Jobs ML / AI

We are looking for a Full Stack Engineer to join enterprise AI projects focused on intelligent automation, AI integrations, and modern internal platforms.
You’ll work on scalable web applications powered by Python, React, cloud technologies, and LLM-based features.

Requirements

• Strong experience with Python
• Experience with FastAPI or similar backend frameworks
• Commercial experience with React.js
• Experience building REST APIs and full stack applications
• Familiarity with cloud platforms (preferably Azure)
• Understanding of scalable architectures and software engineering best practices

Nice to Have

• Experience with AI/LLM integrations
• Familiarity with LangChain, LangGraph, or AI agent frameworks
• Experience with Azure OpenAI or similar AI services
• TypeScript, Docker, CI/CD experience
• Experience with async processing, queues, or event-driven systems

Responsibilities

• Develop and maintain full stack applications
• Build backend services and frontend interfaces
• Integrate AI capabilities into enterprise products
• Collaborate with engineering and product teams
• Contribute to architecture, deployment, and performance improvements

About the Client:

Our client is a leading global healthcare organization, driving innovation in pharmaceuticals, biotechnology, and patient-centric solutions.

We design and deliver advanced data, analytics, and AI-enabled solutions that help global organizations turn complex data into intuitive digital tools, enabling teams to make informed decisions in their daily operations and long-term strategy. Our projects span modern operational applications, interactive dashboards, and advanced analytics platforms designed to deliver actionable insights across multiple business domains.

About the Role:

We are looking for a Junior AI/GenAI Engineer to support and evolve AI-driven capabilities within the Palantir Foundry and AIP ecosystem.

In this role, you will contribute to the transformation of a data platform support function into a proactive, AI-enabled engineering ecosystem, leveraging GenAI, semantic models, and automation to improve data reliability, operational efficiency, and self-service capabilities.

You will work at the intersection of AI, data engineering, and platform operations, helping integrate AI into real production workflows while enabling teams to adopt modern AI-driven approaches.

Key Responsibilities:

• Develop and support AI and GenAI-driven solutions within enterprise data platform
• Apply LLM-based techniques such as prompt engineering, embeddings, and retrieval-augmented generation (RAG) for practical use cases
• Build and integrate AI capabilities into data workflows, pipelines, and backend systems (including Foundry environments)
• Collaborate with data engineers to understand data sources, ensure data quality, and prepare data for AI-enabled workflows
• Integrate AI solutions into Foundry workflows and Ontology-based data models to enable insights and business applications
• Support deployment and operational stability of AI-enabled solutions in production environments
• Assist in troubleshooting and resolving issues in AI-powered workflows and applications
• Work with stakeholders to translate business needs into AI-enabled technical solutions

Required Skills & Experience:

• 2+ years of experience in AI, ML engineering, data engineering, or related technical roles
• Strong Python programming skills
• Hands-on experience in Generative AI / LLM-based solutions (e.g. prompt engineering, embeddings, APIs, NLP use cases)
• Understanding of how AI/ML solutions are used in production systems (integration, inference, workflows)
• Experience working with data (structured and/or semi-structured datasets)
• Familiarity with data pipelines, backend systems, or distributed data workflows
• Ability to troubleshoot and support production environments and technical systems
• Strong problem-solving mindset and ability to work in complex enterprise environments
• Good communication skills and ability to collaborate with engineers and technical stakeholders
• Upper-Intermediate English or higher

Nice to have:

• Experience with Palantir Foundry and/or AIP
• Experience in big pharma or highly regulated industries.
• Exposure to production support, monitoring, or platform reliability engineering

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

We are looking for a Middle AI/ML Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will focus on building and iterating on machine learning and LLM-based solutions, integrating them into Foundry workflows to support analytics, automation, and decision-making. You will collaborate closely with data engineers, business analysts, and domain experts to deliver practical, production-ready AI solutions.

Key Responsibilities:

• Develop and enhance machine learning and AI models to support predictive analytics, classification, forecasting, and AI-assisted workflows.
• Build AI and ML solutions within Palantir Foundry, using Python and existing Foundry pipelines, Ontology objects, and workflows.
• Apply LLMs and NLP techniques (e.g. prompt engineering, fine-tuning, embeddings, retrieval-augmented workflows) using Palantir AIP for enterprise use cases.
• Collaborate with data engineers to understand data sources, ensure data quality, and prepare datasets for model training and inference.
• Conduct experiments, evaluate model performance, and iterate on features and model approaches.
• Integrate AI models into Foundry workflows to surface insights and support business processes.
• Support model deployment and monitoring by following established team standards and best practices.
• Work closely with business and domain stakeholders to translate requirements into practical AI-driven solutions.
• Document model behavior, assumptions, and limitations to support transparency and compliance.
• Stay up to date with applied AI and GenAI trends and contribute ideas under guidance from senior team members.

Requirements:

• 3+ years of experience in machine learning, AI engineering, or applied data science.
• Strong Python skills; experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Hands-on experience with LLMs, NLP, or GenAI use cases (e.g. prompt design, embeddings, text classification, summarization).
• Practical understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and iteration.
• Experience working with structured data (tabular, time series); exposure to text or unstructured data is a plus.
• Familiarity with enterprise data environments and collaborative development workflows.
• Ability to clearly explain model results and AI behavior to non-technical stakeholders.
• Upper-Intermediate English or higher.

Nice to have: 

• Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
• Experience in big pharma or highly regulated industries.
• Knowledge of data privacy, compliance, and security best practices in AI applications.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

We are building the next generation of AI Agentic Marketing Solutions specifically for the Game Development industry. We don’t just build simple chatbots; we build autonomous agents that plan, execute, and optimize User Acquisition (UA) and marketing campaigns for gaming studios.

We are looking for a versatile Product Engineer based in Europe to join our high-performance team and build the end-to-end features that power our agents.

The Role

You will be the bridge between our AI logic and the user experience. You will work across the entire stack—from developing AI agents to building the FastAPI endpoints that drive our agents that our clients use to manage their AI marketing teams.

Key Responsibilities

• Agents Development: Build and maintain AI agents and features from the database level up to the UI.
• Agent Integration: Work closely with our AI team to integrate LangGraph/LangChain workflows into the platform.
• API Design: Develop and optimize high-performance APIs using Python (FastAPI).

Requirements

• AI Expertise: Proven track record of building and scaling AI-powered products. You know the difference between a tutorial and a production-grade agentic system. While you don't need to be an AI researcher, you should have experience with LLM integration and agentic frameworks. 
• Engineering Mastery: 5+ years of experience in software engineering. Solid Python skills with a focus on asynchronous programming (FastAPI, AsyncIO). Familiarity with PostgreSQL, Redis, and modern CI/CD practices. 
• Agentic Frameworks: Deep experience with LangGraph, LangChain, and/or similar libraries.
• Product Mindset: You care about the user experience and understand how your code impacts the business goals of our GameDev clients. 

What We Offer

• High Impact: No bureaucracy. Your code shapes the future of GameDev marketing.
• Elite Team: Work alongside senior experts who value "Delivery in 1 Second" and relentless improvement.
• Medical Insurance in Ukraine and Multisport program in Poland.
• Offices in Ukraine (Kyiv, Kharkiv) and Poland (Wroclaw) or Remote.
• Paid vacation, sick leaves, and official holidays.
• Legal & Accounting services.
• The company provides all necessary equipment.
• English classes and Education reimbursement.

We are building the next generation of AI Agentic Marketing Solutions specifically for the Game Development industry. We don’t just build simple chatbots; we build autonomous agents that plan, execute, and optimize User Acquisition (UA) and marketing campaigns for gaming studios.

We are looking for an AI Jedi—a top-tier engineer who lives and breathes agentic orchestration and can solve the most complex problems in the LLM space.

The Role

This is a high-impact, individual contributor role for a master of AI engineering. You will be responsible for the "brain" of our platform. We need someone who can move beyond basic RAG and prompt engineering to build sophisticated, self-correcting, and autonomous agentic workflows that deliver results for the world’s biggest gaming studios.

Key Responsibilities

• Architecting Autonomy: Design and implement high-level agentic orchestration using LangGraph or custom state-machine frameworks.
• AI Excellence: Solve complex challenges related to agent memory, long-term planning, and multi-agent collaboration.
• Performance & Reliability: Build robust evaluation loops and guardrails to ensure our agents perform reliably in production environments.
• Innovation: Stay at the absolute bleeding edge of AI research, quickly turning new papers and techniques into production-ready features.

Requirements

• Deep AI Expertise: Proven track record of building and scaling AI-powered products. You know the difference between a tutorial and a production-grade agentic system.
• Python Mastery: Expert-level Python skills with a focus on asynchronous programming (FastAPI, AsyncIO).
• Agentic Frameworks: Deep experience with LangGraph, LangChain, and/or similar libraries.
• Infrastructure Savvy: Comfortable with Vector Databases, high-scale data pipelines, and cloud infrastructure (AWS/K8s).
• Startup DNA: You are a "Builder." You value speed, pragmatism, and shipping code that works over theoretical perfection.

What We Offer

• High Impact: No bureaucracy. Your code shapes the future of GameDev marketing.
• Equity & Growth: A fast-track path to a key leadership role with a stake in the company’s success.
• Elite Team: Work alongside senior experts who value "Delivery in 1 Second" and relentless improvement.
• Medical Insurance in Ukraine and Multisport program in Poland.
• Offices in Ukraine (Kyiv, Kharkiv) and Poland (Wroclaw) or Remote.
• Paid vacation, sick leaves, and official holidays.
• Legal & Accounting services.
• The company provides all necessary equipment.
• English classes and Education reimbursement.

Overview
We are looking for a Machine Learning Engineer to design and implement intelligent systems that power personalized digital experiences across connected devices and mobile applications.

This is a hands-on role focused on applied machine learning and data engineering, ideal for someone who thrives at the intersection of ML models, data pipelines, and product integration. You will collaborate closely with backend engineers, data scientists, and product managers to bring ML-driven features into production and continuously optimize them based on real-world usage.

Responsibilities:

• Design, train, and deploy machine learning models for use cases such as personalization, recommendations, and visual analysis;
• Build and maintain scalable, production-grade data pipelines (batch and real-time);
• Collaborate with product and engineering teams to translate product ideas into ML-powered features;
• Implement model observability, monitoring, and retraining workflows;
• Optimize inference performance and model serving in resource-constrained environments (e.g., edge or mobile);
• Contribute to the architecture of a modern ML platform within a cloud-native microservices environment;
• Work with backend teams to expose model outputs via APIs and integrate them into customer-facing experiences;

• Stay up to date with recent ML/AI advancements and evaluate promising methods for future implementation.

   

Requirements:

• 3+ years of experience in applied machine learning or data science;
• Strong knowledge of:
  • Supervised learning, recommendation systems, or computer vision;
  • Python and ML libraries such as TensorFlow, PyTorch, scikit-learn;
  • Building, deploying, and maintaining ML models in production.
• Familiarity with:
  • MLOps tools (e.g., MLflow, TFX, Airflow, Vertex AI);
  • Data pipelines and messaging systems (e.g., Kafka, BigQuery, dbt);
  • Model serving frameworks (e.g., FastAPI, TensorFlow Serving, TorchServe, ONNX);
• Comfortable collaborating with product, engineering, and analytics teams;
• Experience with cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• Bonus: Experience with edge AI, mobile ML, or video/image processing pipelines.

Acropolium, together with its international partner in the energy industry, is looking for two experienced AI Developers to join an intelligent automation & digitalization initiative.

The project focuses on building enterprise-grade AI solutions and AI agents within a Microsoft ecosystem, covering the full development lifecycle — from requirements analysis and architecture design to implementation, deployment, and continuous improvement.

You will work with modern AI orchestration frameworks, Azure AI services, and Microsoft Power Platform technologies to deliver scalable, production-ready solutions integrated into enterprise environments.

Project Details

• Start date: May 15, 2026
• Duration: 6 months with possible extension
• Workload: Full-time
• Location: Remote
• English level: Upper-Intermediate / Advanced (C1

Responsibilities

• Design and develop AI Agents using Azure AI Foundry
• Build and enhance Copilot Studio Agents within Microsoft Power Platform
• Implement LLM-based information extraction pipelines for document processing and data extraction
• Develop and maintain backend services and APIs using Python and FastAPI
• Implement event-driven and queue-based processing solutions
• Integrate AI solutions with enterprise systems, including potential SAP integrations
• Participate in architecture discussions and technical solution design
• Support deployment, monitoring, maintenance, and continuous optimization of AI systems
• Collaborate with cross-functional and international teams throughout the delivery lifecycle

Requirements

• Strong commercial experience with Python backend development
• Hands-on experience with FastAPI
• Solid experience building solutions within Microsoft Azure environments
• Experience with Azure OpenAI and LLM integrations in production environments
• Strong knowledge of Azure AI Foundry and AI agent development
• Commercial experience with Microsoft Power Platform, especially Copilot Studio
• Experience with LangChain and LangGraph
• Understanding of scalable AI architectures and orchestration patterns
• Experience delivering production-grade AI solutions
• Upper-Intermediate or Advanced English level (C1)

Nice to Have

• Experience with Azure Storage Queues
• Experience with Azure Blob Storage
• Experience with Azure Document Intelligence
• Understanding of event-driven architectures
• Enterprise integration experience, including SAP landscapes
• DevOps and operational support experience for AI systems

We Offer

• High-impact leadership role across a group of tech companies

• Opportunity to build a modern AI-first marketing function from scratch

• Freedom in decision-making and real business impact

• Remote-first, flexible format

• Long-term collaboration

Who are we?

Sempico Solutions is an international telecom company and business messaging service built around our own product — the Gatum messaging platform. We help our clients deliver different types of messages, such as marketing campaigns, verification messages, OTPs (one-time passwords), and more.

Our mission is to provide fast, simple, and reliable communication between businesses and customers — through SMS and messaging apps — with global reach, anywhere, always.

Our benefits:

• Work in a fast-growing product company where you can grow together with the business.
• Annual paid vacation of 24 calendar days and paid sick leave.
• Remote working format.
• Convenient working hours from Monday to Friday from 9:00 to 18:00 UTC+2 (including 1 hour for lunch).
• Competitive salary: base rate with an opportunity to review each 6 months.
• Step-by-step onboarding and training process.
• Planning your individual career path together with your manager.
• Reimbursement of expenses for professional development courses/certifications (up to 75% in agreement with the management).
• Strong positive product-company culture with a good sense of humor.

What about the team?

🏡 100% remote | 🌎 Global team

At our company, everyone is on a first-name basis. There's no unnecessary bureaucracy. We work together, support each other, and move toward common goals. At Sempico Solutions, you'll quickly feel what it means to be a real part of the Team.

Requirements

At Sempico Solutions, we're looking for a hands-on AI Engineer (Middle+/Senior) who doesn't just experiment with models — but builds AI systems that work reliably in production and deliver measurable impact on real business processes.

You are someone who thinks in terms of quality metrics, not "generally good." You bring structure to data and logic, take ownership of AI outcomes, and know how to move from idea to stable production without losing quality along the way.

Our ideal candidate has:

• 3+ years of experience in AI/ML in production environments (not pet projects).
• Confident Python skills — your primary working language.
• Hands-on experience with LLM APIs in production (OpenAI, Anthropic, or open-source models).
• Systematic approach to prompt engineering: versioning, A/B testing, quality control.
• End-to-end RAG architecture experience: chunking, embeddings, retrieval, reranking, vector databases (Pinecone, Qdrant, Weaviate, or pgvector).
• Experience building AI evaluation frameworks — automated quality tests for AI responses.
• Knowledge of privacy and GDPR considerations when working with client data.
• REST API integration experience and async I/O work.
• Basic DevOps skills: Docker, monitoring, logging.
• Fluent Ukrainian (C1 or native) and English at B2 Upper Intermediate level or higher (both spoken and written).
• Understanding of prompt injection risks and data leak prevention.

Nice to have:

• Experience integrating messengers: Telegram Bot API, WhatsApp Business API, Microsoft Teams Graph API.
• Experience with support platforms: HelpCrunch, Intercom, or Zendesk API.
• Familiarity with LangChain, LlamaIndex, or Haystack.
• Classical ML background: scikit-learn, PyTorch, or TensorFlow.
• Experience in CPaaS / SMS industry.
• Automation tools: n8n, Zapier, or Make — for rapid flow prototyping.
• PHP reading ability (to navigate the existing product codebase).
• Experience building AI systems from scratch in a startup environment.

What You'll Do

• Build and maintain a unified client inbox — bringing all communication channels (Telegram, WhatsApp, Teams, HelpCrunch, email) into one structured place.
• Launch and continuously develop the AI Support mechanism across all client chat channels.
• Form and maintain the knowledge base that powers AI responses.
• Monitor AI response quality in production: track metrics, run A/B tests, proactively detect degradation.
• Control and optimize AI call costs — you know what your solution costs per month in tokens.
• Integrate AI into other business processes: sales, analytics, and internal tooling.
• Document AI architecture, flow logic, and known limitations clearly — for both technical and non-technical colleagues.

ABOUT THE COMPANY
AI startup building digital employees (AI agents) that handle real business operations — not another ChatGPT wrapper. Our architecture: a modular monolith (uv workspaces + Turborepo) that cleanly extracts into microservices once product-market fit is reached.

RESPONSIBILITIES
— Rapid MVP development of AI agents
— Building and maintaining agent graphs with LangGraph
— Background task orchestration (Temporal — upcoming)
— Enforcing strict modularity within the monorepo
— Working with LLMs and vector databases

MUST-HAVE
— Senior Python / Backend engineer
— Strong FastAPI and PostgreSQL skills
— Solid understanding of modular architecture
— Hands-on experience building multi-agent systems with LangGraph

NICE-TO-HAVE
— Product thinking
— React / Next.js
— Temporal (orchestration)
— Vector DBs: Qdrant, pgvector
— FinOps/LLMOps: LiteLLM, Traceloop
— Evals: Ragas
— Vercel AI SDK

OFFER
— Fully remote
— No bureaucracy, fast processes
— Strong team, rapid growth

Our company is developing its own interactive knowledge base. Users can upload any volume of diverse data, after which the system automatically transforms it into structured, searchable content. To achieve this, we use a comprehensive ML pipeline involving OCR, vision-language models, document parsers, and multiple types of data storage. Search is implemented through an LLM-based chat interface that allows users to submit queries in natural language, retrieve relevant documents, and receive summarized findings and recommendations based on the uploaded materials.

We are currently looking for an ML/AI Engineer with deep experience working with unstructured content - primarily photographs and scanned document copies - who will strengthen our team and lead the development of pipelines and solutions for processing this type of data.

We expect the candidate to:

• Have broad experience working with unstructured data and have used both classical OCR systems (Tesseract, PaddleOCR, EasyOCR) and modern models (PaddleOCR-VL, DeepSeek-OCR, dots.ocr, Qwen3-VL). Understand the strengths and weaknesses of different architectures and the scenarios in which each is most effective.
• Have hands-on experience training and fine-tuning OCR and Vision-Language models.
• Understand algorithmic approaches to image enhancement, preprocessing, and filtering in order to improve downstream recognition quality.
• Have worked with Docling (including advanced backend tuning for parsing complex PDFs and tables), markitdown, Apache Tika, PyMuPDF, and other tools for document conversion and structuring. Be comfortable with processing layered and non-trivial PDF files.
• Have experience working with self-hosted models, including deploying and optimizing models in vLLM environments on H100-class GPUs and above, and understand the principles of GPU architecture and KV cache.
• Have strong Python programming skills, including architectural patterns, multithreading, asynchronous programming, modern testing practices, and experience operating services under high load (monitoring, telemetry, memory utilization).
• Have experience working with document-oriented, relational, and vector databases, and understand index types and the relevant use cases for each type of storage.

It would be a plus if you have:

• Experience working with Speech-to-Text or Video-to-Text pipelines.
• Experience in content analysis, including classification, summarization, and NER.
• Experience in data engineering: understanding of ETL/ELT processes, experience with orchestrators (Airflow, Temporal, Prefect), and distributed computing systems (Ray, Spark).
• Experience in DevOps: CI/CD, Kubernetes, Helm, ArgoCD.
• Experience working with Elasticsearch, MongoDB, PostgreSQL, Qdrant/Milvus, Neo4j, and other storage systems.
• Understanding of modern cybersecurity approaches.
• Hands-on experience with production-grade RAG-based systems.

We offer a fully remote work format on our own product, which uses state-of-the-art technologies and is focused on the public sector. The company has the status of being critically important to the Armed Forces of Ukraine. If needed, we provide military deferment and the necessary office equipment.

–––––––––––––––––––––––––––––Українською–––––––––––––––––––––––––––––

Наша компанія розробляє власну інтерактивну базу знань. Користувачі можуть завантажувати будь-який обсяг різноманітних даних, після чого система автоматично перетворює їх на структурований, придатний для пошуку контент. Для цього застосовується комплексний ML-пайплайн із залученням OCR, VL моделей, документних парсерів та різних типів сховищ даних. Пошук реалізовано через чат на базі LLM, який дозволяє формувати запити звичайною мовою, отримувати релевантні документи, а також узагальнені висновки та рекомендації на основі завантажених матеріалів. 

Зараз ми шукаємо ML/AI інженера з глибоким досвідом роботи з неструктурованим контентом (насамперед фотографіями та скан-копіями документів), який підсилить нашу команду та очолить напрям розробки пайплайнів і рішень для обробки таких даних. 

Ми очікуємо, що кандидат: 
• Має широкий досвід роботи з неструктурованими даними та застосовував як класичні OCR-системи (Tesseract, PaddleOCR, EasyOCR), так і сучасні моделі (PaddleOCR-VL, DeepSeek-OCR, dots.ocr, Qwen3-VL). Розуміє сильні та слабкі сторони різних архітектур і сценарії їх застосування. 
• Має практичний досвід навчання та fine-tuning OCR і Vision-Language моделей. 
• Розуміє алгоритмічні методи покращення зображень, їх попередню фільтрацію та обробку для підвищення якості подальшого розпізнавання. 
• Працював з Docling (включно з тонким налаштуванням бекендів для парсингу складних PDF і таблиць), markitdown, Apache Tika, PyMuPDF та іншими інструментами для конвертації й структуризації документів. Орієнтується у процесингу багатошарових і нетривіальних PDF-файлів. 
• Має досвід роботи з self-hosted моделями, зокрема запуску та оптимізації моделей у середовищах vLLM на GPU рівня H100 і вище, розуміє принципи GPU-архітектури та KV cache. 
• Має сильні навички програмування на Python: архітектурні патерни, багатопоточність, асинхронність, сучасні практики тестування, досвід експлуатації сервісів під високим навантаженням (моніторинг, телеметрія, утилізація пам'яті). 
• Має досвід роботи з документоорієнтованими, реляційними та векторними базами даних, розуміє типи індексів і відповідні юзкейси для кожного типу сховищ. 

Буде плюсом: 
• Досвід роботи з Speech-to-text або Video-to-text пайплайнами.
• Досвід аналізу контенту: класифікація, сумаризація, NER. 
• Досвід у data engineering: розуміння ETL/ELT-процесів, робота з оркестраторами (Airflow, Temporal, Prefect) та системами розподіленого обчислення (Ray.io, Spark). 
• Досвід у DevOps: CI/CD, Kubernetes, Helm, ArgoCD. 
• Досвід роботи з Elasticsearch, MongoDB, PostgreSQL, Qdrant/Milvus, Neo4j та іншими сховищами. 
• Розуміння сучасних підходів до кібербезпеки. 
• Практичний досвід із системами на основі RAG у продакшені. 

Пропонуємо повністю віддалений формат роботи над власним продуктом, який використовує найсучасніші технології та орієнтований на державний сектор. Компанія має статус критично важливої для Збройних сил України. За потреби надаємо бронювання та необхідну офісну техніку.

We are looking for a specialist who will be responsible for the development and maintenance of a complex AI-powered search system built on top of a large interactive knowledge base. The system includes tool calling and agentic behavior that interact with internal tools and multiple types of storage: vector databases for semantic search, document-oriented databases for full-text search, as well as relational and graph databases for lookup by specific identifiers. The search interface is built as an LLM-powered chat that supports natural language queries and returns well-grounded conclusions, recommendations, and links to primary sources.

The candidate will be responsible for designing and implementing the full LLM-powered search pipeline, including orchestration, reasoning, reranking, tool calling, handling tool outputs, validating results, and generating final user-facing responses.

We expect the candidate to:

• Have hands-on commercial experience working with vLLM in self-hosted environments, including model optimization on H100/H200 GPUs, with a solid understanding of GPU architecture principles and cache behavior under production workloads.
• Have a deep understanding of the RAG concept and a proven track record of successfully deploying similar solutions in production.
• Have worked with Haystack, LlamaIndex, LangChain, or similar frameworks, and understand the core differences between them.
• Have experience using MCP and working with LLMs that call external tools and services.
• Have strong Python skills, including architectural principles, design patterns, multithreading, asynchronous programming, modern testing practices, and experience operating systems under load (monitoring, memory optimization, telemetry).
• Have experience working with document-oriented, relational, and vector databases, including an understanding of index types and the appropriate use cases for each.

It would be a plus if you have:

• Experience building or maintaining knowledge bases, AI-powered reporting systems, or chatbots with large context windows.
• Experience training or fine-tuning LLMs or compact models for domain-specific tasks.
• Practical DevOps experience: CI/CD, Kubernetes, Helm, ArgoCD.
• Experience developing OCR- and Vision-Language-based systems for processing unstructured data.
• Experience in data engineering: understanding of ETL/ELT processes, working with orchestrators (Airflow, Temporal, Prefect), and distributed computing systems (Ray, Spark).
• Experience working with Elasticsearch, MongoDB, PostgreSQL, Qdrant/Milvus, Neo4j, and other database systems.
• Understanding of cybersecurity processes and modern approaches to data protection.

We offer a fully remote work format on our own product, which uses state-of-the-art technologies and is focused on the public sector. The company has the status of being critically important to the Armed Forces of Ukraine. If needed, we provide military deferment and the necessary office equipment.

––––––––––––––––––––––––––––Українською––––––––––––––––––––––––––––

Шукаємо фахівця, який буде відповідати за розробку та супровід комплексної AI-powered пошукової системи на основі великої інтерактивної бази знань. У системі реалізовано tool calling та agentic behaviour, що працюють із внутрішніми інструментами та різними типами сховищ: векторними базами для семантичного пошуку, документоорієнтованими для повнотекстового пошуку, а також реляційними та графовими базами для пошуку за конкретними ідентифікаторами. Інтерфейс пошуку побудовано у форматі LLM-powered чату, який підтримує запити natural language і повертає аргументовані висновки, рекомендації та посилання на першоджерела. 

У зону відповідальності кандидата входитиме проєктування та впровадження повного пайплайну LLM-powered пошуку, включно з orchestration, reasoning, reranking, tool calling, обробкою відповідей інструментів, валідацією результатів та формуванням фінальних відповідей для користувача. 

Ми очікуємо, що кандидат: 

• Має практичний комерційний досвід роботи з vLLM у self-hosted середовищах, включно з оптимізацією моделей на GPU H100/200, розумінням принципів GPU-архітектур та поведінки кешу під продакшн-навантаженням. 
• Глибоко розуміє концепцію RAG та має досвід успішного впровадження подібних рішень у продакшені. 
• Працював з Haystack / LlamaIndex / LangChain або аналогічними фреймворками та орієнтується в принципових відмінностях між ними. 
• Має досвід використання MCP та роботи з LLM, які викликають зовнішні інструменти й сервіси. 
• Володіє Python на високому рівні: архітектурні принципи, шаблони проєктування, багатопоточність, асинхронність, сучасні практики тестування, а також досвід експлуатації систем під навантаженням (моніторинг, оптимізація пам'яті, телеметрія). 

• Має досвід роботи з документоорієнтованими, реляційними та векторними базами даних, включно з розумінням типів індексів і відповідних сценаріїв застосування. 

   

Буде плюсом: 

• Досвід створення або підтримки баз знань, систем генерації звітів на базі AI, розробка чатботів із великим контекстним вікном.
• Досвід навчання або fine-tuning LLM чи компактних моделей для специфічних задач. 
• Практичний досвід у DevOps: CI/CD, Kubernetes, Helm, ArgoCD. 
• Досвід розробки систем на основі OCR та Vision-Language моделей для обробки неструктурованих даних. 
• Досвід у data engineering: розуміння ETL/ELT-процесів, робота з оркестраторами (Airflow, Temporal, Prefect) та системами розподіленого обчислення (Ray.io, Spark). 
• Досвід роботи з Elasticsearch, MongoDB, PostgreSQL, Qdrant/Milvus, Neo4j та іншими СУБД. 
• Розуміння процесів кібербезпеки та сучасних підходів до захисту даних. 
   

Пропонуємо повністю віддалений формат роботи над власним продуктом, який використовує найсучасніші технології та орієнтований на державний сектор. Компанія має статус критично важливої для Збройних сил України. За потреби надаємо бронювання та необхідну офісну техніку.

Fullstack + AI Engineer middle · fullstack + ai

Доводити MVP до production — від першого коміту до живих користувачів

Ми шукаємо людину, яка думає продуктово: розуміє, навіщо та що будується, і може зробити технічний вибір без мікроменеджменту

Технічний стек

Frontend / Backend

• React
• Node.js
• TypeScript
• REST API
• GraphQL

Бази даних

• PostgreSQL
• MongoDB
• Redis

AI / LLM Engineering

• RAG
• Qdrant
• Embeddings
• Reranking
• Hybrid search
• Chunking
• Prompt engineering
• Function calling
• Streaming
• LangChain / LlamaIndex

Інфраструктура

• Docker
• Docker Compose
• CI/CD (буде плюсом)
• AWS / GCP (буде плюсом)

Обов’язки

• Підхоплювати MVP на будь-якому етапі й доводити до production-готовності
• Проектувати та розробляти fullstack-фічі: API + UI + БД — від дизайну схеми до кінцевого рендеру
• Будувати AI-пайплайни: ingestion → chunking → embedding → retrieval → generation
• Оптимізувати RAG-системи: hybrid search, reranking, query routing, eval-метрики
• Інтегрувати LLM-провайдерів (OpenAI, Anthropic, Mistral, local models)
• Писати чіткі, підтримувані промпти та function-calling схеми з версіонуванням
• Кодревʼю, документація, участь у технічних дискусіях

Вимоги

Fullstack (must have)

• 2+ роки комерційного досвіду React + Node.js
• TypeScript — впевнено, зі строгими типами
• REST та GraphQL API — проектування і споживання
• PostgreSQL — складні запити, індекси, транзакції
• MongoDB, Redis — базовий практичний досвід
• Docker + Docker Compose — локально і в prod

AI Engineering (must have)

• Практичний досвід побудови RAG-систем
• Розуміння embeddings, vector store, cosine similarity
• Досвід з Qdrant або аналогічним vector DB
• Prompt engineering: few-shot, CoT, system prompts
• Function calling / tool use з будь-яким LLM-провайдером
• Streaming відповідей (SSE / WebSocket)

Буде великим плюсом

• Досвід з LangChain, LlamaIndex або власними оркестраторами
• Робота з локальними моделями (Ollama, vLLM, llama.cpp)
• Eval-фреймворки для LLM: RAGAS, DeepEval, TruLens
• Агентніархітектури: ReAct, Plan-and-Execute, multi-agent
• Досвід fine-tuning або PEFT (LoRA, QLoRA)
• CI/CD пайплайни, хмарна інфраструктура (AWS / GCP / Azure)
• Observability інструменти: LangSmith, Langfuse, Helicone

Ми пропонуємо

Рівень

Middle, з ростом до Senior

Формат

Remote / Hybrid, гнучкий графік

Технології

Сучасний стек, реальні AI-продукти

Команда

Невелика, без бюрократії

Зростання

Менторство та code review

Вплив

Видно результат своєї роботи

You will work on scalable AI solutions, developer-focused tools, workflow automation, and AI capabilities that improve engineering productivity and deliver real business value for clients.

Responsibilities:

— Design, build, and deploy LLM-based applications and agentic AI systems from prototype to production.

— Develop production-grade AI agents, multi-agent systems, and tool-using workflows.

— Implement RAG pipelines over proprietary and third-party data sources.

— Build and maintain vector databases for AI data storage, retrieval, and search.

— Design and implement AI-powered capabilities such as code assistance, documentation generation, test automation, summarization, knowledge discovery, and code review support.

— Evaluate foundation models such as OpenAI, Anthropic, Gemini, Llama, and other commercial or open-weight models.

— Build LLM evaluation and benchmarking pipelines, including offline tests, online monitoring, human-in-the-loop review, and quality measurement.

— Improve model performance across relevance, faithfulness, latency, throughput, reliability, and cost.

— Design and maintain APIs, backend services, integrations, data flows, and custom tools for AI systems.

— Build custom tools, skills, integrations, and MCP-style server/client patterns for agentic workflows.

— Deploy, monitor, and optimize AI systems on cloud platforms, with a focus on scalability, reliability, observability, and cost efficiency.

Requirements: 

— 2+ years of hands-on experience building and deploying LLM-based applications, RAG systems, or AI agents in production.

— Strong Python experience, ideally 3+ years.

— Experience building backend systems, APIs, services, integrations, and data flows.

— Experience with object-oriented programming, backend architecture, design patterns, and production system design.

— Hands-on experience with LangChain, LangGraph, or similar AI orchestration frameworks.

— Strong experience designing agentic AI systems, tool-using agents, or multi-step AI workflows.

— Experience with RAG architecture, including chunking strategies, embeddings, vector databases, reranking, and retrieval evaluation.

— Experience with vector databases such as Pinecone, Weaviate, Qdrant, Chroma, Milvus, or similar.

— Experience with LLM evaluation and benchmarking, including designing evaluation pipelines and measuring model performance.

— Strong prompt design, prompt iteration, and prompt optimization skills.

— Experience working with major model providers or open-weight models such as OpenAI, Anthropic, Gemini, Llama, or similar.

— Cloud experience with AWS, GCP Vertex AI, Azure AI Foundry, or similar platforms.

— Familiarity with AI safety, responsible AI, guardrails, and output validation for production systems.

— Experience with CI/CD pipelines, deployment workflows, and engineering best practices.

We offer:

— remote time job, B2B contract
— 12 sick leaves and 18 paid vacation business days per year
— Comfortable work conditions (including MacBook Pro and Dell monitor on each workplace)
— Smart environment
— Flexible work schedule
— Competitive salary according to the qualifications

Backend AI Engineer

[Freelance, Full-time, Remote]

SNEAK PEEK

⇨ Location: Remote, GMT+0/+4

⇨ Interview process: HR Interview ⇨ Technical interview ⇨ Take-home challenge ⇨ Presentation of home challenge 

WHO ARE WE? 

At Rounds, we believe in harnessing the power of cutting-edge technology to drive business success. Our transformative, machine-learning technology identifies and optimizes mobile assets, while our team of experts, with their unparalleled human capital and business acumen, provides the strategic direction and support to turn mobile assets into profitable businesses. Together, we are revolutionizing the mobile industry. 

THE ROLE

We’re looking for a strong systems-oriented engineer with hands-on LLM experience to join our AI Innovation team. In this role, you’ll build AI systems and internal products that improve how teams work across different departments and areas in the company. The common denominator is ownership: you should be comfortable leading projects end-to-end, including clarifying needs with stakeholders, making decisions under ambiguity, and pushing through blockers when they arise.

This role is a strong fit for someone who enjoys both sides of applied AI work: full-stack engineering and practical use of LLM capabilities.

Hiring manager: Ori Nahum, AI Innovation Team Lead 

What you’ll be working on

Examples of projects you may work on:

• AI agents for code generation workflows (especially in mobile applications)
• A mobile app navigation agent
• Backend services that orchestrate LLM workflows, tool calling, and integrations with internal systems
• AI chatbot connected to internal data sources and business systems
• And other new AI-driven solutions that support different departments across the company

You’ll be expected to move between experimentation and implementation: validating ideas quickly, turning the promising ones into reliable tools, and leading projects far enough to make them useful in practice, not just technically possible.

WHAT ARE WE LOOKING FOR?

Must-have

• 5+ years experience in software development (preferably in Python, TypeScript, or mobile development).
• Ability to lead projects from idea to production, including aligning with stakeholders, driving decisions, and proactively removing blockers when needed
• Hands-on experience building LLM-based products, tools, or agents beyond toy prototypes
• Good understanding of prompt design, tool calling, orchestration, and how to make LLM systems actually useful
• Strong English communication skills

Big advantage

• Experience building internal developer tools or productivity systems
• Background in mobile development, especially native Android or iOS
• Design and implement evaluation frameworks to assess AI performance, accuracy, and reliability.
• Solid understanding of ML theory and how LLMs work under the hood, including key concepts, limitations, and trade-offs beyond the API layer
• Familiarity with cloud infrastructure / DevOps / CI-CD
• Good judgment around where AI adds value and where it doesn’t

Who will do well here

You’ll likely do well in this role if you:

• Like building practical systems, not just demos
• Take initiative without waiting for perfect specs
• Enjoy exploring new tools, but know how to separate hype from what’s actually useful
• Want the freedom to research, experiment, and then ship
• Enjoy working across different problem spaces and use cases, rather than staying in one narrow lane

INTERESTED?

Our recruitment process consists of the following steps: 

• HR interview with the recruitment manager: 45 min
• Technical interview with the AI Engineer Tech Lead & Team Lead: 1 hour
• Take-home challenge: ~ 4 hours of work
• Final Interview - take-home challenge presentation with CTO and AI Engineer Team Lead and Tech Lead: 1 hour

Required Skills
Experience building RAG pipelines and agentic systems
Strong understanding of LLM orchestration frameworks:
LangChain, LangGraph, Langfuse for example
Strong backend engineering experience with Python
Hands‑on experience building APIs/services with FastAPI
Experience integrating with MCP tools, internal APIs, and enterprise systems
Experience building Agent Factories, agent workflows, or multi-agent systems
Solid understanding of distributed systems and event-driven architectures
Experience deploying and operating services on AWS (EKS, S3, Lambda, IAM, networking)
Familiarity with GitLab CI for automated testing and deployments

Desired Skills
expertise with OpenSearch:
Index design, ingestion pipelines, analyzers, relevance tuning
Vector search, hybrid search, embeddings integration
Performance tuning and scaling clusters
Knowledge of embeddings generation and vector database best practices
Experience with OpenSearch plugins, custom scoring, or ingestion frameworks
Familiarity with Kubernetes
Experience with observability stacks (OpenTelemetry, Prometheus, Grafana, Langfuse)
Understanding of enterprise security, RBAC, and data governance
Prior experience building internal knowledge platforms or developer tools

Start ASAP
Duration 6 MM
Location: EU
English language