance for you and your family Corporate mobile plan (unlimited in Cyprus with roaming included) Mindfulness & well-being support, including psychological assistance with 50% coverage. 50% coverage of school and kindergarten fees for your children. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals Professional growth support: language courses, conferences, training programs, and coaching. Peer recognition program: receive and share kudos for great work. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free breakfasts and lunches in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team-building, and hackathons — because great work happens in great communities.

🕹 Список обязанностей: — Развивать кредитный конвейер: статусы и переходы заявки, условия сделки, ограничения кредитных продуктов, историю и аудит действий. — Строить и поддерживать интеграции с АБС, скоринговыми системами, сервисами проверки банковских выписок и справочниками.

Location: Warszawa, Poland Workplace: hybrid Czym będziesz się zajmować na co dzień? Identyfikacja i priorytetyzacja use case’ów AI pod kątem wartości biznesowej, wykonalności technicznej i ryzyka Ocena zasadności inicjatyw wraz z analizą TCO i ROI Tworzenie i współutrzymywanie roadmapy wdrożeń AI Zarządzanie relacjami z dostawcami modeli i platform Wspieranie adopcji AI: dobre praktyki, szkolenia, rozwijanie świadomości możliwości, standardy pracy z narzędziami, także poprzez tworzenie sieci zewnętrznych ekspertów Koordynacja sieci wewnętrznych championów AI w zespołach Prowadzenie bieżącej komunikacji wewnętrznej i urealnianie zapotrzebowania, budowanie silnej relacji i zrozumienia potrzeb zespołu Współtworzenie scenariuszy testowych dla narzędzi, wraz z przejrzystymi kryteriami oceny Wypracowanie i utrzymywanie przejrzystej bazy dopuszczonych i sprawdzonych rozwiązań AI w organizacji, zarówno zewnętrznych, jak i wewnętrznych Współutrzymywanie raportów pipeline’u implementacji i operacyjnych Modele, platformy i zastosowania Rozumienie architektury LLM na poziomie koncepcyjnym Znajomość rozwiązań od głównych dostawców oraz ich implementacji, także w ekosystemie modeli open-weight Definiowanie kryteriów jakości i współtworzenie evali oraz golden datasets do oceny modeli i pipeline’ów Odpowiedzialność za treść wiedzy, z której korzystają narzędzia AI: jej dobór, aktualność i właścicieli merytorycznych Automatyzacja, integracje i wdrożenia Identyfikacja procesów do automatyzacji z wykorzystaniem AI oraz projektowanie logiki przepływów Strukturalna i logiczna znajomość narzędzi low-code/no-code i łączenia AI z systemami firmowymi przez MCP, API i webhooki; prototypowanie rozwiązań Rozumienie różnic cloud vs. on-premise: skalowanie, dostępność GPU, koszty, latency, bezpieczeństwo i rezydencja danych Formułowanie wymagań technicznych i przekładanie ich między biznesem a zespołem inżynierskim Ryzyka i zgodność Świadomość zagrożeń specyficznych dla AI Analiza ryzyk związanych z narzędziami AI zgodnie z wewnętrznymi wymaganiami bezpieczeństwa Podstawowa znajomość wymagań ochrony danych osobowych i praw autorskich w obszarze praktycznego, komercyjnego zastosowania AI Orientacja w wymogach regulacyjnych i zasadach odpowiedzialnego wykorzystywania AI Co oferujemy? Zdrowie i dobrostan wsparcie psychologiczne prywatna opieka medyczna karta Multisport Rozwój zespołowy budżet szkoleniowy wewnętrzna biblioteka Nasze biuro blisko stacji metra Stadion Narodowy i Dworca Wschodniego przyjazne dla psów wewnętrzna siłownia brak dress code'u parking dla samochodów i rowerów strefa relaksu gry wideo, planszowe i arcade Warunki pracy elastyczne godziny praca hybrydowa (3 dni w biurze, 2 dni w domu + dodatkowa pula dni zdalnych w skali roku) 20 lub 26 dni płatnego urlopu międzynarodowe środowisko pracy Wydarzenia i inne uczestnictwo w wydarzeniach game devowych program poleceń coroczne wydarzenia firmowe firmowy merch/swag

Location: Intellias Meet your recruiter Elena Dimitrova elena.dimitrova@intellias.com https://www.linkedin.com... Vacancy details Data Engineering Data Engineer Senior Bulgaria, Croatia, Poland, Portugal, Spain, Ukraine Remote APPLY NOW REFER A FRIEND We are hiring a Senior Data Engineer to join an Intellias delivery team on a large-scale enterprise data platform migration programme for a financial services client. This is a hands-on senior role. You will write production code every week, own architectural decisions on your workstream, and mentor a paired mid-level engineer. What project we have for you Our client is an independent, active global asset manager with over R3 trillion in assets under management. They are executing a firm-wide data strategy to govern, manage and engineer data as a product across more than 70 business-owned sub-domains. As part of this, they are migrating to Databricks as the foundational layer of their Enterprise Data Platform, adopting a lakehouse architecture built on open formats, declarative pipelines and Unity Catalog. What you will do Perform the end-to-end delivery of one or more priority data domains on Azure Databricks. Design and build medallion (Bronze / Silver / Gold) pipelines using Lakeflow Declarative Pipelines, Auto Loader, Structured Streaming and Delta Lake with Liquid Clustering. Register curated data products in Unity Catalog with the correct tags, masks, row filters, lineage and access policies. Implement data quality gates at the Silver-to-Gold boundary, and refine rules with domain stewards. Package and deploy work using Databricks Asset Bundles through Azure DevOps CI/CD Write automated tests and documentation Work at AI-as-Collaborator level today with a path to AI-as-Orchestrator, using Claude Code, Databricks Assistant, GitHub Copilot and MCP-connected agent tooling to accelerate the recurring parts of pipeline build, test and deploy. What you need for this 6+ years of data engineering experience, with at least the last three years on Databricks in production. Deep hands-on experience with medallion / Lakehouse architecture, Delta Lake, Unity Catalog, Lakeflow Declarative Pipelines and Databricks Asset Bundles. Strong python, PySpark and SQL, comfortable diagnosing performance issues on large workloads through Spark UI and Photon. Real production experience with streaming ingestion (Kafka Structured Streaming, Auto Loader) and CDC patterns. Experience implementing data quality at scale (Great Expectations or equivalent), plus lineage, cataloguing and access control. CI/CD on data platforms through Azure DevOps or GitHub Actions, with infrastructure as code (Terraform or equivalent). Fluent working English. Nice to have Active Databricks certifications Prior exposure to investment management platforms, asset management operations data, market data feeds from major providers CDMP DAMA certification or equivalent data governance credential. Experience applying agentic engineering tooling to production data engineering (not just personal productivity), including MCP-connected Databricks or cloud servers. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills Databricks

Location: Москва Ищем ML Engineer для разработки AI-решений на базе больших языковых моделей (LLM). Предстоит заниматься созданием AI-агентов, мультиагентных систем, RAG-решений и адаптацией LLM под прикладные задачи. Специалист будет участвовать в полном цикле разработки: подготовка данных, дообучение моделей, разработка AI-архитектуры и внедрение решений в production. Обязанности ### Твои задачи: * разработка AI-агентов и мультиагентных систем * создание и оптимизация RAG-систем * разработка и настройка промптов (Prompt Engineering) * дообучение LLM * подготовка и обработка датасетов * настройка Embeddings, Vector Search, Hybrid Search * интеграция LLM с API, базами данных и корпоративными системами * оценка качества моделей и оптимизация результатов * развертывание и сопровождение AI-сервисов. Требования ### Мы ожидаем, что у тебя есть: * опыт разработки на Python от 3 лет * опыт работы с LLM и Generative AI * опыт разработки RAG-систем * опыт Fine-Tuning LLM (SFT, LoRA/QLoRA) * опыт работы с Hugging Face Transformers, PyTorch * понимание архитектуры Transformer * опыт работы с Prompt Engineering * опыт создания AI-агентов. **Будет плюсом:** * опыт работы с локальными LLM (Qwen и др.) * опыт развертывания моделей * опыт работы с GPU-инфраструктурой * опыт работы с Vector DB (Qdrant и др.) * опыт построения MLOps-процессов * знание MCP / A2A протоколов * опыт оценки качества LLM Условия ### Работа в СберТехе - это: * гибридный формат работы * годовой бонус и ежегодный пересмотр зарплаты * статус аккредитованной ИТ-компании * расширенный ДМС с первого дня и льготное страхование для семьи * корпоративный университет Сбера, внутренняя образовательная платформа, участие в IT-конференциях * 90 дней удаленной работы из любого региона РФ * льготная ипотека в Сбере * бесплатная подписка СберПрайм, которой можно поделиться с 3 близкими.