Jobs Data & Analytics

We are looking for a Senior AI/ML Engineer to design, build, and scale AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will take ownership of developing production-ready AI systems, including LLM-powered applications, RAG pipelines, and machine learning models, while collaborating closely with cross-functional teams. You will contribute to architectural decisions, ensure high-quality implementations, and help evolve AI capabilities within enterprise environments.

Key Responsibilities

• Design, develop, and enhance AI-driven solutions, including machine learning models, LLM-based applications, and NLP workflows for analytics, automation, and decision-making
• Build and optimize RAG pipelines, including embeddings, retrieval strategies, chunking approaches, and hybrid search techniques
• Develop AI solutions within Palantir Foundry, leveraging Ontology objects, pipelines, and workflows
• Apply LLMs and GenAI techniques (prompt engineering, fine-tuning, embeddings, retrieval-augmented generation) using Palantir AIP
• Own the end-to-end lifecycle of AI solutions: data preparation, model development, evaluation, deployment, and monitoring
• Collaborate with data engineers to ensure data quality, pipeline efficiency, and scalable data processing
• Integrate AI models into production workflows to deliver business-facing insights and automation capabilities
• Evaluate and improve model and system performance, including accuracy, latency, scalability, and cost-efficiency
• Contribute to architecture decisions, including selection of tools, frameworks, and design patterns for AI systems
• Implement and follow MLOps / LLMOps best practices, including versioning, evaluation frameworks, monitoring, and continuous improvement
• Ensure responsible AI practices, including data privacy, governance, and compliance considerations
• Collaborate with stakeholders to translate business needs into practical and scalable AI solutions

• Mentor junior engineers and contribute to knowledge sharing within the team

   

Requirements

• 4–5+ years of experience in AI/ML engineering, applied data science, or related fields
• Strong proficiency in Python and experience with ML frameworks (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow)
• Hands-on experience with LLMs, NLP, or GenAI applications (prompt engineering, embeddings, text processing, summarization, etc.)
• Practical experience with RAG architectures, vector databases, and retrieval strategies
• Strong understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and deployment
• Experience building and deploying production-grade AI systems
• Familiarity with structured and unstructured data processing (tabular, time series, text, documents)
• Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes)
• Understanding of MLOps / LLMOps practices, including monitoring, evaluation, and iteration
• Experience working in enterprise data environments with cross-functional teams
• Ability to communicate AI concepts and results to technical and non-technical stakeholders

• Upper-Intermediate English or higher

   

Nice to Have

• Experience with Palantir Foundry (Ontology, Object Builders, Code Repositories, AIP)
• Experience in regulated industries (e.g., pharma, finance)
• Experience with distributed data processing (e.g., Spark)
• Exposure to multilingual or multimodal AI systems

We are seeking a Senior AI Engineer to design, build, and scale enterprise-grade AI and Generative AI solutions. As part of a Business AI program, the team is building intelligent agents to streamline core enterprise processes and boost productivity. The goal is to free services professionals from repetitive tasks and accelerate time to value for customers. This role combines strong software engineering fundamentals with hands-on experience deploying LLM-powered systems into secure, production environments. You will drive initiatives from proof-of-concept through scalable enterprise deployment.

Details: 

Schedule: Full time remote 

Location: Europe-based 

Capacity: 100% (40 hours/week)
Language: English (mandatory), German (nice to have)

Responsibilities

AI Solution Development

Design, develop, and deploy enterprise AI and GenAI services

Guide solutions from PoC to secure production rollout

Build and integrate multi-agent AI systems and LLM-based products

Work with SAP data products and underlying data architectures

Manage ingestion, transformation, caching, and indexing workflows

Support distributed systems and big data processing environments

Implement CI/CD pipelines and MLOps best practices

Automate model training, validation, testing, and deployment

Work with Azure ML, Databricks, or AWS environments

Implement secure API design, secrets management, and access control

Contribute to security concept design

Ensure observability, reliability, and compliance in AI deployments

Collaborate with AI Product Owners, Data Scientists, and stakeholders

Create architecture diagrams, ADRs, and technical documentation

Ensure high-quality, well-documented codebases

Required Experience

7+ years of professional software engineering experience

Strong Python expertise (mandatory)

Experience with Node.js or Java (at least one additional language)

Backend framework experience (FastAPI, Flask, or Django)

Microservices architecture experience

Docker and Kubernetes experience

Experience with GitHub Actions, MLFlow, or similar orchestration tools

Hands-on ETL, API integration, and model deployment experience

Experience implementing CI/CD and MLOps in cloud environments

Knowledge of distributed systems and big data platforms

Experience working in Agile frameworks (Scrum, Kanban)

Fluent English and strong problem-solving mindset

Nice to Have

Experience with multi-agent or GenAI frameworks (LangChain, CrewAI)

Familiarity with SAP AI Core and SAP BTP

Experience with Jira (Scrum, SAFe)

A leading organization in the media streaming industry focuses on delivering innovative solutions that enhance user engagement and content accessibility. The company caters to a diverse audience, including individual consumers and content creators, providing them with advanced tools for content production and distribution. With a strong emphasis on technology, the organization leverages cutting-edge AI and machine learning capabilities to optimize user experiences and operational efficiency. Their commitment to continuous improvement and adaptation positions them as a significant player in the evolving media landscape.

We are looking for an experienced Data Engineer to participate in desing and architectute of client's data platform and GenAI initiatives. The primary focus of this role is building scalable distributed data processing systems that will serve as the foundation for the company's intelligent services.



Job Description

Required:

• Bachelor’s/Master’s degree in Computer Science, Computer Engineering, Machine Learning, or a related field.
• 4+ years of experience in software development, focusing on Python programming and data engineering.
• Strong expertise in Data Lake architecture and modern data warehousing.
• Hands-on experience with distributed computing systems (Apache Spark is a must).
• Strong Python proficiency for building complex pipelines and internal tooling.
• Good understanding of distributed systems principles, real-time data processing, and batch processing.
• Experience in scaling data infrastructure (AWS/GCP cloud solutions).
• Proven experience in designing and scaling vector databases (e.g. Pinecone, Milvus, Weaviate, pgvector etc.), experience in developing recommendation systems and retrieval-augmented generation (RAG) pipelines.
• Ability to independently drive technical discussions, make informed architectural assumptions, and justify technology choices.
• Ability to decompose complex "from scratch" tasks without detailed specifications.

Nice to have:

• Intermediate knowledge of Airflow for workflow management in data processing.
• Generative AI: Experience with vector databases, RAG architectures, or integrating LLMs into data pipelines.
• Experience designing and building middleware platforms, REST APIs, and distributed systems at scale.
• Web Development: Basic API development skills to provide data access to other services.

Job Responsibilities

• Data Platform: Designing and maintaining high-load Spark pipelines for processing terabytes of data.
• GenAI Support: Building data infrastructure for training and operating generative models (ingestion, cleaning, vectorization).
• Architectural Contribution: Active participation in technical brainstorming, developing data quality standards, and processing protocols.
• Optimization: Identifying and resolving bottlenecks in current distributed processing systems.

Our Mission and Vision

At Solidgate, our mission is clear: to empower outstanding entrepreneurs to build exceptional internet companies. We exist to fuel the builders — the ones shaping the digital economy — with the financial infrastructure they deserve. To achieve that, we’re on a bold path: to become the #1 payments orchestration platform in the world.

We believe the future of payments is shaped by people who think big, take ownership, and bring curiosity and drive to everything they do. That’s exactly the kind of teammates we want on board.
 

About the Role

As a Junior Business Analyst in the Account Management and Sales team, you’ll gain hands-on experience in fintech while strengthening your analytical, operational, and business skills.
This role places you at the core of client interaction and business process optimization, where every task directly contributes to Solidgate’s growth.

What you’ll own

• Analyzing sales results (Cross-sell/Up-sell), building metrics and reports, and providing recommendations to optimize team processes.
• Interacting with clients, addressing requests, and providing information about our products and services.
• Preparing presentations, documentation, and organizing meetings.
• Supporting operational processes within Account Management and Sales teams.
•  

You’re a great fit if you have

• Bachelor’s or Master’s degree (completed or in progress)
• Strong academic achievements and results
• English proficiency at Upper-Intermediate level or higher
• Excellent analytical and communication skills
• High level of responsibility and a results-driven mindset

Participation in international or academic programs (FLEX, Erasmus, CFA Research Challenge, or similar) will set you apart.

Why Solidgate?

— No internships here — we build careers. Get hands-on from day one and make a real impact.
— Your work = real outcomes. Shape how global companies move money.
— Grow like crazy. Learn from top fintech pros and level up faster than anywhere else.
— Flex your schedule. Balance studies and work with flexible hours that fit your life.
— Enjoy the ride. A wow office in Kyiv center, daily lunches, snacks, team buildings, and a learning budget to keep you growing.
 

💌 The Extras: 30+ days off, unlimited sick leave, free office meals, health coverage, and Apple gear to keep you productive. Courses, conferences, sports and wellness benefits — all designed for ideas, focus, and fun.

Tomorrow’s fintech needs your mindset. Come build it with us.

Department: Data Platform
Reports to: Data Engineering Lead
Employment Type: Full Time
Work Model: Fully Remote
Location: Remote EMEA

 

About Traffic Label

Traffic Label is a fast-growing, data-driven technology company operating in the iGaming and affiliate marketing space, building scalable products focused on performance, analytics, and automation across global markets.

What we’re building
We’re building a Customer Data Platform: one unified player profile across our group of brands. The platform should help the business:

 

• Improve acquisition. Understand who actually converts, and why others don’
• Increase conversion. Replace generic flows with journeys built for the specific player in front of us.
• Segment players properly. Who’s a high-value player? Who’s at risk of leaving? Who’s a VIP?
• Reactivate before churn. Spot players who are about to leave and bring them back with offers that match what they actually want.

Tech stack:

• Snowflake (with Snowpipe and Cortex Analyst LLM agent).
• dbt, Python.
• Airflow (Astronomer), AWS (S3, Lambda), Terraform, GitHub Actions.
• Omni BI on top. Reverse ETL into marketing platforms.
• Medallion architecture: bronze, silver, gold.

We’re early in the build, and the person we hire helps shape the foundation.

Role Overview
You sit between the business (Product Owner, stakeholders) and the engineering team.
About 30% of your time is practical data work: validating that CDP capabilities behave as specified, exploring data before specs are written, testing hypotheses for new capabilities, building shared gold layer models that consumer teams use, and helping those teams understand what data is available. It is not business reporting or analytics built for individual brands.

The other 70% is Systems Analysis: turning what you find into specs engineers can build from, owning data quality from symptom to root cause, raising what isn’t right before it ships, and shaping the semantic layer so other business lines can find and trust the data.

Four things define the systems analysis side:

1. Turn business intent into specs that engineers can build from. Talk to stakeholders, figure out what they actually need, and write it down. Each spec covers source schema, target model, transformation logic, business glossary, schedule, data quality checks, consumer, and use case. Stay reachable through development. Engineers will have questions.
2. Find and fix data quality problems at the root, alongside the engineering function. Trace lineage, identify the cause, work with the data source owner on the fix, check downstream impact, and close the loop.
3. Confirm what’s delivered does what we said it would. Validate against the spec you wrote. When the data isn’t right, you raise it before it ships.
4. Make data usable beyond the team that asked for it. Contribute to the semantic layer, data descriptions, and shared definitions so other business lines can find what they need, understand what it means, and trust it without going through you each time.

You work on the Data Platform layer: CDP build, identity resolution, data quality, semantic definitions, and governance. Business analytics on top of the platform, such as dashboards and performance reports for specific brands, is produced by analyst teams aligned to those brands. Your job is to make sure those teams can do theirs: trustworthy data, clear definitions, fast issue resolution.

The team
You sit within the Data Platform alongside:

• A Product Owner who sets the roadmap and business priorities.
• The Data Engineering function. Your manager (Data Engineering Lead) and the engineers building the platform.
• Embedded QA function. Owns automated validation.
• Shared DevOps across the wider organisation.

Where you’ll start
Identity resolution. Deterministic matching is already running in our MDM across five data sources. You extend coverage to the remaining sources and validate match quality at scale. The harder cases are future scope: hashed identifiers without keys, duplicates across sources, device and behaviour signals. They start when we add dedicated ML engineering capacity, with no committed timeline yet. You’ll own the spec and acceptance for that work when it begins.

Skills & Experience

• SQL. Expert level. Window functions, complex joins, and root cause investigation on large datasets.
• dbt. Practical experience. You can write models, write tests, and debug them.
• Python. Comfortable for ad hoc analysis, scripting, and data manipulation.
• Confident across the modern data stack. You investigate problems yourself instead of waiting for DE, and you can explain the root cause to the business in plain language.
• Medallion or layered data architectures.
• You’ve written specifications that engineers built from.
• You’ve owned a data quality problem from “something looks off” to “fixed at source”.
• You can talk to business stakeholders and a backend engineer in the same hour without losing either of them.
• Background in iGaming, affiliate marketing, SaaS, or other high-volume digital businesses.
• Experience unifying customer or user profiles across sources, sometimes called Customer 360 or Single Customer View. Angles: identity matching, semantic modelling, etc.

What We Offer

• Opportunity to work on scalable, high-impact products in a growing iGaming business
• Collaborative and fast-paced engineering environment
• Exposure to modern technologies and architecture
• Competitive salary and performance-based incentives
• Flexible working environment and supportive team culture

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

Join PwC’s pioneering data & AI team and help build the data foundations behind impactful AI solutions. We’re growing quickly due to a strong pipeline of client work, and we’re hiring across multiple seniority levels — from junior to senior Data Engineers and Data Scientists.

Across our projects, Python is the core skill we expect. Depending on your strengths, you may focus more on data engineering (pipelines, platforms, SQL) or data architecture (designing scalable data solutions). Many roles also include “full-solver” flexibility — contributing where needed, including automation, integration work, or enabling AI/GenAI use cases on modern platforms (including Microsoft technologies where relevant).

Key responsibilities:

• Data Pipeline Design & Development: Design, implement, and maintain scalable data pipelines and ETL/ELT processes, primarily using Python and Spark (PySpark), to ingest, transform, and deliver data from various sources into analytics and ML platforms.
• Data Modelling & Warehousing: Design and optimize data models (e.g. star/snowflake schemas), build and manage data warehouses and data lakes, and ensure data structures support reporting, analytics, and ML use cases.​
• Data Preparation for ML: Collaborate closely with data scientists and ML engineers to understand data requirements, implement robust preprocessing and feature engineering steps, and ensure datasets are clean, consistent, and suitable for machine learning models.
• Performance & Reliability: Optimize data processing jobs and SQL queries for performance and cost efficiency, monitor data pipelines in production, and ensure reliability, scalability, and adherence to SLAs.
• Client Collaboration: Work directly with clients across Western Europe and the USA to understand their data landscape and requirements, translate business needs into technical designs, and provide expert guidance on data architecture and best practices.
• Governance, Quality & Security: Implement data quality checks, validation frameworks, and governance standards; ensure data security, privacy, and compliance in line with PwC and client requirements.
• Learning & Development: Stay at the forefront of data engineering, big data, and cloud technologies, continuously improving existing solutions, tools, and processes.
• Mentorship: Support the growth of junior team members by sharing knowledge, reviewing code, and guiding them in data engineering best practices and project work.

Who We're Looking For:

• Programming Skills (Key Requirement)
  Strong programming skills in Python (e.g. pandas, PySpark, SQLAlchemy, airflow-like tools). Ability to write clean, maintainable, and testable code is essential. Experience with other programming languages is a plus.
• Demonstrated hands-on experience with building data pipelines, ideally using Spark (PySpark) or similar distributed processing frameworks.
• Designing and implementing ETL/ELT workflows.
• Working with large datasets and complex data transformations.
• Database Expertise: Proficiency in SQL databases (designing schemas, writing complex queries, optimization). 
• Cloud & Big Data (Nice to Have / Advantage): Experience with cloud data platforms (preferably Azure: Synapse, Databricks, Data Factory, Azure SQL, Data Lake) or similar services on AWS/GCP.
• Professional Background: At least 2 years of relevant professional experience in data engineering, BI engineering, or similar data-focused roles.
• Analytical Thinking: Strong analytical mindset with the ability to understand complex data landscapes, debug data issues, and design logical, efficient data flows.
• Language Skills: English at B2 level or higher.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

We are looking for a Data / Analytics Engineer to join an ongoing initiative focused on building a scalable, AI-driven data platform for product analytics.
This is a new role within an existing analytics team, where you’ll help architect and build the core data layer that will enable self-service analytics across the company. The role combines hands-on data engineering with forward-looking AI automation initiatives.
 

Client/Project: is a global DevOps company.
The project focuses on building a Gold data layer that enables product and business stakeholders to access ready-to-use, reliable datasets without relying on ad-hoc requests.
It’s a complex and high-impact domain, where:

• you will design and build a scalable data model from multiple sources (Snowplow, FullStory, internal systems)
• the team is transitioning to an AI-first development approach (Cloud Code, Codeium - no manual SQL writing mindset)
• AI agents are a core part of the vision (automating data transformations and schema evolution)
• the work has a direct impact on decision-making across a ~600-person product organization

Cooperation: full-time, short-term (6 months with the high possibility of prolongation)
Stage: existing (early stage of data platform transformation - Gold layer not yet built)
Position: new
Timezone requirements: CET ±2h preferred
Location requirements: Remote
Client team: Analytics Guild (up to 9 people)
English: Upper-Intermediate+
 

Requirements:

• 4+ years of experience in Data Engineering / Analytics Engineering (Mid+ or Senior level)
• Strong SQL skills (advanced: window functions, CTEs, joins, performance tuning)
• Hands-on experience with dbt (models, testing, documentation)
• Experience with Amazon Redshift (or strong AWS DWH background)
• Solid understanding of data modeling (dimensional modeling, medallion architecture)
• Experience with Python for data pipelines, integrations, or data quality
• Practical experience using AI coding tools (Copilot, Codeium, Claude, etc.) in daily work
• Experience working with product/event data
• Strong ownership and ability to work autonomously
• Clear communication skills and the ability to work with non-technical stakeholders

Nice to have:

• Experience building or experimenting with AI agents (LangChain, OpenAI API, etc.)
• Familiarity with Snowplow or similar event tracking tools
• Familiarity with FullStory or behavioral analytics tools
• Experience with AWS ecosystem (S3, IAM, etc.)
• Experience with orchestration tools (e.g., Airflow)
• Understanding of BI tools (e.g., Looker) and data consumption patterns

Responsibilities:
This role evolves in two main phases:
Phase 1 (Months 1-4): Building the Gold Layer

• Design and implement Gold-layer data models in dbt
• Transform raw and Silver-layer data into business-ready datasets
• Integrate multiple data sources (Snowplow, FullStory, internal systems)
• Collaborate with the analytics team to translate business needs into reusable models
• Identify and fix inconsistencies in existing data layers
• Establish data quality, monitoring, and observability practices

Phase 2 (Months 4-6+): Automation & AI

• Design and build AI agents for automating data workflows
• Develop systems that detect new incoming events and suggest schema placement
• Automate maintenance of the Gold layer
• Explore and implement AI-driven approaches for data transformations

Ownership areas:

• Gold data layer architecture
• Data quality and reliability
• AI-driven automation of data workflows
• Collaboration with analytics stakeholders
• Long-term scalability of the data platform

Benefits from 8allocate:

• Team & Culture: Team events, offsites, and a culture that keeps people connected.
• Learning & Development: Budget for courses, certifications, and conferences.
• Wellbeing: Flexible support in line with company policy, with options to support your physical and mental well-being (sport, mental health, or medical insurance).
• Rest & Recovery: Paid vacation and sick leave.

We are an innovative AI tech lab building next-generation infrastructure for fully autonomous AI systems. We are currently scaling two core bleeding-edge products:
 

1. An Autonomous Agent Framework: A highly autonomous, "configure-once, forget-forever" agent platform that runs complex workflows, manages its own skills, self-corrects outputs, and operates without traditional approval loops or babysitting.
2. An Intelligence Engine: A massive-scale simulation platform capable of spawning hundreds of grounded AI agents within minutes to simulate real-world behavior, interact across social platforms (Twitter, Reddit), trade on prediction markets, and generate comprehensive counterfactual analysis reports.
    

We are looking for a Senior Backend Developer who is passionate about LLMs, multi-agent orchestrations, graph databases, and building autonomous workflows that operate seamlessly 24/7.
 

Core Responsibilities

• Architect Agent Lifecycles: Design, extend, and optimize the backend core responsible for autonomous agent task execution, state management, and memory retention.
• Scale Swarm Simulations: Improve the performance of multi-agent simulation environments, ensuring concurrent execution of hundreds of agents making API calls, processing text, and updating states in real time.
• Expand the Skills Library: Develop and integrate new "skills" and MCP (Model Context Protocol) tools for agents (e.g., automated code/PR reviews, web searching, live market monitoring, API integrations).
• Self-Healing & Quality Loops: Enhance automated fallback mechanisms, error handling, and self-patching algorithms where AI models evaluate their own outputs and fix failing tasks without human intervention.
• Data & Graph Modeling: Optimize data storage, retrieval, and relational modeling for agent memories, social graphs, and prediction market consensus.

Technical Requirements & Stack

• Languages: Deep proficiency in Python and Node.js/TypeScript (strong backend fundamentals are non-negotiable).
• AI & LLM Integration: Practical experience working with LLM APIs (OpenAI, Anthropic Claude, Ollama) and vector embeddings. Understanding of prompt chaining and structured outputs.
• Databases: Solid experience with Graph Databases (e.g., Neo4j) as well as relational or NoSQL solutions.
• Automation & CI/CD: Strong knowledge of GitHub Actions (used as a runtime framework), workflow dispatches, and containerization (Docker).
• Integrations: Experience building and consuming webhooks, REST APIs, and integrating with third-party platforms (Discord, Slack, Twitter/X, Reddit, or financial data feeds).
• Architecture: Familiarity with event-driven architectures, parallel/sequential task processing, and file-based state logging (Markdown/JSON).

Nice to Have

• Experience or strong interest in Web3, DeFi, and Prediction Markets (Polymarket, Base network ecosystem, tokenomics).
• Open-source contributions or a history of building custom AI tools/bots.
• Familiarity with local LLM deployment and inference optimization.

What We Offer

• 100% Remote & Flexible: Work from anywhere with asynchronous-friendly communication.
• Cutting-Edge Tech: No legacy enterprise maintenance. You will be shipping code to production for autonomous systems from day one.
• High Autonomy: Just like our agents, we value builders who don’t need micro-management and can own features end-to-end.
• 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.

Founded in 1999, the company has a premium listing on the Main Market of the London Stock Exchange and is focused on regulated and regulating markets across its B2B business. By leveraging its proprietary technology, Playtech delivers innovative products and services to ensure a safe, engaging and entertaining gaming experience. 

As the gaming industry's leading technology company, it combines business intelligence-driven software, services, content, and platform technology to drive excellence and innovation across the sector. Read more about who we are and what we do here: www.playtechpeople.com and www.playtech.com
 
Here at Playtech, we genuinely believe that people are our biggest asset. Diverse thoughts, experiences, and individual characteristics enrich our work environment and lead to better business decisions. Embracing differences and maintaining transparency in our processes is the core of Playtech's overall commitment to responsible business practices. 

Ready to level up your career? 

Playtech’s Game team is on the lookout for a diligent, proactive, and detail‑oriented Business Analyst with strong analytical and system thinking skills

Job Description

Your influential mission. You will…

• Translate high-level business solutions into technical specifications
• Analyze requirements, facilitate requirements related meetings
• Create documentation for existing solutions and features
• Support other activities of the development team across the full software development cycle
• Backlog management
• Work with technical documentation
• Perform solution validation

Qualifications

Components for success. You…

• Should have 3+ years of experience in system or business analysis
• Possess profound expertise in business and system analysis of complex software systems
• Demonstrate strong analytical and system thinking skills
• Have good communication skills
• Aim for an Upper-Intermediate level in English (both written and spoken)
• Worked with multiple corporate stakeholders via remote communication channels
• Show strong facilitation skills
• Understand web protocols, messaging protocols and web data formats: HTTP, WS, JSON, XML etc.
• Gain practical experience with Browser DevTools
• Worked with wireframes and diagrams (sequence and activity)

You'll get extra points for…

• Experience working with multiple teams in parallel
• Background in gaming, casino, or gambling industries

Thrive in a culture that values…

• Collaboration across diverse, international teams
• Innovation and continuous improvement
• Transparency and accountability
• Passion for delivering high-quality products to global clients

Additional Information

CASINO UNIT

Casino products are the flagship of Playtech’s products, offering an industry-leading selection of online games together with a state-of-the-art platform for seamless integration with our business customers’ websites. We ensure to deliver a thrilling web experience content library that includes a slot, table/card, fixed odds games, and more. Some of the movie and entertainment brands we have collaborated with, include DC, MGM, and NBC Universal. Casino Unit is represented in the following locations: Estonia, Bulgaria, and Ukraine and includes around 300 great employees in total, who build the most extensive games portfolio across the industry.

Playtech is an equal opportunities employer. Our mission is to welcome everyone and create inclusive teams. We celebrate differences and encourage everyone to join us and be themselves at work. 

Important: after confirming your application on this platform, you’ll receive an email with the next step: completing your application on our internal site, LaunchPod. So keep an eye on your inbox and don’t miss this step — without it, the process can’t move forward.

Why join us

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! :)

About the role

We are looking for a DevOps Engineer to design, build, and operate containerized and serverless workloads on AWS, working across ECS, EKS, Lambda, and Step Functions. You will implement infrastructure as code with Terraform and Helm, establish and maintain CI/CD pipelines, and provide technical mentorship while resolving complex infrastructure challenges. The role spans both greenfield prototyping and support of existing production systems in an Agile environment.

What you will do

• Support and improve existing functionality;
• Prototype new solutions;
• Provide technical mentorship to your colleagues;
• Analyze and resolve intricate technical challenges;
• Design, build, and operate containerized and serverless workloads on AWS;
• Implement Infrastructure as Code and repeatable deployments for Kubernetes and serverless stacks;

• Establish and maintain CI/CD pipelines, monitoring, and operational runbooks.

   

Must haves

• 3+ years of experience;
• Hands-on AWS experience building and operating workloads with ECS (Fargate/EC2) for container orchestration;
• Hands-on AWS experience with EKS (Kubernetes), including core K8s primitives and cluster operations;
• Hands-on AWS Lambda experience for serverless compute;
• Hands-on experience with AWS Step Functions for workflow/orchestration;
• Infrastructure as Code with Terraform, including writing reusable modules, workspaces, and state management;
• Experience with Helm, including authoring and maintaining charts for Kubernetes deployments;
• Proficient in using software collaboration tools such as JIRA;
• Working knowledge of various databases, including MySQL, MSSQL, Oracle, and Postgres;
• Working knowledge of various operating systems, including Windows and Linux;
• Proficient in version control software such as Git;
• Basic understanding of Agile Scrum methodologies;
• Excellent oral and written communication skills;
• Ability to work independently as well as within a collaborative environment;
• Upper-intermediate English level.

Nice to haves

• Working knowledge of developing web-based client interfaces using React.js + TS;
• Working knowledge of Java and Spring.

The benefits of joining us

• Professional growth

Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps

• Competitive compensation

We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities

• A selection of exciting projects

Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands

• Flextime

Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

Meet Our Recruitment Process

Asynchronous stage – An automated, self-paced track that helps us move faster and give you quicker feedback:

• Short online form to confirm basic requirements
• 30–60 minute skills assessment via Codility – a platform founded in Poland that helps us provide quicker feedback and streamline this stage of the process.
• 5-minute introduction video

Synchronous stage – Live interviews

• Technical interview with our engineering team (scheduled at your convenience)
• Final interview with your future teammates

If it’s a match — you’ll get an offer!

MTicket is building a production AI Runtime on top of a real ticketing and live events business.
We work with data from ticket sales, payments, scanners, live events, venues, artists, marketing, finance, and operations. Before AI agents can automate workflows and support business decisions, this data must be clean, normalized, structured, monitored, and AI-ready.
We are looking for a Senior Data Engineer / Data Architect who can design and own the unified data layer for MTicket AI OS.

What You’ll Do

• Design a unified data model for ticketing, events, payments, scans, artists, venues, marketing, and finance
• Build ETL / ELT pipelines from core systems and external APIs
• Normalize sales, tickets, refunds, scans, payments, event history, and transaction logs
• Create analytics-ready and AI-ready datasets for internal teams and AI agents
• Implement data quality checks, freshness tracking, monitoring, and alerting
• Debug production data issues using logs, metrics, and system behavior
• Work closely with the AI / Python team on datasets for AI agents

Tech Stack

Must Have

• Strong SQL and data modeling skills
• Production experience with PostgreSQL
• ETL / ELT pipeline engineering
• Data warehouse / data layer design experience
• Event-driven or streaming data experience
• API integrations as data sources
• Data quality checks in production
• Pipeline monitoring, alerting, and observability
• Strong debugging skills in production environments

Strong Plus

• Python for data pipelines
• dbt, Airflow, Dagster, or Prefect
• Kafka, SQS, RabbitMQ, or other queues
• ClickHouse, BigQuery, Snowflake, or Redshift
• pgvector, embeddings, or AI-related data infrastructure
• Experience with ticketing, e-commerce, fintech, marketplaces, CRM, or payments data

First 90 Days

• Audit existing MTicket data sources
• Design the first version of the unified data model
• Build initial ETL pipelines for sales, events, and payments
• Add data quality checks and validation rules
• Set up monitoring, alerting, and freshness tracking
• Deliver the first AI-ready datasets to the Python / AI team

Format

• Remote
• Flexible timezone
• Full-time, part-time, or consulting format
• High ownership
• Architect-level impact
• Ukrainian or Russian language is important for collaboration
• English for technical documentation is a plus

We’re Applyft — an IT product company which creates value-driven mobile and web apps. Our journey began with the Geozilla family locator product, but now our portfolio consists of 8 apps in Family Safety, Parental Control and AI.

In 2025, we launched a new direction — Finestro, an AI-powered educational app that helps people master AI, improve their financial well-being, and unlock new growth opportunities.

Today, Finestro is powered by a team of 30+ talented professionals, and we continue to grow. We’re looking for people who want to contribute to building an innovative EdTech product that truly impacts users’ lives.

Now we are looking for a Middle/Senior Marketing Data Analyst to support analytics across user acquisition and marketing performance.

About you:

• Strong SQL skills (BigQuery or similar).
• Solid understanding of marketing metrics: CAC, LTV, ROI/ROMI, payback.
• Experience working with large-scale datasets (transaction-level, event-level).
• Strong analytical thinking and ability to translate data into business insights.
• Experience with BI tools (Tableau/Looker Studio).
• Ability to work with attribution data and marketing sources (Meta, Google Ads, etc.).
•  

What you’ll do:

• Analyze marketing performance across different channels (Meta, Google, etc.).
• Work with core datasets (spend, revenue, LTV, attribution).
• Transform marketing data into clear, actionable decisions for scaling.
• Analyze traffic quality, channel performance, and unit economics.
• Identify growth opportunities and initiate data-driven improvements.
• Work with LTV forecasts, payback periods, and scaling scenarios.
•  

Nice to have:

• Experience with subscription-based products.
• Experience with payment data (Stripe, PayPal, refunds, chargebacks).
• Python skills.
• Familiarity with ML models and data science.
• Experience with Amplitude, AppsFlyer.

Overview

We’re hiring a Junior Machine Learning Engineer to work with our AI/ML Team building and scaling intelligent ML systems powering personalized digital experiences across mobile apps and connected platforms.

You’ll work across ML, data infrastructure, and backend systems to bring production-ready AI features into real-world products. This is a hands-on role for someone experienced in deploying scalable ML solutions and optimizing them in live environments.

Responsibilities

• Design, train, and deploy ML models for personalization, recommendations, and computer vision;
• Build scalable batch and real-time data pipelines;
• Integrate ML models into production applications and APIs;
• Improve model monitoring, retraining, and inference performance;
• Collaborate with product, engineering, and data teams on ML-driven features;

• Contribute to cloud-native ML platform architecture and MLOps practices.

   

Requirements

• 2 years of experience in Machine Learning Engineering or Applied AI;
• Experience with recommendation systems, personalization, or computer vision;
• Solid Python skills and hands-on experience with TensorFlow, PyTorch, and scikit-learn;
• Proven experience deploying and maintaining ML systems in production;
• Experience with MLOps and data tools such as MLflow, Airflow, Kafka, BigQuery, or dbt;
• Basic Familiarity with FastAPI, TensorFlow Serving, TorchServe, or ONNX;
• Basic Experience with AWS, GCP, or Azure, including Docker/Kubernetes environments;
• Strong collaboration and communication skills.

Bonus: Experience with edge AI, mobile ML, or image/video processing systems.

Langate is an award-winning provider of web development services in 3 main categories: business, healthcare, and education. At Langate, we're passionate about crafting digital solutions that make a real impact. We take immense pride in our strong collaboration with the U.S.  We're here to shape the future of technology, one milestone at a time. 
In addition to technical expertise, we value strong communication, autonomy, and a high level of business orientation. This role requires close collaboration with stakeholders, proactive requirement discovery, and the ability to work effectively in a fast-changing environment without waiting for fully documented inputs. 
To thrive in this role, we’re seeking candidates with 2–3+ years of commercial engineering experience, hands-on experience building AI agent solutions, strong Python and/or TypeScript fundamentals, and the ability to design custom tool-using agent loops from scratch. Experience with agent frameworks, evaluation systems, and observability tooling will be a strong advantage. 

About the project : The project is focused on building production-grade AI agent capabilities for the U.S. healthcare domain. The engineer will work on agentic product features, legacy-system integrations, and supporting components such as scrapers and tool layers, helping automate complex workflows in an environment with significant real-world business impact. 

Requirements:  

• 2–3+ years of commercial engineering experience
• Ability to build a tool-using agent loop from scratch, including tool calling, structured outputs, stop reasons, parallel tool use, and error recovery
• Strong understanding of context engineering, including what to write, select, compress, and isolate
• Hands-on experience with modern agent frameworks or SDKs such as LangGraph, Claude Agent SDK, OpenAI Agents SDK, or Pydantic AI
• Working knowledge of Model Context Protocol (MCP)
• Experience building or extending evaluation harnesses, solid Python and/or TypeScript skills, and Upper-Intermediate English 

Responsibilities: 

• Design and implement agentic features end-to-end, from prototype to production.
• Build and maintain agent loops, tool layers, context management, persistence, sub-agent orchestration, observability, and safety hooks.
• Define quality standards for agent performance by creating golden datasets, writing evaluations, and setting up regression checks.
• Instrument agents with proper tracing and telemetry, and investigate production behavior using real execution traces.
• Work directly with client stakeholders to elicit and refine requirements, translate them into technical scope, and align on expected outcomes.
• Make pragmatic build-versus-import decisions when selecting frameworks, tools, and external components.
• Participate in architecture discussions and code reviews, contributing to scalable and production-ready engineering decisions.
• Move between projects and priorities as needed, taking ownership of delivery in a fast-changing environment with a high degree of autonomy. 

Schedule: 5/2, 8-hour working day (40 hr per week), flexible schedule. 

Hiring process: HR interview + tech specialists   

At Geniusee, we help businesses thrive through technology partnerships and strengthen the engineering community by sharing knowledge and creating opportunities 🙌
 

We live by our values: Continuous Growth, Team Synergy, Taking Responsibility, Conscious Openness, and Result-Driven Mindset. Here, you’ll find a safe, inclusive, and supportive environment where your voice is heard, and feedback is welcome 🤗
 

Whether you want to work from home or from our offices in Kyiv / Lviv / Warsaw with stable electricity and Wi-Fi, we’ve got you covered.

Join us and make an impact 💜

About the project: Healthcare

Requirements:

• 3+ years in design, development, and maintenance of backend services primarily using Python;
• Collaborate on system architecture decisions and validate technical approaches;
• Contribute to AI/LLM-related workflows and evaluation processes;
• Support integration-heavy insurance and dental management workflows;
• Work within a rapidly evolving startup environment with shifting priorities;
• Participate in deployment and infrastructure discussions around AWS or Azure and Docker;
• Maintain high responsiveness and close collaboration with the internal team;
• Help retain and build domain-specific business context over long-term engagement.
   

Responsibilities:

• Design, develop, and maintain backend services primarily using Python;
• Collaborate on system architecture decisions and validate technical approaches;
• Contribute to AI/LLM-related workflows and evaluation processes
• Support integration-heavy insurance and dental management workflows;
• Work within a rapidly evolving startup environment with shifting priorities;
• Participate in deployment and infrastructure discussions around Azure and Docker;
• Maintain high responsiveness and close collaboration with the internal team;

Help retain and build domain-specific business context over long-term engagement.

What will you get:

Career growth & projects
● Competitive salary based on your skills and experience, and a benefits package.
● Regular performance appraisals to support your career development.
● Professional development support: online courses, certifications, and study compensation (including English courses).
● A modern tech stack across challenging, long-term projects.

Health & well-being
● Paid vacation (18 working days) and sick leave (15 days).
● VIP medical insurance or sports coverage.

Work environment & flexibility
● Remote work from anywhere in the world or in one of our offices in Kyiv, Lviv, or Warsaw.
● Coworking compensation.
● Necessary equipment to perform your work.

Culture & community
● A collaborative and open culture where contributions are recognized.
● Regular corporate online & offline activities.
● Geniusee Charity Fund, making a difference beyond tech.