Вакансии

Задачи: - Проектирование и разработка продакшн-систем с использованием Python 3.12+ для AI-агентов и LLM моделей - Реализация мультиагентной архитектуры: интеграция компонент, реализация пайплайнов и кастомных оркестраторов (LangChain, LangGraph, RAG) - Разработка и поддержка API (FastAPI, Django): создание микросервисов, REST, асинхронные сервисы - Интеграция с реляционными, NoSQL и векторными базами данных (PostgreSQL, Redis, MongoDB, VectorDB: ChromaDB, QDrant) - Создание, обучение и внедрение ML-моделей (ML pipeline, Prompt Engineering, RAG, оценка качества, A/B тестирование) - Контейнеризация (Docker, Docker Compose) и деплой в Kubernetes, частичная настройка DevOps-процессов (CI/CD: Jenkins, ArgoCD) - Разработка unit-тестов, код-ревью, оптимизация производительности, обеспечение безопасности - Взаимодействие в Agile-командах, участие в планировании, менторинг Требования: - Владение Python 3.12+: глубокое знание стандартных и современных возможностей языка (asyncio, typing, dataclasses, pydantic, pytest) от 4-6 лет - Практический опыт разработки AI/ML решений с использованием LangChain, LlamaIndex, RAG, интеграция с LLM API - Опыт проектирования и сопровождения высоконагруженных REST API на FastAPI/Django (архитектура, DI, сериализация, OpenAPI) - Продвинутая работа с PostgreSQL/Redis, проектирование сложных схем, индексация, оптимизация, векторные базы данных - Навыки контейнеризации, деплой в Kubernetes - Опыт внедрения CI/CD пайплайнов, мониторинга, алертинга, организации логирования - Уверенное знание Git, опыт командной работы (Agile, Scrum) - Английский B2+ для чтения документации и коммуникаций Будет плюсом: - Fine-tuning и кастомизация LLM, prompt engineering, оценка качества - Опыт с MLOps, LLMOps и мультирегиональными архитектурами - Участие в R&D или open-source проектах, менторство, архитектурное мышление - Работа с GigaChat API Условия: - Возможность профессионального и карьерного роста в компании, возможность поучаствовать в разных проектах - Опыт работы в распределенной команде профессионалов - Уровень заработной платы обсуждается индивидуально - Формат работы: Офис/гибрид г.Москва или Санкт-Петербург.

Задачи: — участвовать в проектировании RAG-архитектуры под B2B-кейсы: помогать выбирать источники данных, настраивать ingestion, chunking, базовые стратегии retrieval (dense/hybrid) под руководством более опытных коллег; — настраивать LLM/агентов под предметную область: реализовывать промпты, подключать инструменты (tool calling), работать с контекстом и базовой памятью; — реализовывать POC/POV на данных клиента, проводить итерационные улучшения на основе метрик и обратной связи; — строить Data Ingestion пайплайны с OCR; — реализовывать evaluation-пайплайны: генерация тестовых наборов, запуск auto-eval, участие в human-eval; — считать и анализировать ключевые метрики (accuracy, coverage, latency, user success rate), готовить отчеты для команды; — участвовать в настройке мониторинга: логирование, базовые алерты, анализ неуспешных кейсов и их фиксы; — участвовать в интеграции с инфраструктурой (Kubernetes, облако), работать с метриками и логами; — участвовать в нагрузочном тестировании для оценки скорости инференса и необходимых ресурсов. Требования: — опыт работы с Python (pandas, PyTorch/TF, API LLM); — опыт работы в ML/DS/NLP от двух лет; — опыт работы с LLM/RAG; — понимание полного цикла ML-разработки; — практический опыт работы с RAG: настройка retrieval, работа с embedding-моделями, векторными БД (FAISS, Qdrant, Pinecone и др.); — понимание базовых техник улучшения качества (reranking, filtering, prompt tuning); — опыт работы с агентными фреймворками (LangChain / LangGraph / LlamaIndex / ADK и др.); — базовое понимание agentic-подходов и tool calling; — опыт prompt engineering и настройки LLM под задачи; — базовый опыт fine-tuning (или понимание подходов: LoRA, QLora, instruction tuning); — понимание оптимизации инференса (на уровне использования инструментов: vLLM, quantization и др.); — опыт работы с популярными ML фреймворками: tranformers, vllm, sglang, pytorch; — SQL, базовое понимание работы с данными и пайплайнами; — опыт деплоя сервисов (Docker, FastAPI), базовое понимание Kubernetes/облака; — навыки логирования, мониторинга и базовых A/B-экспериментов; — опыт работы с evaluation для ML/LLM (auto-метрики + участие в ручной оценке, LLM-as-Judge).

Location: New York, United States; United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. About Tavily We're building the search engine for AI agents. Our API powers agentic applications and real-time reasoning by connecting LLMs to high-quality, trustworthy web content. We work with some of the most innovative teams in AI — from startups shaping the ecosystem to enterprises deploying AI at scale. The Team Forward Deployed Engineering owns how Tavily shows up technically in the field. The team sits at the intersection of customers, Product, Engineering, Sales, Partnerships, and Customer Success. The Enterprise FDE motion focuses on Tavily’s highest-value customers and strategic enterprise opportunities — from technical discovery and solution design through proof of concept, production rollout, adoption, and expansion. The role This is a full-time, on-site role based in our New York office. As a Forward Deployed Engineer, Enterprise, you’ll work directly with Tavily’s largest and most strategic customers to design, prototype, and deploy production-grade AI systems powered by Tavily’s API. You’ll own the technical relationship across the customer lifecycle, helping enterprise teams move from early use case exploration to deployed, scalable agentic applications. You’ll be deeply hands-on: building RAG pipelines, agent workflows, evaluation loops, reference architectures, and custom integrations alongside customer teams. You’ll also serve as a critical bridge between the field and our Product and Engineering teams, translating enterprise needs into roadmap signal. Your responsibilities will include: Work directly with enterprise customers to understand their AI use cases, technical architecture, success criteria, and deployment requirements. Lead technical discovery and solution design during pre-sales and expansion conversations. Scope, build, and deliver proofs of concept that demonstrate clear business and technical value. Design and implement production-ready integrations using Tavily’s API, including RAG pipelines, agent workflows, internal tools, and industry-specific GenAI applications. Partner with customer engineering, data, product, and AI teams to move use cases from prototype to production. Monitor customer API usage patterns and recommend improvements to increase reliability, latency, coverage, and overall value. Translate recurring customer needs, blockers, and technical patterns into clear product and roadmap input. Create reusable enterprise assets, including reference architectures, integration templates, deployment guides, demo environments, and technical documentation. Represent Tavily in customer architecture reviews, executive technical conversations, implementation check-ins, and post-deployment reviews. Partner closely with Sales, Customer Success, Product, and Engineering to drive adoption, retention, and expansion across strategic accounts. We expect you to have: 5+ years of software engineering experience, ideally in a customer-facing technical role such as Forward Deployed Engineer, Solutions Architect, Solutions Engineer, Sales Engineer, or Technical Consultant. Strong hands-on engineering ability, especially with Python, APIs, backend systems, and production software development. Experience building with LLMs, Retrieval-Augmented Generation, agent architectures, context engineering, and modern AI application stacks. Experience working with enterprise customers, including technical discovery, POCs, solution design, stakeholder management, and production rollout. Strong understanding of how enterprises evaluate, deploy, secure, and scale AI systems. Ability to communicate clearly with both technical and executive stakeholders, including engineering leaders, product teams, AI teams, and technical decision-makers. High autonomy, strong ownership, and comfort operating in a fast-moving startup environment. Excellent written and verbal communication skills, with the ability to turn complex technical concepts into clear recommendations. Based in New York City, or willing to relocate. It will be an added bonus if you have: Experience working with major agent or LLM orchestration frameworks such as LangChain, LlamaIndex, LangGraph, OpenAI Agents SDK, or CrewAI. Experience with vector databases such as Pinecone, Weaviate, pgvector, Qdrant, or similar systems. Experience with enterprise AI use cases in financial services, legal, consulting, enterprise SaaS, sales, marketing, or internal knowledge management. Track record helping large customers move from POC to production. Experience building internal tools, technical playbooks, demos, or reusable customer-facing assets. Prior experience at a high-growth AI infrastructure, developer tools, or enterprise SaaS company. Compensation We offer competitive compensation packages. The actual compensation offered within the listed range will be determined based on job-related factors, including experience, skills, qualifications, and the level at which the candidate is hired, consistent with applicable law. #LI-BH3 Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $179,500 — $224,300 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Seattle, WA ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 5+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $165,000–$380,000 USD Looking for a hands-on implementation role focused on custom delivery, bespoke integrations, and scoped consulting projects? Please check out the Deployed Engineer (Professional Services) roles. COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Europe We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones. Currently, we are looking for AI Video Agent Engineer for Elva. Location: Remote Job Type: Full-Time OVERVIEW: We are building an AI-driven video production system designed as an intelligent multi-agent orchestration layer capable of transforming raw ideas and references into fully structured video content. The system operates as a black-box creative engine for different types of users: - professional video creators - casual users - creators of short narrative concepts Users provide an idea, references, or media fragments, and the system automatically orchestrates multiple AI agents responsible for analysis, scripting, editing, and production of video content. We are looking for an engineer who can design and implement multi-agent pipelines, orchestrate AI tools, and build intelligent workflows that combine video analysis, storytelling logic, and automated editing. This role sits at the intersection of AI systems architecture, creative tooling, and multimodal content generation. RESPONSIBILITIES: AI Agent Architecture Design and implement the architecture of a multi-agent video editing system including agents responsible for: - video analysis - narrative generation - editing orchestration - production and output synthesis Define system prompts, behavioral rules, and structured instructions for agents interacting within the pipeline. Pipeline Orchestration (n8n) Develop and maintain complex orchestration pipelines in n8n, including: - multi-agent workflows - tool-calling logic - dynamic routing between tools and models - context passing between agents Pipelines must be capable of selecting the most appropriate models, tools, and strategies depending on the task. Multimodal Data Processing Design robust pipelines for handling: - video materials - image assets - user text prompts - structured metadata Ensure proper data transformation and context transfer across the pipeline stages. Tool & API Integration Integrate both external and internal APIs for multimodal generation and processing, including: - image generation - video generation - speech synthesis - audio generation - video processing services Rapidly evaluate available APIs and select the best quality tools and models for each task. Model Orchestration & Optimization Tune and optimize model interactions, primarily based on Gemini models, including: - prompt engineering - structured outputs - tool-calling workflows - agent collaboration logic Optimize pipelines for quality, reliability, and execution efficiency. Future Architecture (RAG & Knowledge Systems) Design systems that support: - vector databases - retrieval-augmented generation (RAG) - memory and contextual reasoning between agents EXPECTED OUTCOMES: The pipeline system should be capable of: 1. Taking an idea + references as input 2. Analyzing the content 3. Generating a coherent narrative structure 4. Selecting appropriate visual and audio elements 5. Producing a high-quality, structured video output REQUIREMENTS: AI Systems & Agent Architecture Strong experience building multi-agent systems, including: - intent and sub-intent modeling - agent orchestration - agent communication and transport layers - summarization pipelines - context passing between agents Workflow Orchestration Hands-on experience with: - n8n - Agent tool-calling - n8n MCP Experience designing complex automation pipelines is essential. Programming Strong practical coding skills with vibe coding mindset: Primary languages: - Python - JavaScript Bonus experience: - ComfyUI custom nodes - lightweight APIs (e.g., HuggingFace Spaces or inference endpoints) Multimodal Tooling Knowledge Ability to quickly navigate API documentation and integrate tools for: - image generation - video generation - speech synthesis - audio generation - multimodal analysis You should know where and how to obtain the best generation quality for each modality. Creative Thinking - Strong sense of visual rhythm and composition - Creative intuition and storytelling awareness - Good taste in video structure and montage - Ability to evaluate AI-generated output not only by metrics, but also by creative quality and narrative coherence Video & Media Processing Preferred experience with: - FFmpeg - video processing pipelines - image processing workflows NICE TO HAVE: The following qualifications are not mandatory, but will significantly strengthen a candidate’s profile during the evaluation process: Agentic Frameworks Deep understanding of frameworks such as LangGraph and LangChain for building complex cyclic state graphs and stateful agent systems. Advanced RAG & Memory Management Experience designing long-term memory systems for agents, including mechanisms for storing and retrieving successful execution patterns or scenarios to improve future performance through experience-based retrieval. Self-Correction & Reflection Experience building agents with feedback loops such as self-reflection, self-critique, or strategy correction, enabling them to verify their own actions and adapt execution logic dynamically. Evaluation & Observability Experience with tools for monitoring, debugging, and evaluating agent chains and prompt behavior, such as LangSmith, Arize Phoenix, or Promptfoo, with the ability to identify logical failures, quality regressions, and orchestration bottlenecks. IDEAL CANDIDATE: The ideal candidate is someone who naturally operates between engineering and creative production, capable of building systems that automate complex media workflows while preserving narrative coherence and aesthetic quality. You enjoy designing systems where AI agents collaborate to produce meaningful creative outputs. What’s next? If this role sounds like a fit — we’d love to hear from you! Just send over your CV and anything else you’d like us to consider. We’ll review everything within five working days, and if your background matches what we’re looking for, we’ll get in touch to set up a call and get to know each other better.

Location: Washington DC Workplace: Remote ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE As our first Federal Partner Alliances Lead for the US, you will own the systems integrator and consulting partner ecosystem across the US Federal market. This is a high-leverage, senior individual contributor role where you will build and drive our federal partner strategy from the ground up — focused primarily on establishing deep, revenue-generating relationships with the major Federal Systems Integrators (FSIs) and a curated set of specialized boutique partners. You are an operator at heart who loves the ambiguity of a fast-growing startup. You understand how developer tools and enterprise AI stacks fit together within the unique compliance and regulatory requirements of the federal space, and you have a track record of driving sourced and influenced revenue through partner channels without needing a heavy management playbook to guide you. This role sits within our GTM organization and will work closely with our field sellers, customer engineering teams, and product leaders to embed LangChain into the delivery practices and solution portfolios of the partners who win and execute the biggest federal AI programs. WHAT YOU'LL DO - Own FSI Relationships: Build and lead LangChain's strategic partnerships with the major federal primes — including Leidos, Booz Allen Hamilton, Northrop Grumman, SAIC, Accenture Federal, and similar large-scale integrators. Drive structured engagement across their AI/ML practices, solution architects, and business development teams to embed LangChain into active and upcoming program pursuits. - Develop Boutique and Specialized Partners: Identify and activate a curated set of smaller, mission-focused federal consultancies and AI-native partners that are embedded in specific agency relationships or cleared environments where the primes don't reach. - Build Joint Go-to-Market Motions: Work with FSI partners to co-develop solution offerings, reference architectures, and proposal language that positions LangChain as the preferred agentic AI framework for federal program delivery. - Drive Pipeline Through Partners: Own the partner-sourced and partner-influenced pipeline, working hand-in-hand with LangChain's field sales team to ensure FSI relationships translate into real opportunities and closed revenue. - Support Hyperscaler Relationships Selectively: Maintain a lightweight working relationship with AWS GovCloud, Azure Government, and GCP Public Sector teams, primarily to support event sponsorships, joint visibility opportunities, and marketplace presence — without making this a primary focus of the role. - Execute Co-Marketing Motions: Partner with marketing to show up effectively at key federal industry events (AFCEA, AWS Summit DC, industry days) and develop technical content and co-branded materials that reinforce LangChain's credibility with FSI and agency audiences. - Build the Playbook: Create the operational blueprint for how LangChain scales federal partnerships — from initial relationship mapping and partner tiering to joint pipeline tracking and executive engagement cadences. WHAT YOU'LL BRING - Experience: 6+ years of experience in federal partner management, business development, or alliance roles, with a strong track record of building and monetizing relationships with major FSIs and federal primes. Direct experience working within or alongside Leidos, Booz Allen Hamilton, Northrop Grumman, SAIC, or similar organizations is a significant plus. - FSI Network: A genuine, pre-existing network within the business development, AI/ML practice, and solutions architecture communities at the major federal primes. You should be able to get meetings quickly and have credibility with the people who shape program pursuit decisions. - Technical Foundation: Enough technical fluency to speak credibly with enterprise architects and engineering leads in federal environments. You don't need to write code, but you must understand how LLMs, agentic frameworks, and developer tooling operate within federal infrastructure, including FedRAMP, IL4/IL5, and zero-trust requirements. - Startup Agility: Proven ability to navigate a high-growth environment with limited structure. You are comfortable building the playbook as you run it, executing independently with minimal supervision in the often long-cycle federal sales environment. - Operational Rigor: Strong pipeline management skills. You track partner activity with clean CRM hygiene, maintain accurate opportunity attribution, and communicate clearly and consistently to internal stakeholders. - Strong Communication & Influence: Equally comfortable writing sharp internal strategy docs as you are presenting to senior BD and practice leaders at major federal integrators. NICE TO HAVE'S - Active security clearance (Secret or higher) or existing clearance eligibility. - Prior experience at an open-source, developer tools, or infrastructure software company bringing a new technology into the federal FSI ecosystem. - Familiarity with federal procurement vehicles (GSA Schedule, OTAs, BPAs) and how primes use them to structure program delivery. - Familiarity with the modern LLM orchestration stack, federal data environments, and compliance frameworks (FedRAMP, NIST, CMMC). Annual Salary Range: $190,000 to 270,000 + Equity COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Обязанности: • разработка и сопровождение AI-агентов для автоматизации процессов оценки кредитного риска • интеграция LLM и ML-моделей в агентные пайплайны (оркестрация, tool-calling, memory, RAG) • проектирование агентных архитектур: определение инструментов, стратегий и логики принятия решений • написание технической документации: описание агентов, регламенты, схемы взаимодействия. Требования: • опыт разработки на Python от 3 лет, особенно в контексте написания бизнес-логики или скриптов автоматизации • уверенное и архитектурных паттернов • опыт работы с агентными фреймворками: LangChain, LangGraph, AutoGen, CrewAI или аналоги • понимание ML (train/inference): xgboost, catboost, lightgbm, pytorch — опыт интеграции моделей в продуктовые системы • работа с Python-библиотеками pyspark / pandas / numpy для анализа данных • опыт работы с HTTP(S), RESTful API (интеграция агентов и моделей с внешними сервисами) • опыт работы с Docker; базовые знания Kubernetes и Helm • опыт работы с Git Условия: • комфортный современный офис рядом с м. Кутузовская • график работы- гибрид • ежегодный пересмотр зарплаты, годовая премия • корпоративный спортзал и зоны отдыха • более 400 образовательных программ СберУниверситета для профессионального и карьерного развития • расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа • гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ • бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров • вознаграждение за рекомендацию друзей в команду Сбера.

ФОДЖИН занимается разработкой и дизайном цифровых продуктов для крупных клиентов (Сбер, МТС, Т‑банк, Газпром и др.). В команду требуется Python‑разработчик для развития отдела и работы над непримитивными задачами. Требования: — Коммерческая разработка на Python от 2 лет — Опыт работы с PostgreSQL — Понимание асинхронности (asyncio / aiohttp) и микросервисной архитектуры — Опыт использования фреймворков/библиотек для AI‑агентов (LangChain, LangGraph и др.) — Опыт работы с брокерами сообщений Kafka или RabbitMQ — Опыт работы с Docker, CI/CD, Kubernetes Условия: — Зарплата: от 120 000 ₽ — Можно удаленно — Полный день, трудоустройство по ТК РФ — Поддержка HR и ментора, уютные офисы в ЮФО, корпоративная жизнь, компенсации на подписки, спорт, образование и здоровье

Location: Berlin, Germany Workplace: hybrid At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Founding Backend Engineer(Go) to join one of our clients ' team in Berlin. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. Key Responsibilities: Develop and maintain backend applications using Go Design and optimize cloud-based solutions using AWS services (EC2, Lambda, S3, SQS, SNS, etc.) Design, use and manage databases, including PostgreSQL, Neo4J, Redis, and Elasticsearch Develop, manage, and optimize containerized applications using Docker Automate processes using Bash/Python scripting Optimize and maintain RESTful APIs, ensuring security and performance Work closely with frontend engineers, DevOps, and product team to deliver robust applications Monitor, debug, and improve backend performance, reliability, and scalability Implement caching, messaging queues, and event-driven architectures where needed Build whole platform from scratch 5+ years of GoLang experience Hands-on coding mentality; can build things from scratch and familiar with different architectures Hands-on experience with Docker, Kubernetes (EKS) and containerized workloads Experience designing RESTful and gRPC APIs and using frameworks like Gin Hands-on experience with messaging systems (e.g., SQS , Kafka ) Experience with CI/CD pipelines (GitHub Actions or similar) Experience operating PostgreSQL (RDS / Aurora), Neo4J(or similar) Experience with AI agents , LLM-based systems, MCP, RAG, Prompts, Embeddings, Vector, etc Experience with AI stack (AWS Bedrock, LangChain, pgvector or similar) Experience with Infrastructure as Code (Terraform) Experience with monitoring, logging, observability (Grafana, OpenTelemetry, Prometheus) Ability to troubleshoot production issues end to end Experience with Coding CoPilots (Claude Code, GitHub Copilot, AWS CodeWhisperer, Codex, etc.) Experience supporting production SaaS platforms Strong understanding of SaaS integrations and app-to-app permission flows High ownership mentality, startup mindset, and ability to move quickly Experience in startup or scale-up environments Low ego, high commitment, and a true tech startup mentality Strong problem-solving skills and ability to work in a collaborative environment Excellent English communication skills Nice-to-have requirements: Experience working with Java Ability to code in Python Experience with security architecture, identity security, or security engineering Familiarity with compliance frameworks (NIS2, DORA, ISO 27001, SOC 2) Experience with AWS in production environments Exposure to graph-based modeling (identity graph, access graph, risk graph) Familiarity with compliance frameworks (NIS2, DORA, ISO 27001, SOC 2) Understanding of OAuth/OIDC, API tokens, IdP, scopes, SSO, SCIM, roles, RBAC/ABAC, service accounts Familiarity with cloud identity and security controls (e.g. IAM, CloudTrail, Azure Active Directory / Entra ID ) Hands-on with SIEM platforms such as Splunk, Microsoft Sentinel, or IBM QRadar Experience designing permission models, identity graphs, or access control frameworks Knowledge of tokenization, Zero Trust principles , least privilege, and continuous verification Experience with Security related to AI/LLM systems, agent logic, or willingness to learn fast Familiarity with AI agent behavior , LLM security, or agent sandboxing Previous experience in cybersecurity , identity startups You are a fan of rock or metal music Excellent German communication skills Benefits: Founding Team Member Equity — ESOPs in a cybersecurity company Competitive Compensation — salary aligned with market, flexible early-stage arrangements possible Founding Team Member Status — shape the company from day one and own critical technical decisions Fresh Funding Secured — immediate runway to build, hire, and execute fast Security Contribution — contribute to security architecture across identity, AI agents, and enforcement High Autonomy — freedom to design and build without corporate overhead Work with a Technical CEO and CPTO — fast iteration, strong alignment, clear direction Cutting-Edge Domain — identity security, SaaS-to-SaaS access, AI agent governance Massive Learning Curve — quickly gain depth in cybersecurity, identity, and AI systems Fast Career Path — opportunity evolve into leadership as we scale the engineering team Berlin Location — top-tier tech environment with strong cybersecurity and AI ecosystems Direct Impact — your architecture and code become the foundation of the entire platform Best Equipment and Tools - High quality equipment and modern tools to help you do your best work from day one Team Offsites - Regular team offsites designed to build strong connections, alignment, and shared momentum

Location: Strava SF Workplace: Hybrid ABOUT STRAVA Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. We are looking for a Staff AI Engineer to join the GenAI + Discovery Platform team at Strava, a team at the core of Strava's AI strategy, responsible for building the shared tooling that enables product teams to ship high value GenAI-powered features at scale. This role sits at the intersection of AI engineering, platform engineering, and server engineering. You will own the systems that make it easy and reliable for all of our product teams to build user facing features on top LLMs at Strava, from shared context, tool management, agent loops, orchestration, data access, search and retrieval to evaluation and ROI frameworks. This is a high-leverage technical role: you're not just building infrastructure, you're building the core understanding of athletes that enable consistent athlete experiences, insight across product surfaces. You'll work closely with product engineers, product managers and data teams to translate cutting-edge AI capabilities into production-ready platforms that facilitate development of AI features that provide value to our athletes. We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco office — three days per week. WHAT YOU'LL DO: - Build for a Well Loved Consumer Product: Work at the intersection of AI and fitness to launch and optimize product experiences that will be used by tens of millions of active people worldwide. - Build the GenAI + Discovery Platform: Set the vision, Design and the shared genAI platform: LLM, and workflow orchestration, prompt management systems, RAG pipelines, search and retrieval services (vector, hybrid and structured search), and evaluation tooling - Enable Teams to Ship AI Features Faster: Build self-serve interfaces and golden paths so that product and CUJ engineering teams can build GenAI-powered features without deep AI expertise. - Own End-to-End AI Capability Delivery: Drive projects from architecture and interface design through production deployment and monitoring, ensuring correctness, latency, reliability, and cost-efficiency of the AI capabilities your platform serves. - Collaborate Across Engineering, and Product: Work closely with engineers and PMs across different verticals to enable the new features and build the genAI roadmap. inform product teams on how to consume and leverage AI capabilities effectively. - Build from a Rich Dataset: Explore and use Strava's extensive unique fitness and geo datasets from millions of users to inform how AI capabilities can extract actionable insights, improve product decisions, and power novel athlete experiences. YOU WILL BE SUCCESSFUL HERE BY: - Treating AI Platform as a Product: Bringing engineering rigor — versioning, contracts, SLAs, monitoring, and deprecation paths — to AI capabilities and LLM integrations that product teams depend on. You don't ship a prototype; you ship a platform. - Leading as an Owner: Taking end-to-end accountability for the reliability and impact of the systems you build, including their correctness in production, their adoption by downstream teams, and the business outcomes they enable. - Building for Leverage: Designing platforms and tooling that multiply the output of the broader team, reducing the AI infrastructure expertise required for CUJ teams to ship GenAI-powered features. - Collaborating Across Disciplines: Working fluidly with ML engineers, data engineers, data scientists, and product managers to align on model selection, evaluation standards, prompt strategies, and consumption patterns. - Raising the Standard: Helping establish best practices for GenAI system development, responsible AI patterns, and operational health, and mentoring teammates at all levels to do the same. - Being passionate about the work you are doing and contributing positively to Strava's inclusive and collaborative team culture and values. WHAT YOU'LL BRING TO THE TEAM: - 5+ years of experience building and operating complex, production AI or backend systems at scale, with a track record of decomposing large technical problems into well-scoped execution across teams. - Demonstrated experience building AI platform tooling or developer-facing infrastructure ideally for LLM or ML systems with a strong instinct for API design, versioning, and self-serve patterns. - Hands-on experience building with large language models in production: agentic workflows, prompt and context engineering, RAG architectures, embedding pipelines, fine-tuning workflows, or LLM evaluation frameworks and tools like Langchain . - Proficiency in search systems (Elasticsearch/OpenSearch, Vector Search, etc) - Proficiency in backend service development on cloud environments (AWS preferred), using Python, Go. Solid understanding of distributed systems and containerized infrastructure (Kubernetes, Docker). - Strong technical leadership: ability to lead multi-team projects, define technical direction, and grow engineers at multiple levels. - Deep curiosity about the evolving GenAI landscape: model capabilities, agent frameworks, multimodal systems: and strong judgment on where and how to apply them to real product problems. - Strong communication and collaboration skills, with the ability to align cross-functional partners around technical direction and build organizational trust in the platforms your team ships. For information on benefits, please click here https://docs.google.com/document/d/e/2PACX-1vTkFMPz3eCjd0FgQ28VWnK4d2BEnzGyaSFGwATR-dQdBb9HxZgay6kboqnT0-V-qaBDzSvYIzI76vT5/pub. WHY JOIN US? Movement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals. Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact. When you join Strava, you’re not just joining a company—you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together. Strava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together. Strava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. California Consumer Protection Act Applicant Notice https://docs.google.com/document/d/e/2PACX-1vSc8y6On4NlP5s12hf4kmWe_pvenVyQ78TbtVaz_clROhj9ADQ6kY4YScglBIuY2joKFKalOReX7vP_/pub

Location: Montenegro; Slovenia; Slovakia; Moldova; Romania; Poland The position is open for a global, publicly traded AdTech market leader. The company's platforms handle over 1 trillion requests per day, operating within a highly optimized real-time cloud architecture across dozens of servers and processing terabytes of data daily. The engineering team focuses on intense performance optimization, low-latency infrastructure, asynchronous data streaming, and cutting-edge GenAI research and development. Salary: upto $5,000 USD / month. Format: Full-time. Hybrid (Budva, Montenegro) or 100% Remote globally Contract Type: B2B Contract Responsibilities Design, scale, and maintain real-time advertising bidding systems (DSPs, RTB Exchanges, and SSP platforms). Optimize backend services using Java (Spring Boot / WebFlux) and Go (Golang) to meet strict low-latency SLA/SLO targets. Build and manage data-intensive architectures utilizing high-load storage solutions (Aerospike, ClickHouse) and event-driven messaging (Apache Kafka). Participate in R&D initiatives involving GenAI, integrating Agentic AI frameworks (LangChain, LangGraph, N8N) for workflow automation and predictive analytics. Take full ownership of features end-to-end, contributing to the frontend layer (React / TypeScript) for internal tools and dashboards when required. Requirements 5+ years of commercial software development experience with Java as the primary language. Deep knowledge of the Spring ecosystem (Boot, Data, MVC, Security, Cloud) and strong practical experience with reactive/asynchronous programming (Spring WebFlux / Project Reactor). Solid understanding of distributed systems, concurrency, and performance tuning at the JVM level. Strong verbal English skills at B2 level or higher, with the ability to explain architectural decisions and collaborate directly with a global engineering team during voice calls. Location outside of the Russian Federation due to contractual and payment restrictions. Candidates from Belarus are eligible only if they possess an active legal entity/IP in Georgia or Europe for international payments. Commercial programming experience or strong familiarity with Go (Golang). Hands-on experience with high-load and Big Data tools including Apache Kafka, ClickHouse, and Aerospike. Real-world experience or deep interest in LLMs and AI orchestration tools such as LangChain, LangGraph, or N8N. Familiarity with frontend development using ReactJS and TypeScript. Benefits Opportunity to work on production infrastructure handling 1 trillion + daily requests. Work within a team of senior engineers with direct impact on the platform's architecture. Choice between a fully remote schedule or a hybrid format from the office in Budva, Montenegro. Stable monthly payments in USD via international B2B contracts.

Location: Москва Команда занимается разработкой Disrupt-решений в сфере Безопасности Сбера Цель команды – разработка инновационных решений, проверка гипотез, посредством подготовки MVP и PoC планируемых продуктов, поддержка продуктовых команд в части оперативной разработки. Обязанности * разработка ML-алгоритмов * разработка ML-моделей * поддержка существующих AI-решений * разработка AI-Агентов * проработка AI-архитектуры внедрения решений в целевой процесс * генерация идей. Требования * высшее образование * коммерческий опыт работы разработки\\в сфере ИИ не менее 2 лет * опыт самостоятельного лидирования * готовность работы в условиях многозадачности и сжатых сроков, интенсивному обучению и повышению квалификацию * опыт работы со следующим стеком: Python, numpy, pandas, scipy, scikit-learn, XGBoost, PyTorch, OpenAI, LangChain, LangGraph, Chroma, prompt engineering, FastAPI, REST/gRPC, React, Docker, Kubernetes, GitLab. Будет плюсом: * навыки работы с генеративными AI-моделями * опыт создания AI-агентов и использования их в работе будет преимуществом * опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов. Условия * офисный формат работы, г.Москва * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * 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.

Location: Manila, Philippines Role Overview We are looking for a creative, hands-on Python / AI Solutions Full-Stack Developer to help design, build, and deploy AI-powered solutions for customers. This person will work across the full delivery lifecycle: understanding customer needs, designing technical approaches, building Python services and full-stack applications, integrating with third-party systems, and delivering reliable solutions that create measurable business value. The ideal candidate is comfortable moving quickly in a small team, thinking creatively through ambiguous problems, and connecting AI capabilities with real-world systems through APIs, MCP, data workflows, and modern application development. Key Responsibilities Design, develop, and deploy Python-based AI applications, automation workflows, and customer-specific software solutions. Build full-stack applications, including backend services, frontend interfaces, databases, authentication flows, and deployment pipelines. Create, consume, and maintain APIs, including REST, GraphQL, webhooks, SDK-based integrations, and enterprise authentication patterns such as OAuth. Develop and integrate Model Context Protocol (MCP) servers, tools, resources, and client workflows that connect AI systems with external applications and data sources. Translate customer requirements into practical technical designs, prototypes, proofs of concept, and production-ready implementations. Integrate AI solutions with customer systems such as CRMs, ERPs, ticketing platforms, data warehouses, collaboration tools, and custom internal applications. Work with LLMs, agentic workflows, retrieval-augmented generation, structured outputs, prompt orchestration, and evaluation approaches where appropriate. Collaborate closely with product, engineering, customer success, and leadership in a small-team environment where ownership and flexibility matter. Write clean, maintainable, well-tested code and contribute to reusable components, integration patterns, and internal technical standards. Participate in customer demos, technical discovery conversations, solution reviews, and post-deployment support as needed. Required Qualifications Strong professional experience with Python and modern backend frameworks such as FastAPI, Flask, or Django. Full-stack development experience, including JavaScript or TypeScript and a modern frontend framework such as React, Next.js, Vue, or similar. Proficiency designing and integrating APIs, including authentication, authorization, pagination, rate limits, error handling, and observability. Hands-on experience with MCP or comparable tool/plugin protocols used to connect AI assistants, agents, and applications to external systems. Experience building AI-enabled applications using LLM APIs, orchestration frameworks, vector databases, RAG patterns, or agent-based workflows. Solid understanding of databases, including SQL and at least one NoSQL or search/vector-oriented data store. Experience with Git, Docker, automated testing, CI/CD concepts, and deploying applications to cloud or cloud-adjacent environments. Ability to break down ambiguous customer problems and propose creative, practical technical solutions. Strong communication skills and comfort explaining technical tradeoffs to both technical and non-technical stakeholders. Preferred Qualifications Experience with cloud platforms such as AWS, Azure, Digital Ocean, or Google Cloud, especially serverless, containerized, or managed AI services. Experience with AI platforms and tooling such as OpenAI, Azure OpenAI, Anthropic, LangChain, LlamaIndex, semantic search, embeddings, or evaluation frameworks. Background integrating with common business platforms such as Salesforce, HubSpot, ServiceNow, Jira, Confluence, Slack, Microsoft 365, Google Workspace, or custom enterprise systems. Experience with data engineering, ETL/ELT, workflow automation, event-driven systems, or queue-based architectures. Familiarity with security, privacy, and governance considerations for customer-facing AI solutions. Consulting, agency, startup, or customer-facing software delivery experience. What Makes Someone Successful in This Role Creative problem-solver who can move from idea to prototype to production without needing a large team around them. Systems thinker who understands how APIs, data, user experience, and AI capabilities fit together. Comfortable with ambiguity, changing requirements, and fast iteration based on customer feedback. Pragmatic builder who balances innovation with reliability, maintainability, security, and cost. Collaborative teammate who communicates openly, shares context, and helps raise the technical bar for the team. Representative Technology Stack Python, FastAPI/Flask/Django, JavaScript/TypeScript, React/Next.js, REST/GraphQL APIs, MCP, Docker, Git, SQL, NoSQL, vector databases, LLM APIs, cloud services, CI/CD, and modern integration tooling. Working Style This is a hands-on role in a small team. The right person will be expected to contribute across architecture, coding, integration, troubleshooting, customer communication, and delivery. They should enjoy building useful AI solutions in the real world, where creativity, technical judgment, and follow-through matter as much as raw coding ability. Your partner for AI, consulting, software development, and nearshore staffing.

Location: United Kingdom; Canada; United States About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary We are looking for a skilled AI Engineer with at least 2 years of hands-on experience in developing, deploying, and optimizing AI and machine learning solutions. You will work closely with product, engineering, and data teams to design intelligent systems, integrate AI models into production environments, and contribute to cutting-edge AI initiatives. This is an exciting opportunity for someone passionate about machine learning, generative AI, LLMs, automation, and scalable AI infrastructure in a fully remote environment. Key Responsibilities Design, build, and deploy AI/ML models for real-world applications. Develop and optimize AI-powered features using modern frameworks and APIs. Work with Large Language Models (LLMs) such as GPT, Claude, or open-source alternatives. Build AI pipelines for data processing, training, inference, and monitoring. Collaborate with cross-functional teams to translate business needs into AI solutions. Integrate AI services into web applications, SaaS platforms, and internal tools. Fine-tune and evaluate machine learning models for performance and scalability. Maintain documentation and ensure AI systems follow security and compliance best practices. Stay updated with the latest advancements in AI, machine learning, and automation technologies. Requirements 2+ years of experience as an AI Engineer, Machine Learning Engineer, or similar role. Strong experience with Python and AI/ML libraries such as TensorFlow, PyTorch, Scikit-learn, or LangChain. Experience working with LLMs, generative AI, prompt engineering, or AI agents . Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG). Experience deploying models using cloud platforms like AWS, Azure, or Google Cloud. Understanding of APIs, microservices, and backend development. Experience with Docker, Git, and CI/CD workflows. Strong analytical and problem-solving skills. Excellent communication skills and ability to work remotely with global teams. Bachelor’s degree in Computer Science, AI, Data Science, or related field preferred. Experience with AI automation tools and agent frameworks. Knowledge of MLOps and model monitoring tools. Familiarity with NLP, computer vision, or recommendation systems. Experience building AI SaaS products or chatbots. Exposure to FastAPI, Node.js, or React-based applications. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: North Macedonia; Georgia; Serbia; Croatia; Slovenia; Bosnia and Herzegovina About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary As an AI Engineer, you will be responsible for developing and optimizing AI systems, integrating machine learning models into production environments, and building scalable AI-driven applications. You will contribute to everything from model experimentation to deployment and performance optimization. Key Responsibilities Design, build, and deploy AI and machine learning solutions for real-world business applications. Develop and maintain applications using Large Language Models (LLMs) such as GPT-based systems. Build AI-powered automations, copilots, chatbots, and workflow systems. Fine-tune, evaluate, and optimize machine learning models for performance and scalability. Integrate AI systems with APIs, databases, CRMs, and third-party platforms. Collaborate with product and engineering teams to translate business requirements into AI-driven solutions. Implement prompt engineering strategies and retrieval-augmented generation (RAG) systems. Monitor model performance, reliability, and cost efficiency in production environments. Maintain documentation, testing procedures, and deployment workflows. Stay updated on the latest AI trends, frameworks, and emerging technologies. Requirements 3+ years of experience in AI Engineering, Machine Learning, or Software Engineering. Strong experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or Hugging Face. Experience working with LLMs, OpenAI APIs, Anthropic, Gemini, or similar AI platforms. Familiarity with vector databases, embeddings, and RAG architectures. Experience deploying AI applications using cloud platforms such as AWS, GCP, or Azure. Strong understanding of APIs, backend systems, and scalable application architecture. Experience with Docker, Git, CI/CD pipelines, and modern development practices. Excellent problem-solving and analytical thinking skills. Strong communication skills with the ability to work in remote, cross-functional teams. Bonus: Experience building AI agents, automation systems, or voice AI applications. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: South Africa; Pakistan; Philippines; United States; United Kingdom; Canada About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary We are looking for a highly skilled AI Engineer to design, build, and deploy AI-driven applications and machine learning solutions. You’ll work closely with product, engineering, and data teams to create intelligent systems that improve automation, customer engagement, and operational efficiency. This role is ideal for someone passionate about artificial intelligence, large language models (LLMs), machine learning infrastructure, and production-grade AI systems. Key Responsibilities Design, develop, and deploy AI and machine learning models for real-world applications. Build and optimize AI-powered tools using technologies such as OpenAI, Claude, Gemini, or open-source LLMs. Develop scalable APIs and backend services for AI applications. Fine-tune machine learning models and improve model performance. Work with structured and unstructured datasets for training and inference. Implement prompt engineering strategies and retrieval-augmented generation (RAG) pipelines. Integrate AI solutions into web platforms, CRMs, and business systems. Monitor AI model performance, reliability, and scalability in production. Collaborate with cross-functional teams to define AI product requirements and technical roadmaps. Stay updated on emerging AI technologies, frameworks, and best practices. Requirements 3+ years of experience in AI engineering, machine learning, or software engineering. Strong experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or Hugging Face. Experience working with LLMs, generative AI tools, and prompt engineering. Familiarity with vector databases, embeddings, and RAG architectures. Knowledge of cloud platforms such as AWS, GCP, or Azure. Experience building REST APIs and scalable backend systems. Understanding of MLOps, model deployment, and monitoring workflows. Strong problem-solving and analytical thinking skills. Excellent communication and collaboration abilities. Experience working in remote or distributed teams is a plus. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: Mexico; Colombia; Brazil; Chile; Argentina; Costa Rica About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary We are looking for a highly skilled AI Engineer to design, develop, and deploy scalable AI and machine learning solutions. You’ll work closely with product, engineering, and leadership teams to build intelligent systems that power automation, analytics, conversational AI, and predictive capabilities. This role is ideal for someone passionate about artificial intelligence, large language models (LLMs), machine learning infrastructure, and solving real-world business challenges with cutting-edge technology. Key Responsibilities Design, develop, and deploy AI/ML models for production environments. Build and optimize AI-powered applications using large language models (LLMs) and generative AI tools. Develop intelligent automation workflows, chatbots, recommendation systems, and predictive analytics solutions. Fine-tune, evaluate, and improve machine learning models for performance and scalability. Collaborate with software engineers and product teams to integrate AI features into existing platforms. Work with structured and unstructured datasets for training and inference pipelines. Implement prompt engineering strategies and retrieval-augmented generation (RAG) systems. Monitor AI systems, troubleshoot issues, and continuously improve model accuracy and efficiency. Stay updated with the latest advancements in AI, machine learning, and automation technologies. Maintain documentation for AI models, systems, and workflows. Requirements 3+ years of experience in AI engineering, machine learning, or related software engineering roles. Strong experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or LangChain. Hands-on experience working with OpenAI APIs, LLMs, generative AI, or NLP systems. Experience deploying machine learning models into production environments. Familiarity with vector databases, embeddings, and RAG architectures. Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. Knowledge of Docker, Kubernetes, APIs, and CI/CD pipelines is a plus. Strong understanding of data structures, algorithms, and software engineering best practices. Excellent problem-solving and analytical skills. Strong communication skills and ability to work in a remote, collaborative environment. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: Mexico; Colombia; South Africa; Argentina; Pakistan About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and EdTech. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor About the Company Our client is a high-ticket coaching, consulting, and implementation company working with founders and CEOs of digital marketing agencies scaling toward seven and eight figures. The business provides strategic consulting while also building acquisition systems directly for clients, including funnels, paid media infrastructure, sales systems, automation, and operational workflows. Job Summary We are hiring a Senior GoHighLevel Specialist / Technical Operations Consultant to own technical builds across client launches and internal systems. This is a hands-on role for someone with deep GoHighLevel expertise, strong automation and integration skills, and real experience building AI-powered workflows. You will build pipelines, funnels, automations, AI agents, attribution systems, and integration layers across GoHighLevel and third-party tools. This role is ideal for someone who can find problems, design clean solutions, build independently, and document everything to a high standard. Key Responsibilities Build and manage GoHighLevel accounts, pipelines, funnels, campaigns, workflows, and automations. Create workflow automations using Zapier, Make, direct webhooks, and API integrations. Build and integrate AI agents using tools such as Cassidy, Custom GPTs, OpenAI, Anthropic, n8n, LangChain, or similar platforms. Connect GoHighLevel with tools such as Stripe, Slack, Calendly, Fathom, ClickUp, and other business systems. Design clean attribution systems from ad click to booked call to closed deal. Troubleshoot technical issues across client accounts and internal systems. Identify workflow inefficiencies and proactively suggest better technical solutions. Document every build clearly through SOPs, Looms, process notes, and technical documentation. Collaborate with media buyers, account managers, technical operators, and leadership teams. Requirements 3+ years of hands-on GoHighLevel experience, including pipelines, funnels, campaigns, and automations. 3+ years of media buying or technical media operations experience. Strong experience with Zapier, Make, webhooks, APIs, and custom integrations. Experience with Meta Pixel, Conversions API, tracking, and lead-generation attribution. Direct experience building AI agents using Cassidy, Custom GPTs, OpenAI, Anthropic, n8n, LangChain, or comparable tools. Experience working with B2B digital marketing agencies or agency-side clients. Ability to read API documentation and solve technical problems independently. Coding or scripting ability in JavaScript, Python, or TypeScript is strongly preferred. Familiarity with ClickUp and Slack. Excellent written and spoken English for internal and client-facing communication. Strong SOP documentation skills. Benefits 💻 Fully Remote: Work from anywhere with international teams 🚀 Career Growth: Join companies in SaaS, MarTech, and B2B services 🤝 Peer Community: Connect with high-performing sales professionals in our network 🧭 Ongoing Support: Receive guidance from Huzzle before and after placement 💰 Tailored Compensation: Salaries vary by client and candidate preference — we’ll match you with options that fit your goals