Tasks:
● Architect & Develop – Build robust back-end components for trading platform using modern C++
● Scale Systems – Design high-performance server solutions that handle massive trading volumes
● Collaborate – Work with cross-functional teams to deliver new features and optimize existing systems
● Innovate – Drive technical decisions and contribute to the evolution of our trading technology stack
● Document – Maintain comprehensive technical documentation for server-side components

Requirements:
● Strong passion for writing clean, efficient C++ code
● Experience working with existing codebases and legacy systems
● Solid understanding of client-server architecture and network protocols
● Proficiency in algorithms, data structures, and performance optimization
● Hands-on experience with multi-threaded programming and concurrency
● Git version control expertise

A plus would be:
● MongoDB database experience
● Kubernetes container orchestration
● AWS cloud platform knowledge
● C# and C++/CLI development background
● Previous experience in fintech or trading systems

Extra information that could be important:
● Professional development and training opportunities
● Exciting projects with prestigious clients
● Timezone: EEST +/- 2
● Long-term collaboration
● You can work from from all over the world

Responsibilities
Perform functional and non-functional testing of client applications (web + mobile) and server-side systems.
Create and maintain test cases and checklists.
Identify, document, and track defects; reproduce and analyze complex bugs.
Analyze logs and data to determine the root cause of defects.
Collaborate with the team to improve testing processes and overall product quality.
Conduct User Acceptance Testing (UAT) and participate in release decision-making.
Participate in QA activities at all stages of development: from requirements analysis and clarification to post-release verification.
Evaluate release results and propose improvements to enhance software stability and quality.
Requirements
5+ years of experience as a Software Tester or Quality Assurance Engineer.
Ability to analyze requirements and design comprehensive test cases and test scenarios.
Excellent knowledge of software testing methodologies and experience applying them in practice.
Strong hands-on experience testing web, mobile, and server applications.
Knowledge of REST API and experience using API testing tools (Postman, Swagger, or similar).
Experience with Jira, Confluence, TestRail, and log analysis tools.
Strong debugging skills and a deep understanding of defect nature and lifecycle.
Understanding of the software development lifecycle and experience working with agile methodologies (Scrum, Kanban).
Nice to Have
Bachelor’s degree in Information Systems, Mathematics, or a related field.
Understanding of OOP principles.
Knowledge of trading systems and how they operate across various financial markets.

You will:

Own and evolve core backend services that power our campaign engine, matching logic, and creator/brand workflows.

Work closely with product and data/ML teams to ship LangGraph-powered “agentic” workflows – for example:

creator matching,

AI-generated briefs,

AI pricing/rate suggestions,

campaign health monitoring.

Help us keep the platform fast and reliable as we scale across markets and run more campaigns in parallel.

Remote-first, async-friendly, but with enough overlap in EU time for real collaboration.

What you’ll do

Design, implement and maintain Django-based backend services for our brand and creator dashboards.

Build robust APIs (Django Ninja / FastAPI) consumed by our web and mobile clients.

Implement background processing with Celery, orchestrating workloads like:

syncing with Snapchat / Amazon Ads APIs,

running batch evaluations / scoring creators,

heavy AI / LangGraph workflows off the request path.

Use Django ORM efficiently to eliminate N+1 queries and keep the database happy.

Work with Redis and RabbitMQ for caching, queues, and pub/sub patterns.

Contribute to LangGraph-based flows (with LLMs and tools) that automate campaign operations and internal agentic assistants.

Collaborate with product, data, and ops to turn fuzzy “how do we make this easier for brands/creators?” into clean, well-structured backend solutions.

Own quality end-to-end: tests, observability, performance and reliability.

Must-have (Required)

Strong Python: idiomatic, clean, testable code; comfortable with async where needed.

Strong Django: models, ORM, migrations, middlewares; experience with real production apps.

Hands-on Celery: designing task architectures, avoiding deadlocks, handling retries & failures.

Solid understanding of relational databases and SQL (indexes, joins, transactions).

Experience building and maintaining production APIs.

Comfortable working remote in EU time zones, communicating clearly in English.

Very good to have

Product thinking, especially in adtech / marketing / attribution: you can talk about trade-offs, not just endpoints.

Experience with Django Ninja and/or FastAPI for high-performance APIs.

Practical experience with LangGraph (or similar tools) to orchestrate LLM workflows, tools, and memory.

Good understanding of Redis (caching, rate limiting, locking) and RabbitMQ (queues, routing, durable messaging).

Experience integrating with ads / analytics APIs (Snapchat Ads, Amazon Ads, Meta, Google Ads, etc.).

 What you’ll do (outcomes) 

● Ship working systems: Design, build, and maintain small-to-medium services, scripts, and workflows that solve concrete team needs with clear SLAs. 

● Automate everything: Orchestrate cross‑app workflows (n8n/Make/Zapier/Custom) across CRM, sheets, Meta/Instagram APIs, email, SMS/WhatsApp, Slack, and web backends. 

● Agentic apps: Build LangChain/LangGraph‑based agents and tools for data enrichment, routing, triage, and outreach; implement evaluation, guardrails, retries, and cost controls. 

● Scrape—responsibly: Use headless browsers and official APIs to extract data, respecting ToS/robots/legal; implement rotating proxies, backoff, and anti‑bot patterns when appropriate. 

● Connect data: Stand up light ETL/ELT to Postgres/BigQuery; build RAG/search over internal docs and metadata; keep data fresh and observable. 

● Reliability & telemetry: Add logging, metrics, alerts, and dashboards; own on‑call for the automations you ship (during business hours). 

● Documentation & handoff: Write runbooks, diagrams, and clear READMEs so others can extend what you build. 

Sample projects you might own 

● Instagram lead intake → compliant DM triage: Pull creator profiles, enrich, score, then route to a Messenger/IG inbox with auto‑replies and human‑handoff. Track deliverability and outcomes. 

● AI outreach bot: Given a segment, generate personalized first‑touch + follow‑ups, dedupe against CRM, schedule messages, and log replies; A/B evaluate prompts and templates. 

● Scrape → Clean → Sync: Headless browser job (Playwright) to capture public business data, normalize, and sync to Postgres/Sheets with change detection and alerts. 

● RAG for Sales/Success: Vectorize pitch docs, briefs, and prior wins; build a chat tool that drafts proposals and answers objections with citations. 

Must‑have qualifications 

● 4–7+ years building production automations, internal tools, or platform glue (startups or product teams). 

● Strong Python and TypeScript/Node; you can ship a CLI today and a small service tomorrow. 

● Real experience with LLM apps (tool use/function calling, evals, prompt versioning, cost/perf tuning). 

● Confident with APIs/webhooks, auth (OAuth), rate‑limits, pagination, retries, and idempotency. 

● Hands‑on with headless browsers and public‑data scraping patterns; pragmatic about ToS/legal. 

● Comfortable with databases & SQL, queues, and basic cloud deploys; you instrument what you ship. 

● Excellent product sense and communication; you clarify the job to be done and bias to action. 

Nice to have 

● WhatsApp Business API, Meta Graph (IG), Slack/Telegram bots. 

● Vector search/RAG in production; knowledge graphs (Neo4j). 

● Data plumbing: Airbyte/dbt/Great Expectations. 

• Pipeline Development: Design, develop, and maintain scalable data pipelines to ingest, process, and store large volumes of structured and unstructured data.
• Infrastructure Management: Build and optimize data warehouses and data lakes using cloud-based technologies.
• Cross-Functional Collaboration: Partner with AI/ML specialists to ensure high-quality data is available for model training and deployment.
• Code Quality: Write clean, maintainable, and efficient code for data processing tasks following industry best practices.
• System Optimization: Identify and resolve performance bottlenecks in data workflows and database queries.
• Architecture: Contribute to the overall data architecture and technical direction of the platform.
• Data Integrity: Implement monitoring and validation checks to ensure data accuracy, security, and reliability.

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience: 3+ years of professional experience in data engineering or a related backend role.
• Languages: Strong proficiency in Python, SQL.
• Cloud & Devops: Hands-on experience with cloud platforms (e.g., AWS) and containerization (e.g., Docker, Kubernetes).
• Big Data Tools: Experience with data tools such as BigTable, Airflow, Looker, etc.
• Soft Skills: Strong problem-solving skills and the ability to work in a fast-paced, collaborative startup environment.

• Experience with NoSQL databases and vector databases for AI applications.
• Familiarity with data visualization tools and analytics frameworks.
• Knowledge of CI/CD practices specifically for data engineering (DataOps).

Requirements 

• 5+ years of experience in quality engineering, with significant time spent in data/analytics environments 

• Strong SQL skills and comfort writing complex validation queries 

• Python proficiency for test automation and data analysis 

• Experience testing data pipelines and analytical datasets 

• Working knowledge of AWS data ecosystems, dbt, and Airflow or similar orchestration tools 

• Ability to reason about business logic, metrics definitions, and data lineage 

• Strong analytical and problem-solving skills, including statistical analysis fundamentals 

• Excellent communication skills to translate technical issues into business impact 

• Experience operating in fast-paced environments where priorities shift 

• Proven ability to speak up when data quality concerns arise and advocate for the customer experience 

• Able to take ownership of problems and drive them to resolution without constant direction 

Preferred 

• Experience with real-time and streaming data validation 

• Exposure to data observability tools (Monte Carlo, Great Expectations, or similar) 

• Test management tool experience (Qase, TestRail) 

• Experience in fintech, payments, or SaaS analytics environments 

• Background in performance analysis of data pipelines (throughput, latency, resource utilization) 

• Familiarity with Prometheus, Grafana, or similar monitoring tools 

• Hands-on experience applying AI/ML testing and validation practices in data warehouse and analytics environments, including dataset/feature validation, automated data quality checks, training/serving consistency testing, and monitoring for anomalies or data/model drift across pipelines. 

Requirements 

● 3–7 years of experience in software quality engineering, preferably in SaaS environments. 

● Experience testing AI/ML-powered features, conversational interfaces, or LLM-based products. 

● Strong proficiency in API testing methodologies (REST, GraphQL, streaming APIs). 

● Advanced SQL skills for data validation and pipeline testing. 

● Strong demonstrated proficiency in Linux distributions and CLI-based testing, including log file analysis and other troubleshooting tasks. 

● Experience with AWS or other major cloud platforms. 

● Basic Python/Shell (or similar) scripting knowledge with ability to edit existing scripts and create new automation. 

● Familiarity with test management tools such as TestRail; experience with Qase is a plus. 

● Demonstrated experience leveraging Version Control Systems with a focus on GitHub. 

● Experience with testing tools: Jira, DataDog. 

● Strong understanding of Agile/Scrum methodologies. 

● Proven track record of mentoring junior engineers and contributing to process improvements. 

● Excellent analytical and problem-solving abilities. 

● Strong communication skills with ability to present to both technical and non-technical stakeholders. 

● Be vocal about quality concerns and testing impediments. 

Preferred Qualifications 

● Experience with prompt engineering and adversarial prompt testing techniques. 

● Experience testing SaaS products in regulated industries (such as PCI-compliant environments). 

● Familiarity with AI observability platforms and LLM tracing tools. 

● Basic understanding of containerization, Kubernetes, and CI/CD pipelines (Jenkins, CircleCI). 

● Experience with microservices architectures and distributed systems testing. 

● Knowledge of AI safety and responsible AI testing practices. 

● Certifications such as ISTQB or CSTE. 

• Design and implement scalable applications using modern web application frameworks (e.g., Rails, React, Node, NextJS).
• Collaborate with product teams to assess trade-offs, identify risks, and align improvements with business objectives.
• Modernize web applications to enhance user experience, improve performance, and ensure scalability.
• Work closely with UX teams to design and ship web applications with a focus on usability.
• Support software deployments by debugging, troubleshooting, and coordinating with DevOps and QA engineers.

• BS in Computer Science or related field, or equivalent professional experience.
• 7+ years of experience designing, implementing, and debugging large-scale, cloud-based solutions.
• Extensive experience building production-grade React applications, including developing reusable components, managing complex state, and optimizing front-end performance.
• Professional experience with Ruby on Rails, with the ability to develop and maintain APIs and other backend functionality.
• Experience with Lean product development and Agile frameworks (e.g., Scrum, Kanban).
• Strong understanding of SOLID design principles and software design patterns.
• Proficiency in SQL and experience working with relational databases such as PostgreSQL or MySQL.
• Excellent teamwork, documentation, and communication skills.
• Demonstrated experience leveraging AI tools and technologies to improve workflows, enhance decision-making, or drive innovation.

• Experience with cloud platforms (e.g., AWS, Google Cloud Platform).
• Experience with Rails (or equivalent), NodeJS and NextJS.
• Experience with React, Bootstrap and other frontend technologies.
• Experience building scalable Software as a Service (SaaS) applications.

• Develop and optimize ETL processes
• Integrate data sources across a broad product portfolio to provide stakeholders access to key
• information they need to excel at their job
• Work in close collaboration with operations, product management, data scientists, and
• analysts to clarify requirements and translate them into robust, scalable, operable data
• architecture
• Define and model data architecture for the data warehouse

• Experienced data engineer with minimum 7+ years working in a data/analytics function
• Strong skills in SQL, Python, AWS (specifically Redshift is required), DBT, Airflow, Kafka
• Knowledgeable of how real-time streaming works using technologies such as Kafka
• Business domain knowledge in Fintech, finance, sales, marketing, and Go To Market areas
• Proven experience working in data teams/building out data environments