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Location: United Kingdom Workplace: remote About Intermedia Are you looking for a company where YOUR VOICE is heard? Where can you MAKE A DIFFERENCE? Do you THRIVE in a FAST-PACED work environment? Do you wake every morning EXCITED to work with GREAT PEOPLE and create SUCCESS TOGETHER? Then Intermedia is the place for you. Intermedia has established itself as a leading provider of cloud communications and collaboration tech that allows companies to connect better. We have a strong track record of growth, profitability, and creating an environment where everyone matters. Everyone. While we are fast-paced and admittedly a bit intense, we promise that you won’t be bored. You will find Intermedia is a place where you can indulge your passion for creating and supporting great cloud technology. What’s more, we always look to promote from within and have many employees who have been with us 10, 15, and 20+ years! Culture at Intermedia is built on teamwork and transparency. We hold each other accountable and always have each other’s back! While primarily remote , this role requires occasional visits to the Bristol office or London. About the Role Intermedia is looking for a Data Scientist to join our AI Data Science team. In this role, you will develop and apply advanced machine learning, generative AI, and statistical techniques to improve the intelligence, effectiveness, and reliability of Intermedia's digital agents. You will work on challenging problems involving large language models, retrieval, agent behavior, experimentation, evaluation, and optimization to help create digital agents that can understand customer needs, access relevant knowledge, and successfully complete complex tasks. You will work closely with AI/ML engineers, software engineers, product managers, and other data scientists to take ideas from experimentation through production. You will have significant ownership of data science solutions while helping establish strong practices for measuring and continuously improving the quality of our AI-powered experiences. What You Will Be Doing Machine Learning & Agent Intelligence Develop, evaluate, and improve machine learning and generative AI solutions that power Intermedia's Digital Agent Platform. Apply large language models (LLMs), natural language processing, retrieval, and other advanced AI techniques to improve agent understanding and performance. Develop approaches that improve agent reasoning, tool selection, knowledge retrieval, context management, personalization, and task completion. Experiment with model, prompt, retrieval, and agent configuration strategies to identify approaches that deliver the best customer and business outcomes. Evaluate commercial and open-source models and recommend appropriate approaches based on quality, latency, scalability, and cost. Generative AI & RAG Design, develop, and optimize Retrieval-Augmented Generation (RAG) solutions that ground digital agents in relevant enterprise and customer information. Develop and evaluate embeddings, retrieval strategies, ranking approaches, semantic search, and other knowledge-retrieval techniques. Build and refine end-to-end pipelines that combine LLMs with retrieval systems, enterprise knowledge sources, and agent workflows. Develop approaches to improve the relevance, accuracy, and consistency of AI-generated responses. Identify and mitigate issues such as hallucinations, poor retrieval, inappropriate responses, and other failure modes in generative AI applications. Evaluation & Experimentation Develop rigorous evaluation frameworks for measuring digital agent quality, including accuracy, relevance, task completion, reliability, safety, and customer experience. Design offline and online experiments to compare models, prompts, retrieval strategies, agent configurations, and other AI approaches. Apply statistical analysis, hypothesis testing, segmentation, and other quantitative methods to evaluate AI performance and identify opportunities for improvement. Define appropriate metrics and benchmarks that connect model and agent performance to customer and business outcomes. Analyze production behavior and feedback to identify patterns, failure modes, and opportunities to continuously improve digital agents. Ensure data and model quality through comprehensive testing, validation, and performance evaluation. Data & Solution Development Gather, preprocess, analyze, and model large volumes of structured and unstructured data from multiple sources. Use Python, SQL, Spark, and other relevant technologies to build scalable analytical and machine learning solutions. Develop features, datasets, and analytical approaches that support model development, experimentation, and evaluation. Partner with data and engineering teams to build and maintain reliable pipelines for model training, evaluation, and production use. Contribute to scalable ML/AI pipelines that support experimentation, deployment, monitoring, and continuous improvement. Ensure solutions are reproducible, maintainable, and designed to operate effectively at production scale. Collaboration Partner with Product, AI/ML Engineering, Software Engineering, and other Data Science team members to translate customer and business problems into effective AI solutions. Communicate analytical findings, model performance, tradeoffs, and recommendations clearly to technical and non-technical stakeholders. Participate in technical and design reviews and help establish strong practices for AI experimentation, evaluation, and model development. Mentor and support less experienced data scientists and contribute to knowledge sharing across the team. What You Will Bring to the Role Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Machine Learning, Analytics, or a related quantitative field; Master's degree preferred. 4+ years of professional experience in data science, machine learning, applied AI, or a related analytical field. Strong experience developing and applying supervised and unsupervised machine learning models to real-world problems. Hands-on experience with generative AI, large language models, NLP, or other modern AI technologies. Strong programming skills in Python and experience with SQL and large-scale data processing technologies. Experience with modern machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies. Strong understanding of statistical analysis, experimentation, hypothesis testing, model evaluation, and performance measurement. Experience working with large volumes of structured and unstructured data. Demonstrated ability to independently frame ambiguous problems, develop analytical approaches, evaluate alternatives, and deliver actionable solutions. Experience taking machine learning or AI solutions beyond experimentation and contributing to their deployment and operation in production environments. Understanding of model quality, data quality, bias, reliability, and other considerations associated with production AI systems. Strong problem-solving and analytical skills with the ability to connect technical results to customer and business outcomes. Strong written and verbal communication skills with the ability to explain complex analytical and AI concepts to technical and non-technical audiences. Ability to collaborate effectively across Data Science, AI/ML Engineering, Software Engineering, Product, and business teams. Diversity, Inclusion, and Equal Opportunity We hire, promote, and compensate employees based on their ability to perform their job responsibilities, without regard to race, color, creed, religion, sex, gender, marital status, national origin, ancestry, age, citizenship, physical or mental disability, sexual orientation, or any other basis protected by applicable law (collectively referred to in our Code of Conduct as “Protected Classes”). We do not tolerate employment discrimination in the workplace, and we are committed to making reasonable accommodations for identified disabilities or other limitations as required by all applicable laws. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Location: Portugal Workplace: remote About Intermedia Are you looking for a company where YOUR VOICE is heard? Where can you MAKE A DIFFERENCE? Do you THRIVE in a FAST-PACED work environment? Do you wake every morning EXCITED to work with GREAT PEOPLE and create SUCCESS TOGETHER? Then Intermedia is the place for you. Intermedia has established itself as a leading provider of cloud communications and collaboration tech that allows companies to connect better. We have a strong track record of growth, profitability, and creating an environment where everyone matters. Everyone. While we are fast-paced and admittedly a bit intense, we promise that you won’t be bored. You will find Intermedia is a place where you can indulge your passion for creating and supporting great cloud technology. What’s more, we always look to promote from within and have many employees who have been with us 10, 15, and 20+ years! Culture at Intermedia is built on teamwork and transparency. We hold each other accountable and always have each other’s back! While primarily remote , this role requires occasional visits to the office in Coimbra or in Aveiro. We plan to open an office in Porto in the future. This approach gives team members the flexibility to work remotely while also coming together in the office for collaboration and teamwork. About the Role Intermedia is looking for a Data Scientist to join our AI Data Science team. In this role, you will develop and apply advanced machine learning, generative AI, and statistical techniques to improve the intelligence, effectiveness, and reliability of Intermedia's digital agents. You will work on challenging problems involving large language models, retrieval, agent behavior, experimentation, evaluation, and optimization to help create digital agents that can understand customer needs, access relevant knowledge, and successfully complete complex tasks. You will work closely with AI/ML engineers, software engineers, product managers, and other data scientists to take ideas from experimentation through production. You will have significant ownership of data science solutions while helping establish strong practices for measuring and continuously improving the quality of our AI-powered experiences. What You Will Be Doing Machine Learning & Agent Intelligence Develop, evaluate, and improve machine learning and generative AI solutions that power Intermedia's Digital Agent Platform. Apply large language models (LLMs), natural language processing, retrieval, and other advanced AI techniques to improve agent understanding and performance. Develop approaches that improve agent reasoning, tool selection, knowledge retrieval, context management, personalization, and task completion. Experiment with model, prompt, retrieval, and agent configuration strategies to identify approaches that deliver the best customer and business outcomes. Evaluate commercial and open-source models and recommend appropriate approaches based on quality, latency, scalability, and cost. Generative AI & RAG Design, develop, and optimize Retrieval-Augmented Generation (RAG) solutions that ground digital agents in relevant enterprise and customer information. Develop and evaluate embeddings, retrieval strategies, ranking approaches, semantic search, and other knowledge-retrieval techniques. Build and refine end-to-end pipelines that combine LLMs with retrieval systems, enterprise knowledge sources, and agent workflows. Develop approaches to improve the relevance, accuracy, and consistency of AI-generated responses. Identify and mitigate issues such as hallucinations, poor retrieval, inappropriate responses, and other failure modes in generative AI applications. Evaluation & Experimentation Develop rigorous evaluation frameworks for measuring digital agent quality, including accuracy, relevance, task completion, reliability, safety, and customer experience. Design offline and online experiments to compare models, prompts, retrieval strategies, agent configurations, and other AI approaches. Apply statistical analysis, hypothesis testing, segmentation, and other quantitative methods to evaluate AI performance and identify opportunities for improvement. Define appropriate metrics and benchmarks that connect model and agent performance to customer and business outcomes. Analyze production behavior and feedback to identify patterns, failure modes, and opportunities to continuously improve digital agents. Ensure data and model quality through comprehensive testing, validation, and performance evaluation. Data & Solution Development Gather, preprocess, analyze, and model large volumes of structured and unstructured data from multiple sources. Use Python, SQL, Spark, and other relevant technologies to build scalable analytical and machine learning solutions. Develop features, datasets, and analytical approaches that support model development, experimentation, and evaluation. Partner with data and engineering teams to build and maintain reliable pipelines for model training, evaluation, and production use. Contribute to scalable ML/AI pipelines that support experimentation, deployment, monitoring, and continuous improvement. Ensure solutions are reproducible, maintainable, and designed to operate effectively at production scale. Collaboration Partner with Product, AI/ML Engineering, Software Engineering, and other Data Science team members to translate customer and business problems into effective AI solutions. Communicate analytical findings, model performance, tradeoffs, and recommendations clearly to technical and non-technical stakeholders. Participate in technical and design reviews and help establish strong practices for AI experimentation, evaluation, and model development. Mentor and support less experienced data scientists and contribute to knowledge sharing across the team. What You Will Bring to the Role Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Machine Learning, Analytics, or a related quantitative field; Master's degree preferred. 4+ years of professional experience in data science, machine learning, applied AI, or a related analytical field. Strong experience developing and applying supervised and unsupervised machine learning models to real-world problems. Hands-on experience with generative AI, large language models, NLP, or other modern AI technologies. Strong programming skills in Python and experience with SQL and large-scale data processing technologies. Experience with modern machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies. Strong understanding of statistical analysis, experimentation, hypothesis testing, model evaluation, and performance measurement. Experience working with large volumes of structured and unstructured data. Demonstrated ability to independently frame ambiguous problems, develop analytical approaches, evaluate alternatives, and deliver actionable solutions. Experience taking machine learning or AI solutions beyond experimentation and contributing to their deployment and operation in production environments. Understanding of model quality, data quality, bias, reliability, and other considerations associated with production AI systems. Strong problem-solving and analytical skills with the ability to connect technical results to customer and business outcomes. Strong written and verbal communication skills with the ability to explain complex analytical and AI concepts to technical and non-technical audiences. Ability to collaborate effectively across Data Science, AI/ML Engineering, Software Engineering, Product, and business teams. Diversity, Inclusion, and Equal Opportunity We hire, promote, and compensate employees based on their ability to perform their job responsibilities, without regard to race, color, creed, religion, sex, gender, marital status, national origin, ancestry, age, citizenship, physical or mental disability, sexual orientation, or any other basis protected by applicable law (collectively referred to in our Code of Conduct as “Protected Classes”). We do not tolerate employment discrimination in the workplace, and we are committed to making reasonable accommodations for identified disabilities or other limitations as required by all applicable laws. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

– Умение анализировать бизнес-процессы, считать эффект, ROI и стоимость владения решением. Опыт запуска AI-пилотов или автоматизации от идеи до результата.

Location: Hybrid About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Location: London What you will do as a Customer Engineer The Customer Engineer (CE) is the core driver of our technical go-to-market strategy: a trusted technical advisor and primary architect of the customer journey. You will bridge the gap between technical strategy and business value—guiding enterprise clients from initial pre-sales technical validation through onboarding, deployment architecture, and full lifecycle expansion. Sitting within the GTM organization and reporting to a Customer Engineering Leader, you will not hand off your customers once an initial agreement is reached. Instead, you will operate as a quota-carrying technologist, leveraging AI-augmented workflows to eliminate administrative toil so you can focus on high-value architectural design and driving measurable business outcomes across the entire customer journey. Key Responsibilities Technical Validation: Partner closely with Account Executives to lead technical deep-dive discovery, capture business requirements, and map complex customer infrastructure - DNS, CDN, Zero Trust, Network Security, Workers - to fit-for-purpose Cloudflare architectures and bespoke solutions. . Define, scope, success criteria, and technical evaluations plans for Proof of Concepts (PoCs) and Technical Validations. Deliver tailored technical presentations, architectural diagrams, and demonstrations that show how Cloudflare solves specific performance, security, and reliability challenges. Proactively address complex technical objections, security compliance questions, and edge-case architectural requirements during the sales cycle. Take accountability for a suitable solution deployment strategy (Customer, Partner or Cloudflare Professional services) being an integral part of all proposals. Customer Adoption & Value Realization: Provide oversight to technical onboarding and implementation, but not execute the implementation, serving as the primary executive and engineering contact for the customer. Design structured migration and onboarding blueprints tailored to the customer’s environment (e.g. DNS migrations, Zero Trust rollouts, WAF tuning guidance), and act as the lead consultant for customer engineering teams, walking them step-by-step through configuration best practices.  Partner with Account Executives to own discovery, demos, onboarding, technical health, risk, and expansion strategy. Proactively monitor customer health scores and telemetry to ensure rapid time-to-value, resolve integration bottlenecks, and reduce deployment risk. Commercial Accountability & Expansion: Carry a variable quota tied directly to new business acquisition and/or ongoing account growth. Be commercially accountable for ensuring deep platform adoption, retaining revenue, and identifying strategic cross-sell and up-sell opportunities based on product usage data. Lead technical Quarterly Business Reviews (QBRs) to translate platform capabilities into return on investment for C-level executives. Trusted Advisory: Act as a trusted technical advisor throughout the entire customer lifecycle, maintaining a continuous, deep relationship with key stakeholders from initial onboarding through maturity, renewal, and expansion. Provide thought partnership on architecture, AI control layers, security posture, and deployment confidence. Identify potential deployment risks or integration bottlenecks early, and provide remediation strategies to de-risk customer outcomes. AI Orchestration & Workflow Automation: Leverage AI agents, Large Language Models (LLMs), and internal platforms to automate routine tasks such as RFP/Security Questionnaire responses, sandbox provisioning, basic telemetry monitoring, and internal/external documentation, reclaiming your time for strategic customer advisory. Education & Enablement: Partner closely with the Enablement Team to design, build, and govern technical resources. Define, document, and educate both internal teams and customers on deliverables such as Standard Operating Procedures (SOPs), architectural best practices, and technical guides to continuously raise the technical baseline across the organization. Minimum Qualifications Experience: Experience in a customer-facing technical role, such as Solutions Engineering, Customer Engineering, Professional Services,  Sales Engineering, Technical Account Management, or as a Forward Deployed Engineer (years of experience required will vary based on Associate, Senior, Staff, or Principal leveling). Architectural Mindset: Ability to white-board, design, and articulate complex enterprise network and security architectures clearly. Consultative & Advisory Skills: Excellent communication skills with the ability to translate deeply technical concepts into business outcomes for both hands-on engineers and C-level executives. Commercial Mindset: Proven track record of operating in a quota-carrying or revenue-aligned environment, with a strong understanding of SaaS metrics, business value translation, and enterprise sales cycles. Communication: Exceptional presentation and stakeholder management skills, capable of bridging the gap between deep technical implementation details and high-level C-suite business strategy. Technical Breadth: We do not expect every candidate to be an expert in every domain. Qualified candidates will demonstrate depth in at least three of the technical areas below: Internet fundamentals: Deep understanding of how the Internet works, including OSI Model layers 1–7, BGP, GRE, TCP/UDP, DNS (authoritative and recursive), HTTP(S), and SSL/TLS. Security: Expertise in the security of Internet properties, including WAF, Bot Management, Firewalls, Rate Limiting, (M)TLS, Zero Trust, and SASE concepts. Performance: Expertise in the performance of Internet properties, including speed, latency, caching, video streaming, HTTP/2, and TLS 1.3. AI Proficiency: Familiarity with prompt engineering, AI-assisted scripting and log analysis, LLM utilization, and workflow automation to augment everyday CE workflows. Coding/Scripting: Proficiency in Python, JavaScript, Bash, Lua, Go, or similar languages to write custom integration scripts, API connectors, and edge computing functions. Developer Platform Fluency: Experience designing, building, deploying or scaling applications using RESTful/GraphQL APIs, SDKs, webhooks, and developer tooling in cloud-native environments. Familiarity with infrastructure-as-code (Terraform, Pulumi), CI/CD pipelines, and observability for developer-led deployments. Strongly Preferred Qualifications (The "Good-to-Haves") Technical Enablement: Track record of creating and delivering technical enablement - workshops, code samples, documentation, or developer onboarding - that accelerates customer adoption of complex platforms. Applied AI Knowledge: Experience with LLM orchestration, Retrieval-Augmented Generation (RAG) architectures, and model-access controls. Regulatory Knowledge: Understanding of regulatory requirements such as PCI DSS, HIPAA, and SOC 2. Hyperscaler / Digital Native Background: Talent coming out of hyperscalers, digital natives, distributed systems environments, or startups is strongly valued for its deeper cloud fluency and advanced architecture depth. What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

Location: Ukraine; Moldova; Albania; Kazakhstan; Montenegro; European Union; Serbia; Georgia Workplace: Remote ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE At Ruby Labs we are looking for an AI Engineer (Strong Middle / Senior level) to own and drive the quality, reliability and evolution of our AI systems in production. This is a high-ownership role. You will be responsible for end-to-end delivery of AI features, production stability of AI systems, and data-driven experimentation using tools like Langfuse and Cloudflare AI gateway for model routing. Increasingly, this includes agentic, tool-using AI systems: defining clean tool contracts (including MCP-based tools) and orchestrating how AI interacts with internal services, search and background pipelines. The stack is TypeScript end to end: Node.js and Hono services on Cloudflare Workers with Durable Objects and Containers, PostgreSQL, OpenSearch. Models from several providers run behind an AI gateway, with prompts, traces and evaluations in Langfuse. KEY RESPONSIBILITIES AI Systems Ownership & Feature Delivery - Take ownership of major AI features and LLM workflows and deliver them to production within agreed timelines. - Own AI output quality, structure and predictability across user-facing AI interactions, with consistent structured output across different LLMs for the same request type. - Integrate and orchestrate multiple LLM providers through an AI gateway, managing model selection, fallback strategies and cost optimisation. - Design and orchestrate tool-using and agentic AI workflows: clean tool contracts (including MCP-based tools), function-calling interfaces and reliable AI-to-system integrations. - Build and maintain multi-step LLM workflows and RAG pipelines (indexing, embeddings, retrieval, re-ranking) for reasoning, context reuse and search. Prompt Engineering, Evaluation & Experimentation - Design and manage production prompt systems with dynamic prompting, context injection, and conditional logic. - Own prompt management, the release of LLM experiments and Langfuse-based evaluation pipelines: test datasets, LLM-as-a-judge, output scoring. - Run A/B tests across models and prompts, analyse the results and present the data-driven impact of AI features and experiments. - Deep-debug LLM chains using Langfuse traces: identify bottlenecks, optimise for cost, latency and context-window usage, and root-cause hallucinations and logic errors. Code Quality & Production Reliability - Write clean, scalable and maintainable TypeScript across the Node.js / Cloudflare Workers stack. - Build reliable backend logic for AI systems: request and output validation, error handling, fallback flows for malformed or low-quality model responses, and reliable tool execution. - Ensure high code quality through tests (including validation and fallback paths for AI output), code reviews and clear engineering standards. - Monitor AI system metrics, quality signals, latency and release health, and resolve production issues with a documented root cause. - Document prompt designs, model and routing choices, evaluation results and architectural decisions, so others can pick up the work. QUALIFICATIONS - 4+ years of backend/fullstack software engineering experience, with production-grade TypeScript/Node.js. - 1+ year of AI/LLM systems in production with real users, not only side projects or experiments. - Daily use of AI-centred development tools (Claude Code, Cursor or similar). - Deep hands-on experience with LLM APIs (OpenAI, Anthropic, Google Gemini or similar) in production: structured output, function calling, streaming, token and cost control. - Experience with agentic AI, multi-step orchestration, tool-based workflows (function calling / tool execution) or RAG pipelines (indexing, retrieval, re-ranking). - Experience with LLM observability and evaluation tools (Langfuse, LangSmith or similar). - Experience with AI gateways and model routing (OpenRouter, Cloudflare AI Gateway or equivalent). - Solid understanding of relational databases (PostgreSQL) and caching (Redis, KV or similar). - Exceptional ownership and personal responsibility for engineering quality and delivery. NICE TO HAVE - Evaluation frameworks (LLM-as-a-judge, RAGAS) and building test datasets. - MCP (Model Context Protocol): building MCP servers/clients or designing tool contracts for AI agents. - Edge/serverless runtimes (Cloudflare Workers) and their services: KV, Durable Objects, Queues, R2, Containers. - Search engines and vector search (OpenSearch, Elasticsearch, pgvector), embeddings. - Background workflow engines (Hatchet, Temporal, Inngest) for high-volume LLM pipelines. - Browser automation and browser agents (Playwright, CDP, browser-use). - Practical fine-tuning for domain-specific tasks or strict JSON/schema compliance. - Working Python for data science, evaluation scripts, or AI tooling. LOCATION Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours. BENEFITS Discover the perks of being part of our vibrant team! We offer: - Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance. - Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days. - Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge. - Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them. - Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0#heading=h.ndsdl4wapxtt Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth! INTERVIEW PROCESS After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps: - Recruiter Screening (40 minutes) - Technical Interview (90 minutes) - Final Interview (60 minutes) LIFE AT RUBY LABS At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day. This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen. Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success. #LI-Remote

Location: Manila, Philippines About Advantage HQ Advantage HQ is building the next generation of creator-led growth infrastructure for consumer brands. We combine creative strategy, creator partnerships, performance content, whitelisting, affiliate distribution, paid media, and proprietary technology into one integrated growth system. Our team manages more than $850 million in annual media spend and works with a network of more than 400,000 creators across Meta, TikTok, and YouTube. Through Meteoric AI, our proprietary intelligence platform, we use data and AI to improve decision-making across creative production, creator selection, customer acquisition, campaign performance, and brand growth. We work with ambitious consumer brands across health, wellness, beauty, nutrition, personal care, and lifestyle. The Opportunity We are looking for a hands-on AI Engineer to bring AI into how Advantage HQ operates, across every team and every core process. As we scale, our teams spend a large share of their time on manual work: gathering data, building reports, writing briefs, moving information between tools, and repeating the same steps across clients. We see a large opportunity to use AI to remove that work, speed up decisions, and help every team do more with the same headcount. Your mission is to design and build the AI systems, internal tools, sites, and dashboards that make our company faster, more efficient, and more data-driven. You will own this work end to end: mapping how teams work today, identifying where AI and automation can make the biggest difference, building the solution, rolling it out, and making sure people use it. This is not a research role or a prompt-writing role. We are looking for an engineer who writes production code, understands how to apply LLMs to real business processes, and knows how to build tools that people rely on every day. You will work closely with leadership and with our Growth, Creative, Media Buying, Client Services, Finance, People, and Technology teams to find the highest-value problems and solve them with AI. Success means AI is built into how Advantage HQ works: core processes are automated, teams have the tools and dashboards they need, and the business runs measurably faster and more efficiently. What You'll Own AI Strategy & Process Transformation Map current workflows across departments and identify where AI and automation can save time, reduce errors, or improve decisions. Build and maintain a prioritized roadmap of AI opportunities based on business impact and effort. Redesign processes around AI, not only add AI to existing steps, working with team leads to agree on the new way of working. Recommend which problems need custom builds and which are better solved with existing AI tools and platforms. Track and report the impact of each initiative to leadership in terms of time saved, cost, and quality. Stay current with new models, tools, and techniques, and assess which ones are ready for use across the company. AI Systems, Agents & Automation Build AI agents and multi-step workflows that automate research, briefing, reporting, analysis, and operational tasks. Develop LLM-powered applications with Claude as our primary model, using other providers where they fit better. Automate repetitive work between tools, such as data entry, status updates, client reporting, onboarding steps, and approvals. Build AI assistants that help teams draft, summarize, review, and answer questions using company knowledge. Write, test, and version prompts, tool definitions, and structured outputs as part of the codebase. Add human review steps where accuracy matters, so automation stays reliable. Internal Tools, Sites & Dashboards Design and build internal web apps, portals, and sites that give teams one place to access the tools and information they need. Build dashboards that give leadership and teams real-time visibility into performance, operations, and key business metrics. Connect dashboards to live data sources so reporting is automatic rather than built by hand. Create AI-powered features within internal tools, such as natural-language search, automated insights, and summaries. Build tools quickly using a mix of custom code and low-code platforms, choosing whichever fits the problem best. Maintain and improve internal tools based on user feedback and changing business needs. Data, Integrations & Knowledge Systems Integrate the systems we use every day, including Google Workspace, Slack, project management tools, CRM, HR systems, and advertising platforms. Build data pipelines that collect, clean, and structure data from internal and external sources. Build retrieval-augmented generation (RAG) systems over SOPs, playbooks, client information, and internal knowledge so teams can find answers instantly. Organize company knowledge so it is accurate, current, and usable by both people and AI systems. Work with team leads to define data standards and keep data clean across systems. Connect with the Technology team on Meteoric AI where internal tools and our proprietary platform overlap. Quality, Security & Reliability Build evaluation checks that measure the accuracy and usefulness of AI outputs before and after changes. Monitor AI systems and automations for errors, failures, and drift, and fix issues quickly. Ensure company and client data is handled securely, with the right access controls and data privacy practices. Set up logging and monitoring so every system can be traced and debugged. Monitor and manage the cost of AI tools, APIs, and infrastructure. Document every system clearly so it can be maintained, handed over, and improved. Adoption, Enablement & Collaboration Work closely with each team to understand their workflows, pain points, and goals before building. Roll out new tools with clear guides, demos, and training so people use them. Help teams use Claude effectively in their daily work, including setting up shared Projects, Skills, and connectors for each team. Collect feedback, track usage, and improve tools that are not getting adopted. Explain technical trade-offs and results clearly to non-technical teammates and leadership. Help build a culture where every team looks for ways to work smarter with AI. Who You Are You are an experienced engineer who uses AI to change how businesses operate, not only to build demos. You have hands-on experience building AI systems, automations, and internal tools that teams rely on, and you understand the full process, from mapping a workflow and choosing an approach to building, rolling out, and measuring the result. You know that a tool nobody uses has no value. You measure your work by hours saved, processes improved, and how many people use what you build. You are pragmatic about technology. You pick the simplest approach that solves the problem, whether that is an off-the-shelf tool, a low-code automation, a dashboard, an AI agent, or a custom application. You are also a builder. You can take an unclear problem, define the scope, ship a first version quickly, and improve it based on feedback and data. You are comfortable working with people from every department, understanding how they work, and explaining technical decisions in plain language. Most importantly, you are highly accountable, proactive, analytical, and comfortable taking ownership of the systems you build. Experience We Value 4+ years of professional software engineering experience, including 2+ years building AI, automation, or internal tooling in production. Strong proficiency in Python and TypeScript or JavaScript. Strong hands-on experience with Claude, including the Claude API, Claude Code, Projects, Skills, and connecting Claude to business tools through the Model Context Protocol (MCP). Experience with other LLM providers such as OpenAI or Google Gemini, and knowing when each model is the right fit. Experience building AI agents, tool use, function calling, and multi-step workflows. Experience with workflow automation platforms such as n8n, Make, or Zapier. Experience integrating business tools through APIs and webhooks, including Google Workspace, Slack, CRM, and project management tools. Solid SQL skills and experience with databases, data pipelines, and data warehouses. Experience leading AI adoption or process improvement inside a company is a strong plus. Excellent communication skills and the ability to work directly with non-technical stakeholders. Entrepreneurial mindset with a strong bias toward execution, ownership, and measurable results. What Success Looks Like Your performance will be measured primarily by how much AI improves the way Advantage HQ operates. Key metrics include: Processes Automated: Number of core business processes automated or redesigned with AI. Time Saved: Hours of manual work removed each month across teams. Tool Adoption: Active, regular use of AI systems, internal tools, and dashboards by each team. Delivery: Number and quality of AI systems, sites, and dashboards shipped on schedule. Reporting Coverage: Share of key business metrics available in automated, real-time dashboards. Process Speed: Reduction in turnaround time for key workflows such as reporting, briefing, and onboarding. Output Quality: Accuracy and usefulness of AI outputs, measured against defined checks. System Reliability: Uptime and error rates of AI systems and automations. Cost Efficiency: Cost of AI tools and infrastructure relative to the time and money they save. Stakeholder Satisfaction: Feedback from the teams who rely on the tools you build. Why Join Advantage HQ This is an opportunity to lead how AI is put to work inside a rapidly scaling creator-led growth business. You will have the autonomy to decide which processes to transform, choose the right tools and architectures, and see your work used every day by every team in the company. You will work alongside experienced Growth, Creative, Media Buying, Client Services, and Technology teams, with direct access to leadership and the support to make real changes to how we work. We are looking for someone who wants to make a real operational difference, grow with a fast-moving team, and take ownership of systems with company-wide impact. Compensation & Location $24,000 - $48,000 USD total annual compensation, including base salary, performance bonus, and equity. Fully remote. We have built the infrastructure for high-performance distributed teams and trust our people to do their best work from wherever they work best. Compensation will be based on experience, technical depth, and the scope of the role. If you are excited to build AI systems, internal tools, and dashboards that change how a company works, and to put AI at the center of every team and process, we would love to hear from you.

Разработка, обучение и оптимизация моделей машинного обучения для решения прикладных бизнес-задач; Разработка решений на базе LLM и VLM, включая мультимодальные системы обработки текста и изображений;

— разработка сервисов и API мультиагентной системы; — извлечение данных из чертежей и техдокументации: OCR, VLM, парсинг PDF, DWG/DXF и сканов;

Задачи: — Разработка Android-функциональности нового AI-продукта мобильного приложения. — Реализация экранов и пользовательских сценариев с использованием Kotlin и современного Android-стека. — Развитие переиспользуемых Android-компонентов, библиотек и SDK для ускорения внедрения функциональности. — Работа с чатом и ИИ-помощником: асинхронные ответы, история сообщений, загрузка документов, обработка ошибок и запасных сценариев. — Разработка UI для риск-профиля и медицинских данных, включая анкеты, карточки, графики, объяснения, доверия и согласия. — Интеграция с backend/API, авторизацией, аналитикой, фича-флагами и системами наблюдаемости. — Участие в развитии многомодульной архитектуры Android-приложения и разграничении слоев feature/platform/core. — Оптимизация CI/CD, Gradle-конфигураций и скорости сборки для улучшения поставки команды. — Учет ограничений мобильных релизов: обратная совместимость, поэтапный раскат, регрессии, поддержка разных версий Android. — Написание тестируемого кода, участие в код-ревью, декомпозиции и обсуждении API-контрактов. — Работа в кросс-функциональной команде с Product, Backend, iOS, QA, SA, Design и ML. Требования: — Уверенное владение Kotlin. — Опыт работы с Kotlin Coroutines и Flow, включая SharedFlow, StateFlow, операторы, scopes, lifecycle, отмену, структурированную конкуренцию и обработку ошибок. — Знание архитектуры Android-приложений: Clean Architecture, UDF/MVI/TEA или близких подходов, separation of concerns. — Опыт работы с Jetpack Compose и понимание взаимодействия с legacy View. — Навыки навигации, управления состоянием и работы с UI-состояниями загрузки, пустого экрана, ошибок и контента. — Опыт работы с сетевым слоем: REST, авторизация/сессия, повторы запросов, маппинг ошибок, работа в условиях отсутствия или плохой сети. — Знание локального хранения и кэширования: Room, DataStore, SharedPreferences или аналогов. — Понимание многомодульных Android-проектов, влияния модулей на время сборки, границ API, подхода `api/impl` и изоляции зависимостей. — Опыт работы с Gradle: конфигурации зависимостей, различия `implementation` и `api`, version catalogs, основы convention plugins. — Опыт работы с CI/CD для Android: сборки, проверки, тесты, артефакты, ускорение обратной связи. — Знание жизненного цикла мобильного продукта: push-уведомления, диплинки, разрешения, аналитика, crash reporting. — Навыки тестирования: unit-тесты для ViewModel/use cases/services, UI-тесты приветствуются. — Готовность к релизу: фича-флаги, обратная совместимость, поэтапный раскат, регрессионные проверки. — Умение работать в команде с Backend, ML, Product, QA, SA, iOS и Design. Будет плюсом: — Опыт работы с consumer health/medtech/wellness приложениями. — Знание UX чата/помощника, потоковых ответов, голосовых функций, работы с файлами и загрузками. — Опыт работы с графиками, визуализацией данных и UX для чувствительных данных. — Навыки наблюдаемости: Sentry, Firebase Crashlytics, AppMetrica, Grafana или аналоги. — Опыт оптимизации производительности Android: время запуска, ANR, лаги, память, оптимизация сети. — Опыт профилирования и поиска утечек памяти. — Опыт работы с модульной архитектурой, общими библиотеками, SDK и дизайн-системами. — Опыт написания Gradle-плагинов или настройки Android CI/CD с нуля. — Практический опыт ИИ-помощи в разработке с дисциплиной код-ревью. — Базовое понимание LLM, RAG и agentic-сценариев на уровне интеграции клиента с backend/ML. Условия: — Возможность работать удалённо по России или в офисе в Москве. — Медицинская программа, включающая телемедицинские консультации, очные приёмы, психологов, стоматологию, лабораторные и инструментальные диагностики. — Оплачиваемые курсы английского языка. — Корпоративный ноутбук. — Компенсация спортивного абонемента. — Оплата профильного обучения и курсов через СберУниверситет. — Поддержка участия и выступлений на профильных конференциях. — Работа в крупной Digital Health платформе с командой из 360+ IT специалистов из 40+ городов. География работы: Москва, возможна удалённая работа по России.

Задачи: — Управление проектами автоматизации на всех этапах: инициация, планирование, исполнение, контроль и закрытие; — Проведение анализа текущих процессов, построение карт процессов, выявление «точек роста» и узких мест для автоматизации; — Формирование технического задания (ТЗ), дорожных карт и планов-графиков реализации проектов; — Координация кросс-функциональных команд (в том числе с привлечением специалистов из других подразделений): разработка, аналитика, инженерия, ИТ; — Управление бюджетом, сроками, ресурсами и рисками проектов; — Взаимодействие с внутренними заказчиками (сбор и уточнение требований, презентация прогресса, согласование изменений, управление ожиданиями); — Организация пилотных проектов (PoC, MVP) и их масштабирование; — Подготовка регулярной отчетности для руководства и стейкхолдеров. Требования: — Высшее техническое образование (инженерное, ИТ или математическое); — Опыт управления проектами от 3 лет; — Понимание архитектуры и принципов построения систем автоматизации процессов; — Базовое понимание технологий ИИ/ML: принципы работы LLM, RAG-систем, компьютерного зрения, агентных решений; — Понимание жизненного цикла AI-продуктов: от гипотезы и данных до внедрения и оценки эффекта; — Владение методологиями управления и системами управления проектами; — Умение работать с данными, бизнес-аналитика и формирование ключевых показателей (метрики); — Навыки командной работы, ведения переговоров, управления рисками и сроками. Условия: — Конкурентная зарплата и премии с возможностью влиять на размер заработной платы; — Перспективы профессионального и карьерного роста; — Работа в крупной стабильной компании; — Широкие возможности для обучения и развития; — Расширенный социальный пакет: официальное трудоустройство, гарантии согласно ТК РФ; — Забота о сотрудниках: компенсация питания, система материальной поддержки, льготы для женщин с детьми, льготные условия банковского кредитования, пенсионная программа, участие в жилищной программе; — Корпоративные скидки, мероприятия, культурная жизнь, санаторно-курортное лечение, доставка на работу и с работы вахтой; — Забота о детях сотрудников: бесплатные путевки в детские лагеря, новогодние подарки, приоритетное право на трудоустройство, трудоустройство на период летних каникул, участие в профессиональных форумах.

Location: Москва Вакансия для того, кто хочет строить инновации мирового уровня и видеть реальный след от своей работы. Команда создаёт ИИ-решение для анализа реализации стратегии Сбера. Это кейс на уровне топовых мировых исследований в области сценарного моделирования комплексных экономико-социальных систем и построения предиктивных алгоритмов. Ищем в команду ребят с сильным техническим и концептуальным мышлением и жаждой создавать новое. Обязанности ### Обязанности * функциональное тестирование backend сервисов и UI и написание и поддержка тестовой документации (чек-листы, тест-кейсы, баг-репорты, инструкции) * подготовка тестовых данных для тестирования / проведения ПСИ, участие в релизах, проведение регрессионного тестирования и в проведении сценариев приемо-сдаточных испытаний (ПСИ) * участие в работе с обращениями от пользователей и анализ информации в БД и логах сервисов * построение и поддержка eval-набора (golden set) и регрессионного контроля качества при смене моделей, промптов и версий приложения * автоматизированная оценка качества генерации (LLM-as-judge, метрики типа Ragas) при релизах * тестирование RAG: качество поиска релевантного контекста, корректность источников, поведение при неполной / противоречивой информации * тестирование агентных сценариев: многошаговые цепочки, вызовы инструментов (MCP), повторные попытки, эскалация к человеку * участие в мониторинге качества в проде и настройке обратной связи от пользователей. Требования ### Требования * опыт работы на позиции AQA на Python от 1 года * понимание HTTP, кодов ответов, авторизации * опыт тестирования API (REST/JSON) для проверки интеграций и бизнес-логики, микросервисного взаимодействия * опыт тестирования запросов с помощью Postman/Insomnia/Swagger * опыт работы с форматами данных: JSON, YAML, XML, HTML * знание SQL, умение написать SQL запрос средней сложности * базовый опыт работы с системами сбора и визуализации метрик, работа с логами (Prometheus, Grafana) и понимание CI/CD и участия QA в пайплайнах доставки * понимание принципов работы LLM и их ограничений: недетерминированность вывода, галлюцинации, методы оценки качества генеративных моделей и опыт построения eval-наборов (golden set) и оценки качества LLM; желательно — LLM-as-judge, Ragas. ### Будет плюсом * понимание RAG и методов оценки качества retrieval: релевантность контекста, корректность источников * опыт тестирования агентных систем: многошаговые агенты, tool calling * опыт работы с Python для автоматизации оценки (pytest) * понимание метрик качества AI-продукта и мониторинга качества в проде * опыт работы с Kafka * опыт работы с векторными / графовыми БД (например, Qdrant). Условия ### Условия * гибридный формат работы из офиса в г. Москва * годовой бонус и ежегодный пересмотр * ДМС с первого дня + стоматологию и льготное страхование для семьи * корпоративный университет Сбера, внутреннюю образовательную платформу, участие в IT-конференциях * офис на Ленинском проспекте с зонами отдыха и спортзалом * льготную ипотеку в Сбере, корпоративную пенсионную программу, подписку СберПрайм с возможностью совместного использования на трёх близких, скидки от партнеров и сервисов группы компаний.

Задачи: — разработка бэкенда AI-функций, включая чат, стриминг ответов, retrieval и Deep Research — работа с API LLM-провайдеров (OpenAI, Anthropic, Gemini): управление параллельными вызовами, лимитами, кешированием prompt и контролем стоимости — разработка контрактов между фронтендом и бэкендом — ревью AI-сгенерированных pull request и поиск дефектов за зелёными тестами — при необходимости исправление фронтенда на React и TypeScript Требования: — минимум 3 года коммерческого опыта бэкенд-разработки, включая работу с LLM-сервисами в продакшене — опыт с Python, asyncio, FastAPI, Pydantic v2, стриминг через SSE — знание API OpenAI, Anthropic, Gemini: использование инструментов, структурированный вывод, кеширование prompt, управление лимитами — опыт работы с PostgreSQL и Redis — навыки работы с React и TypeScript на уровне самостоятельного исправления кода — английский язык на уровне B1 и выше Будет плюсом: — опыт с RAG и векторными базами данных — работа с очередями (Celery, arq) — знакомство с Langfuse или OpenTelemetry — опыт работы с Docker — опыт с evals Условия: — выход на работу на следующий день после собеседования — удалённая работа, полный рабочий день — участие в опционной программе

Location: Москва Мы создаем передовые решения в области интеллектуальной обработки неструктурированного контента бизнес-инициатив Банка и жизненного цикла AI Агентов, в том числе хранения и эволюции памяти. Наши продукты составляют сервисы от high-load до UI и располагаются в 3 сегментах сети: * RAG Platform * AI Agents SkillHub * AI Agents Memory * LLM Harness * AI Studio UI Наша платформа поддерживает и развивает более 300 инициатив, обрабатывает 100М+ запросов ежемесячно и интегрирована во все клиентские сценарии банка. Мы ищем Lead DevOps с сильным уклоном в Platform Engineering, который возглавит направление DevOps платформы: сформирует эффективные процессы, осуществит переход с ClickOps, legacy кодовой базы на тестируемый код, современные GitOps практики (в том числе перестройка CI/CD пайплайнов) для всех продуктов трайба. Вы будете отвечать за конечные метрики пользования платформой несколькими командами разработки и сопровождения (DORA и пр) и будете напрямую влиять на процессы внедрения наших продуктов, улучшая их стабильность, предсказуемость и общие трудозатраты команд на релиз. Обязанности \- руководство направлением DevOps платформы \- проектирование и реализация перехода на GitOps подход \- подбор команды, планирование целей на спринт/квартал/год \- выстраивание процессов по взаимодействую с платформой со смежными командами разработки и сопровождения \- контроль и влияние на DORA метрики. Требования • проверенный опыт в создании DevOps платформы, которой пользуются несколько команд/продуктов • инженерный подход к написанию тестируемого кода • продвинутое понимание k8s/openshift, ArgoCD, Helm • архитектурное понимание и умение планировать вид платформы на годы вперед • навыки технического ведения platform engineering направления - от сбора требований от стейкхолдеров до реализации CI/CD пайплайнов • сильный уровень Python / Java / иной язык разработки. Понимание groovy бонусом. **Будет плюсом** * желание разбираться и устранять проблемы в корне, нетерпимость к "заплаткам" и накоплению техдолга * умение обосновывать сложные технические решения и в том числе выдержка и умение говорить "нет" * опыт миграций DevOps стека работающего продукта * кросс-командная коммуникация и трансляция требований на команды разработки и сопровождения * работа с multi-tenant / segmented-network продуктами. Условия * гибридный формат работы * годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * регулярные митапы и развитое DS-community * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбер.

Location: Abu Dhabi, UAE; Hong Kong SAR; 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. 岗位概述 我们正处于 AI 重塑金融基础设施的历史节点。作为 AI Agent 架构师 ，你将成为 AI 智能体系的核心构建者——不只是编写代码，而是定义下一代金融级 Agent 如何感知市场信号、规划执行路径、记忆业务上下文与跨系统协作。你将主导打造可承载真实金融场景的 Agent 体系，覆盖交易辅助、风控研判、合规监察、用户智能服务等核心业务，让 AI 在加密金融的高速、高压、高合规环境中真正自主完成复杂任务。这里没有边界模糊的分工，有的是直接影响亿级用户体验的技术决策权，以及一支对 LLM 与 Agent 技术有极高密度认知的精英工程团队。 核心职责 Agent 体系架构设计 ：主导设计 AI 智能体架构，定义 Agent 在 Openclaw 平台上的运行模型、生命周期管理与资源隔离策略；构建支撑交易辅助、风控研判、合规监察等金融核心场景的 Agent 能力基座，确保系统在高并发、低延迟、强合规约束下稳定运行。 金融场景 Agent 工程化落地 ：将交易信号分析、风险识别、监管合规、智能客服等业务需求转化为可执行的 Agent 工作流；设计任务规划链路（ReAct / Plan-and-Execute）、异常回退机制与结果验证体系，推动 Agent 从 PoC 快速进入生产环境。 Openclaw 平台建设与演进 ：深度参与 Openclaw Agent Runtime 的架构演进与性能优化；设计插件体系、能力注册中心与多 Agent 编排机制，降低业务团队接入成本，持续提升平台的扩展性与复用率。 工具生态与内部系统集成 ：构建标准化工具调用框架，打通 Bybit 内部交易引擎、风控系统、数据平台与外部 API；设计工具权限管控、调用链追踪与错误恢复机制，集成 MCP 等标准协议，构建金融级异构工具生态。 生产质量与可观测性体系 ：主导 Agent 系统的可观测性建设，包括 Trace 追踪、Evaluation 评测、成本监控与延迟治理；建立金融场景下的 Agent 质量基线与回归测试体系，持续提升系统稳定性与可解释性。 技术前瞻与团队赋能 ：持续追踪 Agent 领域前沿进展，将研究成果转化为 AI 工程实践；制定团队 Agent 开发规范与最佳实践，通过 Code Review、技术分享与方向评审推动团队整体 AI-native 工程能力提升。 任职要求 扎实的 LLM/Agent 工程经验 ：具备 3年以上 AI 系统开发经验，其中 1年以上 大型语言模型（LLM）、RAG 或 Agent 系统的生产环境落地经验；具备 Openclaw 平台的开发与优化实战经验，熟悉其 Agent Runtime 架构、插件体系与多 Agent 编排机制，能基于 Openclaw 独立完成复杂 Agent 应用的工程化落地与性能调优。 系统架构能力 ：具备分布式系统设计能力，熟悉微服务架构、消息队列（Kafka / RabbitMQ）、异步任务调度等工程模式；能够独立完成从需求分析、架构设计到技术选型的完整决策链路。 编程能力 ：熟悉至少一门后端语言（ Golang / Java / Node.js ）；具备 REST API 设计与 Docker / Kubernetes 容器化部署能力。 LLM 核心技术理解 ：深入理解 Transformer 架构、Attention 机制、Prompt Engineering（CoT、Few-shot、Structured Output）；熟悉主流模型 API（OpenAI、Anthropic Claude、Google Gemini）及本地部署方案（Ollama、vLLM）。 工程质量意识 ：具备良好的代码设计习惯（设计模式、单元测试、CI/CD）；有构建 LLM 评测（Evaluation）体系或 Agent Tracing（LangSmith / Phoenix / Langfuse）的实战经验。 加分项 有 MCTS、A\*、强化学习（RL） 与 LLM 结合的规划/推理研究或工程经验，熟悉 SFT / RLHF 训练流程。 在 金融、 Web3 、合规 或其他高复杂度垂直领域有 Agent 系统落地经验，理解领域知识对 Agent 设计的特殊约束。 有开源贡献或在 NeurIPS / ICML / ACL / ICLR 等顶会发表过 Agent / RAG / LLM 相关论文。 具备 多模态（Multimodal） Agent 开发经验，包括图文理解、文档解析（PDF / 财报 / 研报）等非结构化数据处理能力。 熟悉 MCP （ Model Context Protocol ） 或参与过 Agent 标准协议的设计与实现。 About the Role We're at an inflection point where AI is fundamentally reshaping financial infrastructure. As an AI Agent Architect , you will be a core builder of AI's intelligent ecosystem — not just writing code, but defining how next-generation financial-grade Agents perceive market signals, plan execution paths, retain business context, and orchestrate across systems. You will lead the construction of Agent capabilities purpose-built for real financial scenarios: trading intelligence, risk assessment, compliance monitoring, and smart user services — engineered to operate autonomously in crypto finance's high-velocity, high-stakes, and high-compliance environment.This is a role with genuine technical ownership. You'll make architectural decisions that directly shape the experience of hundreds of millions of users, alongside an elite engineering team with exceptional depth in LLM and Agent technology. Key Responsibilities Agent Architecture Design : Lead the architectural design of AI's intelligent Agent layer — defining agent execution models, lifecycle management, and resource isolation strategies on the Openclaw platform. Build the foundational Agent capabilities powering core financial scenarios including trading intelligence, risk assessment, and compliance monitoring, engineered for high-concurrency, low-latency, and regulatory-grade reliability. Financial Scenario Agent Engineering : Translate complex financial use cases — trading signal analysis, risk identification, regulatory compliance, and intelligent customer service — into production-ready Agent workflows. Design task planning chains (ReAct / Plan-and-Execute), fallback and error recovery mechanisms, and result validation frameworks that accelerate the path from PoC to production. Openclaw Platform Development & Evolution : Contribute deeply to the architectural evolution and performance optimization of the Openclaw Agent Runtime. Design the plugin ecosystem, capability registry, and multi-agent orchestration mechanisms to reduce onboarding friction for product teams and improve platform extensibility and reusability. Tool Ecosystem & Internal System Integration : Build a standardized tool-calling framework connecting Bybit's internal trading engine, risk systems, data platforms, and external APIs. Design tool permission controls, call-chain tracing, and error recovery; integrate standards such as MCP to unify a financial-grade heterogeneous tool ecosystem. Production Quality & Observability : Lead the observability stack for Agent systems, including trace monitoring, evaluation pipelines, cost tracking, and latency governance. Establish quality baselines and regression testing frameworks for financial Agent scenarios, continuously improving system stability and interpretability. Technical Vision & Team Enablement : Track and internalize cutting-edge Agent research, translating advances into AI engineering practice. Define team-wide Agent development standards and best practices; drive AI-native engineering capability uplift through code reviews, technical sharing, and architectural reviews. Requirements Proven LLM / Agent Engineering Experience : 3+ years of AI systems development experience, including 1+ year of production experience with Large Language Models (LLMs), RAG systems, or Agent frameworks; hands-on development and optimization experience with Openclaw , including familiarity with its Agent Runtime architecture, plugin ecosystem, and multi-agent orchestration mechanisms. Systems Architecture Proficiency : Strong distributed systems design skills including microservices architecture, message queues (Kafka / RabbitMQ), and async task scheduling; capable of independently driving the full decision chain from requirements analysis through architecture design to technology selection. Programming Expertise : Proficiency in at least one backend language ( Golang / Java / Node.js ); solid REST API design and containerized deployment skills (Docker / Kubernetes). Deep LLM Technical Understanding : Strong grasp of Transformer architecture, Attention mechanisms, and advanced Prompt Engineering (CoT, Few-shot, Structured Output); experience with major model APIs (OpenAI, Anthropic Claude, Google Gemini) and local deployment solutions (Ollama, vLLM). Engineering Quality Standards : Strong software design fundamentals (design patterns, unit testing, CI/CD); hands-on experience building LLM evaluation frameworks or Agent tracing pipelines (LangSmith / Phoenix / Langfuse). Nice to Have Experience combining MCTS, A\*, or Reinforcement Learning (RL) with LLMs for planning and reasoning; familiarity with SFT / RLHF training pipelines. Proven Agent system deployments in high-complexity vertical domains such as Finance, Web3, or Compliance , with an understanding of domain-specific constraints on Agent design. Open-source contributions or publications in NeurIPS / ICML / ACL / ICLR on Agent, RAG, or LLM-related topics. Experience with multimodal Agent development, including vision-language understanding and unstructured document parsing (PDFs, financial reports, research papers). Familiarity with MCP (Model Context Protocol) or prior involvement in designing and implementing Agent communication standards. 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: Georgian office; Yerevan, Yerevan, Armenia About Lineate Lineate is a US-based international software development company with over two decades of experience. From Intelligent Document Processing(IDP) and Agentic RAG systems to scalable cloud architectures, we turn complex ideas into real, measurable results. We deliver AI-driven custom solutions for FinTech, HealthTech, AdTech, and beyond, empowering businesses to grow smarter, faster, and more efficiently. Our expertise falls into three main categories: Building Custom AI Solutions: Deploying high-impact, AI-enabled technology utilizing IDP, Agentic RAG. Cloud and Data Infrastructure: Optimizing business operations with our data management and cloud computing solutions. Team Augmentation: Providing specialized experts in FinTech, AdTech, and HealthTech to integrate seamlessly and accelerate project timelines. Our goal is not just to build technology, but to build the future operating model for our clients. Requirements 6+ years of professional software engineering experience. Strong hands-on experience with Node.js, TypeScript, and React.js , with a backend focus. Practical experience with Agentic Development and AI-assisted development tools. Solid experience with AWS cloud services. Strong understanding of microservices architecture , REST APIs, and distributed systems. Experience with SQL/NoSQL databases, CI/CD, and automated testing. Ability to independently design, develop, and deliver scalable software solutions. We offer Freedom to Develop - equal opportunity to learn and grow professionally Clear career and professional path, strong performance management system Social Benefits Package Equipment English lesson Gym membership All the advantages of working in an international IT company Flexible vacation time Fun and inclusive in-person and digital events Lineate is proud to be an Equal Opportunity Employer - We do not hire on the basis of race, colour, religion, creed, gender, national origin, citizenship, age, disability, veteran status, marital status, pregnancy, parental status, sex, gender expression or identity, sexual orientation, or any other basis protected by labor legislation. All employment is decided based on qualifications, merit, and business ne ed. Learn more about Lineate at our website: www.lineate.com

Location: USA Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are looking for a Senior AI Quality & Evaluation Engineer to own the independent proof that retrieval works and that permissions hold. You’ll build and run the golden question suite, negative entitlement tests, and drift alarms that serve as acceptance gates — so the engineers who built the system are not grading their own work. This is a 50% allocation role across weeks 3–10, drawn from a Quality Engineering or GRC background, reporting to the POD Lead and working day-to-day with the retrieval engineer. WHAT YOU’LL DO - Build the golden question suite from top contact drivers and needs workshops — question, expected source, expected passage, and acceptance thresholds for relevance, grounding, and citation accuracy, versioned alongside the content it tests. - Build the negative entitlement test set — queries issued under unentitled identities that must return no restricted passage, with any failure raised as a severity-one alarm. - Build freshness and retirement tests — source-modified-to-index-available lag per item against the agreed threshold, and verification that retired items disappear on the next sync. - Automate the harness to run on schedule and after every content, configuration, or model change — publishing scores to the quality dashboard with trend lines and regression alarms. - Define the QA gate content analysts apply to remediated content. - Run the suite before every pilot change in weeks 7–9 and report misses with root cause — content, chunking, ranking, or permissions — to the right owner. - Write the evaluation runbook and train client stewards and platform owners to add questions, re-run the suite, and interpret regressions. REQUIRED SKILLS & EXPERIENCE - 3+ years in software quality engineering or test automation with Python, including building test harnesses that run in CI on a schedule. - Hands-on evaluation of a search or RAG system in production — writing ground truth sets, scoring relevance and grounding, and tracking drift over time. - Experience designing security-focused negative tests — authorization, entitlement, data exposure — and reporting them at the severity a client security team expects. - Ability to work in AWS — invoking Bedrock and OpenSearch APIs, reading CloudWatch, deploying a scheduled job with infrastructure code. - Clear written reporting; the suite’s output is read by client stewards, not only engineers. PREFERRED QUALIFICATIONS - AWS Certified AI Practitioner or Machine Learning Engineer Associate. - Experience with RAG evaluation libraries and LLM-as-judge scoring with human calibration. - Contact center or knowledge management domain exposure. - Familiarity with SOC 2 or ISO 27001 evidence practices. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: Москва Дивизион Исследования и аналитика — дивизион внутри Блока «Люди и культура» Сбера, который занимается созданием AI-решений и агентных систем, а также их внедрением в HR-процессы банка. Сейчас мы ищем в команду python-разработчика на проекты по внедрению AI-агентов в HR-процессы Сбера (подбор, оценка и развитие компетенций сотрудников и т.д.). Первый этап отбора на эту вакансию — общение с AI- рекрутером. После отклика вам на почту придёт приглашение пройти первичное интервью с ГиаРекрутером. Диалог займёт примерно 10 минут. Его задача — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. ГиаРекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным! Обязанности * анализ прототипов AI-агентов от Data Scientist'ов * оптимизация инференса моделей, LLM и RAG-пайплайнов * доведение решений до production-ready кода (тесты, типизация, логирование) * интеграция агентов с корпоративными API и базами данных (PostgreSQL, OpenSearch), Kafka. Требования * опыт разработки на Python от 2 лет, умение писать чистый, тестируемый код * практический опыт доведения прототипов AI-агентов до продакшена * знакомство с агентными фреймворками и архитектурами (LangGraph, LlamaIndex и др.) * опыт разработки RAG-систем, работы с реляционными и векторными базами данных * опыт работы с параллелизмом и асинхронностью * английский язык на уровне B1 (Intermediate). Будет плюсом: * опыт работы с Kafka, Elastic/OpenSearch, FastAPI, Docker * высшее техническое или физико-математическое образование * навыки работы с генеративными AI-моделями * опыт создания AI-агентов и использования их в работе * опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов. Условия * гибридный формат работы. Кутузовский проспект 32 к.1 * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

• Разработка и поддержка веб‑приложений на Python и React. • Проектирование и внедрение AI‑функций: интеграции LLM, RAG‑пайплайны, AI‑ассистенты и поиск по базе знаний.