Jobs

A-Players is an AI-powered product company running four fast-growing business units (AI chats, mental health & mindfulness, self-learning) with a distributed team of 70 people across 15 countries. 

We're looking for a Head of HR to build a scalable HR function that acts as a true partner to founders and management - a systematic foundation with the energy to actually execute. This is a hands-on leadership role for someone who owns outcomes end-to-end, partners directly with the C-level, and is comfortable operating in permanent startup mode.

Responsibilities:

• Own HR strategy and the people roadmap
• Rebuild and run company-wide performance management
• Design and manage compensation & benefits, including salary architecture, benchmarking and bands
• Drive retention, succession planning and internal talent development
• Handle employee relations and difficult people decisions
• Own onboarding and offboarding processes
• Build people analytics and monitor organizational health
• Lead internal communications and culture initiatives
• Build, lead and grow the HR team
• Partner closely with founders and management as a trusted business advisor
• Coordinate with the (separate) Recruitment function on shared touchpoints: salary bands, pre-onboarding/onboarding handover, internal moves, and workforce planning.

Note: recruitment/talent acquisition and office administration are explicitly out of scope for this role - they are owned by separate functions.

Requirements:

Must have:

• Track record leading HR in a product tech company of 50-200 people, ideally through fast growth or new business unit launches
• Proven experience building HR systems from scratch (not just operating within existing infrastructure)
• Demonstrated partnering with founders/C-level where your input directly influenced business decisions
• Experience developing managers, including first-time/inexperienced ones
• Hands-on compensation & benefits expertise: salary architecture, benchmarking, bands, promotion frameworks, comp review cycles
• Real people analytics experience, with concrete examples of data-driven decisions
• Strong business and numbers literacy: unit economics, cost of people, impact of people decisions on P&L
• Strong ownership from strategy through execution, with the ability to manage stakeholders and dependencies independently
• The maturity and courage to challenge leadership with data-backed alternatives
• Strong stakeholder management and ability to influence without formal authority
• A solution-oriented mindset - focused on how to make things work despite constraints
• Practical daily use of AI in your own workflow.

Nice to have:

• Experience with distributed teams, ideally Cyprus- or EU-based
• Experience managing multiple product units at different maturity stages within one company.

What we offer:

• A seat at the table: direct, ongoing partnership with founders and the leadership team, with real influence over key business decisions
• Full ownership of the HR function - you build the system, not just execute someone else's playbook
• A fast-growing, AI-first product company (70 people, doubling year-over-year) with room to shape culture and process from the ground up
• A distributed, international team spanning 15 countries, with an on-site hub in Limassol, Cyprus
• Relocation support for candidates moving to Cyprus
• A culture that genuinely lives its values (Think AI-first, Drive to Results, Embrace R&D, Raise the Bar, Lift Others Up) - reflected in strong internal metrics: 16.6 months average tenure and 93% employee recommendation rate.
   

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product:

Our client operates a cloud-based platform dedicated to corporate ground transportation management, addressing a multi-billion-dollar market. The solution aggregates multiple transportation providers—such as corporate fleets, ride-hailing services, taxi operators, and limousine networks—into a unified system that helps businesses streamline operations and reduce spend. It serves a significant share of the largest companies worldwide and handles high volumes of transactions and data across diverse geographies. The platform’s core challenges include integrating heterogeneous external services, maintaining reliability under high-load conditions, implementing advanced business logic for scheduling and pooling, and providing accurate cost control and reporting. Strong backend engineering is critical to scaling global coverage, ensuring performance, and delivering a seamless user experience.

About the Role:

You will join a cross-functional development team responsible for core backend services that directly impact end users. The role offers full ownership of feature delivery—from reviewing product requirements and defining technical designs alongside architects and product managers, through to coding, testing, deployment, and monitoring in production. You will serve as first-line support for your services, proactively identify and address reliability and performance issues, and collaborate with other teams to ensure end-to-end system integrity. This position demands technical leadership, a hands-on approach to system architecture, and the ability to influence both engineering and product decisions. You will work remotely with periodic team gatherings and receive the tools and environment needed to deliver tangible business impact in a fast-paced, agile setting.

Key Responsibilities:

• Lead end-to-end development of backend microservices, including design, implementation, deployment, and production monitoring.

• Translate product requirements into scalable technical designs, data models, and RESTful APIs.

• Integrate with external transportation providers and internal systems to enable reliable, real-time workflows.

• Analyze and optimize system performance and database queries under high-load scenarios.

• Propose and implement architectural improvements to enhance resilience, scalability, and maintainability.

• Maintain and refactor existing services to improve code quality, test coverage, and observability.

• Collaborate with cross-functional teams and mentor peers on best practices in coding, testing, and operations.

• Participate in agile ceremonies, including backlog grooming and sprint planning, to align deliverables with business priorities.

Required Competence and Skills:

• 5+ years of backend software development experience in Golang (willingness to work with Ruby). 

• Proven experience designing and implementing data-driven applications using relational databases (e.g., PostgreSQL) and NoSQL stores (e.g., Redis).

• Solid understanding of RESTful API design principles and the HTTP protocol.

• Hands-on experience with Agile/Scrum methodologies and iterative delivery.

• Proficiency in writing unit tests and applying automated testing practices.

• Strong English communication skills, both verbal and written.

• Ability to understand complex business domains and translate needs into optimal technical solutions.

• Deep understanding of system architecture, high-load applications, and concurrency principles.

Nice to Have:

• Expertise in performance tuning of relational databases.

• Familiarity with gRPC and Protocol Buffers.

• Prior work on high-load, distributed systems.

• Background in building concurrent applications.

Why Us:

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.

Our Customer:

A global enterprise organization building modern data, analytics, and AI solutions within a Microsoft-first ecosystem. The company focuses on scalable and secure enterprise platforms that support business intelligence and digital transformation.

Your Tasks:

• Define and drive architecture for enterprise Data, Analytics, and AI solutions across multiple initiatives
• Transform business requirements into scalable, secure, and maintainable technical architectures
• Design solution blueprints, integration approaches, and implementation strategies
• Support delivery teams throughout the full solution lifecycle, from discovery and prototyping to production deployment
• Conduct architecture, design, and code reviews to ensure solution quality and alignment with business goals
• Provide hands-on technical leadership and guidance to engineering teams
• Ensure solutions meet requirements for quality, scalability, security, maintainability, operational readiness, and cost efficiency
• Ensure security, governance, and compliance standards are incorporated into solution designs
• Collaborate with business stakeholders, architects, engineering teams, and governance functions to drive successful delivery
• Participate in troubleshooting, risk assessment, estimation, and technical decision-making activities

Required Experience and Skills:

• 15+ years of experience in IT, including 10+ years in Solution Architecture roles focused on enterprise Data, Analytics, and AI platforms
• 10+ years of hands-on experience with Azure-based data solutions, including Azure Data Factory, Databricks, Azure Data Lake, SQL, dimensional modeling, ETL/ELT processes, and data orchestration
• Strong expertise in Power BI architecture, including semantic models, DAX, Power Query, governance, workspace management, performance optimization, and enterprise reporting solutions
• Proven experience delivering end-to-end architecture solutions, including solution design, prototyping, implementation support, technical reviews, and production readiness activities
• Strong knowledge of enterprise security, governance, compliance, and architecture best practices
• Ability to translate complex business challenges into practical and delivery-focused technical solutions
• Experience providing technical leadership in distributed enterprise environments
• Experience working with distributed teams and external partners in enterprise delivery environments
• Strong troubleshooting, analytical, estimation, decision-making, and risk management skills
• Ability to work effectively with enterprise architects, business stakeholders, and cross-functional teams
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field
• Excellent communication skills in English

Would be a Plus:

• Experience with enterprise AI solutions and Microsoft AI services, including Azure OpenAI, Azure AI Search, AI Foundry, Copilot Studio, Semantic Kernel, and Prompt Flow
• Experience with Microsoft Fabric and Power Platform governance practices
• Experience with Azure DevOps, GitHub Enterprise, and CI/CD implementation for Data, Analytics, or AI platforms
• Knowledge of Microsoft security and governance services such as Entra, Purview, and Key Vault
• Experience working in regulated industries, including life sciences, healthcare, or pharmaceuticals
• Microsoft certifications related to Azure, Data, Analytics, Power BI, or AI Architecture
• Experience with Python, data observability, and monitoring solutions

Working conditions

5-day working week, 

8-hour working day;

Remote work.

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

Responsibilities:

- Design, build, and maintain ETL/ELT pipelines on AWS
- Migrate existing data pipelines and workloads from legacy/on-prem systems to AWS
- Develop and optimize data models for data warehouse/data lake (Redshift, S3)
- Build and orchestrate data workflows (Glue, Step Functions, Lambda, EMR)
- Implement data quality checks, validation, and reconciliation processes
- Optimize pipeline performance and manage compute/storage costs
- Ensure data security and access control (IAM, KMS, encryption)
- Monitor and troubleshoot pipeline failures (CloudWatch, logging)
- Collaborate with data analysts, BI developers, and architects on data requirements
- Document data pipelines, architecture, and operational runbooks

Mandatory Skills Description:

- 5+ years of experience
- Hands-on experience building data pipelines on AWS (Glue, EMR, Lambda, Step Functions)
- Strong SQL and experience with data warehousing (Redshift, dimensional modeling)
- Proficiency in Python or Scala for data engineering
- Experience with S3-based data lake architecture (partitioning, cataloging, formats like Parquet)
- Experience migrating data pipelines from on-prem or other cloud platforms
- Understanding of data governance, security, and access control on AWS
- Experience with CI/CD for data pipelines

Nice-to-Have Skills Description:

- AWS certification (Data Analytics Specialty or Data Engineer Associate)
- Experience with streaming data (Kinesis, MSK/Kafka)
- Familiarity with Infrastructure as Code (Terraform/CloudFormation)
- Experience with orchestration tools (Airflow, dbt)
- Experience in financial domain

Languages:

English: C2 Proficient

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

Responsibilities:

-Wave planning — plan migration waves based on system dependencies and priorities
-Complexity assessment — evaluate complexity of each workload/job prior to migration
-Workload analysis — analyze existing batch processes, their dependencies, schedules, and SLAs
-Orchestration migration strategy — design the strategy for migrating from Control-M to AWS Step Functions (job mapping, dependencies, triggers)
-Cutover runbook — develop detailed cutover runbooks (steps, rollback points, success criteria)
-Pod coordination — coordinate across multiple teams/pods involved in the migration
-Release governance — manage release processes, ensuring quality and compliance with standards prior to deployment

Mandatory Skills Description:

- Large-scale migration experience — proven track record on enterprise-scale migration projects
- Wave planning — hands-on experience planning waves in multi-system migrations
- Control-M — deep knowledge of Control-M (jobs, schedules, dependencies, calendars)
- AWS Step Functions — hands-on experience designing and building workflows in Step Functions
- Risk assessment — experience identifying and mitigating risks in migration projects
- Data reconciliation — experience validating data/results post-migration (before/after comparison)
- Release management — experience managing releases in an enterprise environment

Nice-to-Have Skills Description:

- Experience with other orchestration tools (Airflow, AWS Glue Workflows)
- AWS certification (Solutions Architect / DevOps Engineer)
- Knowledge of AWS Lambda, EventBridge (commonly used- alongside Step Functions)
- Experience in financial domain

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

Responsibilities:

- Design, build, and maintain ETL/ELT pipelines on AWS
- Migrate existing data pipelines and workloads from legacy/on-prem systems to AWS
- Develop and optimize data models for data warehouse/data lake (Redshift, S3)
- Build and orchestrate data workflows (Glue, Step Functions, Lambda, EMR)
- Implement data quality checks, validation, and reconciliation processes
- Optimize pipeline performance and manage compute/storage costs
- Ensure data security and access control (IAM, KMS, encryption)
- Monitor and troubleshoot pipeline failures (CloudWatch, logging)
- Collaborate with data analysts, BI developers, and architects on data requirements
- Document data pipelines, architecture, and operational runbooks

Mandatory Skills Description:

- 5+ years of experience
- Hands-on experience building data pipelines on AWS (Glue, EMR, Lambda, Step Functions)
- Strong SQL and experience with data warehousing (Redshift, dimensional modeling)
- Proficiency in Python or Scala for data engineering
- Experience with S3-based data lake architecture (partitioning, cataloging, formats like Parquet)
- Experience migrating data pipelines from on-prem or other cloud platforms
- Understanding of data governance, security, and access control on AWS
- Experience with CI/CD for data pipelines

Nice-to-Have Skills Description:

- AWS certification (Data Analytics Specialty or Data Engineer Associate)
- Experience with streaming data (Kinesis, MSK/Kafka)
- Familiarity with Infrastructure as Code (Terraform/CloudFormation)
- Experience with orchestration tools (Airflow, dbt)
- Experience in financial domain

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

Responsibilities:

- Agentic AI Migration Framework development — design and build an agentic AI framework to automate and accelerate migration workflowsж
- Pattern library build — develop and maintain a library of reusable migration patterns/templates for common conversion scenarios;
-Automated conversion pipeline — build pipelines that automatically convert/transform code and configurations (e.g., Matillion jobs) as part of the migration process;
-GitHub Copilot integration for code generation — integrate GitHub Copilot into the migration workflow to accelerate code generation and conversion tasks;
-Support factory pods — provide technical support, tooling, and troubleshooting to migration factory pods executing migrations at scale

Mandatory Skills Description:

- Python — strong hands-on Python development experience for building tools and automation
- GenAI/LLM integration — experience integrating GenAI/LLM capabilities into applications, workflows, or tooling
- Prompt engineering — hands-on experience designing, testing, and optimizing prompts for LLM-based tools
- AWS Bedrock — hands-on experience with AWS Bedrock for building GenAI-powered applications
- GitHub Copilot — practical experience using and/or integrating GitHub Copilot into development workflows
- Automation frameworks — experience designing and building automation frameworks/tooling from scratch
- Testing — strong experience with test automation and validation frameworks to ensure conversion accuracy
- Matillion JSON parsing — experience parsing, interpreting, and transforming Matillion job definitions (JSON format)

Nice-to-Have Skills Description:

Experience in financial domain

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

Responsibilities:

-Target-state architecture design — define and own the target-state AWS architecture across compute, data, and orchestration layers
-HLD/LLD ownership — produce and own High-Level Design and Low-Level Design documentation for migration workloads
-ARB submissions — prepare and present architecture proposals to the Architecture Review Board for approval
-Technical decisions — make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)
Pattern definition — define reusable architecture and migration patterns for use across teams/pods
-Agentic AI framework architecture — design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

Mandatory Skills Description:

- 5+ years experience
- hands-on experince with AWS Migration
- AWS Glue, Step Functions, Lambda, EventBridge — deep hands-on experience designing solutions using these core AWS services
- IaC (Terraform) — strong experience defining and managing infrastructure as code with Terraform
- Data platform architecture — proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale
- PySpark — hands-on experience with PySpark for large-scale data processing
- CI/CD — experience designing and implementing CI/CD pipelines for infrastructure and data workflows
- AI/ML frameworks — working knowledge of AI/ML frameworks and their application within architecture design
- GitHub Copilot — practical experience using GitHub Copilot within development/architecture workflows

Nice-to-Have Skills Description:

- AWS certification (Data Analytics Specialty or Solutions Architect)
- Experience with BI tools (QuickSight, Tableau, Power BI)
- Infrastructure as Code experience (Terraform/CloudFormation)
- Industry experience relevant to your business
- Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)
- experince in financial domain

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

Responsibilities:

-Target-state architecture design — define and own the target-state AWS architecture across compute, data, and orchestration layers
-HLD/LLD ownership — produce and own High-Level Design and Low-Level Design documentation for migration workloads
-ARB submissions — prepare and present architecture proposals to the Architecture Review Board for approval
-Technical decisions — make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)
Pattern definition — define reusable architecture and migration patterns for use across teams/pods
-Agentic AI framework architecture — design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

Mandatory Skills:

AWS Database Migration Service

Mandatory Skills Description:

- 5+ years experience
- hands-on experince with AWS Migration
- AWS Glue, Step Functions, Lambda, EventBridge — deep hands-on experience designing solutions using these core AWS services
- IaC (Terraform) — strong experience defining and managing infrastructure as code with Terraform
- Data platform architecture — proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale
- PySpark — hands-on experience with PySpark for large-scale data processing
- CI/CD — experience designing and implementing CI/CD pipelines for infrastructure and data workflows
- AI/ML frameworks — working knowledge of AI/ML frameworks and their application within architecture design
- GitHub Copilot — practical experience using GitHub Copilot within development/architecture workflows

Nice-to-Have Skills Description:

- AWS certification (Data Analytics Specialty or Solutions Architect)
- Experience with BI tools (QuickSight, Tableau, Power BI)
- Infrastructure as Code experience (Terraform/CloudFormation)
- Industry experience relevant to your business
- Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)
- experince in financial domain

Languages:

English: C2 Proficient

Project description

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

Responsibilities

-Target-state architecture design — define and own the target-state AWS architecture across compute, data, and orchestration layers

-HLD/LLD ownership — produce and own High-Level Design and Low-Level Design documentation for migration workloads

-ARB submissions — prepare and present architecture proposals to the Architecture Review Board for approval

-Technical decisions — make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)

Pattern definition — define reusable architecture and migration patterns for use across teams/pods

-Agentic AI framework architecture — design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

Skills

Must have

5+ years experience

hands-on experince with AWS Migration

AWS Glue, Step Functions, Lambda, EventBridge — deep hands-on experience designing solutions using these core AWS services

IaC (Terraform) — strong experience defining and managing infrastructure as code with Terraform

Data platform architecture — proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale

PySpark — hands-on experience with PySpark for large-scale data processing

CI/CD — experience designing and implementing CI/CD pipelines for infrastructure and data workflows

AI/ML frameworks — working knowledge of AI/ML frameworks and their application within architecture design

GitHub Copilot — practical experience using GitHub Copilot within development/architecture workflows

Nice to have

AWS certification (Data Analytics Specialty or Solutions Architect)

Experience with BI tools (QuickSight, Tableau, Power BI)

Infrastructure as Code experience (Terraform/CloudFormation)

Industry experience relevant to your business

Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)

experince in financial domain

Other

Languages

English: C2 Proficient

We are looking for a Head of Product with hands-on experience in blockchain, digital asset, and/or fintech products to lead product strategy, roadmap development, and delivery.

Key Responsibilities:

• Define and maintain the product vision, strategy, and roadmap.
• Research market trends, competitors, and user needs.
• Translate business goals into clear product requirements.
• Prioritize features and manage the product backlog.
• Coordinate product, design, engineering, and business teams.
• Define product metrics and evaluate feature performance.
• Manage product delivery, timelines, risks, and dependencies.
• Work with external technology and service providers.

• Improve internal product development processes.

   

Requirements:

• Experience as a Head of Product, Product Lead, or Senior Product Manager.
• Hands-on experience with blockchain, digital asset, and/or fintech products is required.
• Strong understanding of product discovery, development, and delivery.
• Experience creating product roadmaps and writing clear requirements.
• Understanding of wallets, payments, trading systems, liquidity, custody, and KYC/AML solutions.
• Strong analytical, communication, and leadership skills.
• Experience working with technical teams and external providers.

• English proficiency sufficient for working with international teams and documentation.

   

What We Offer:

• Full-time employment.
• Remote work.
• Flexible working hours.
• Competitive compensation based on interview results.
• Paid vacation and sick leave.
• Direct influence on the product strategy and development.
• Long-term cooperation.

• This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
  During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
  The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
  This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

• Responsibilities:

  - Design, build, and maintain ETL/ELT pipelines on AWS
  - Migrate existing data pipelines and workloads from legacy/on-prem systems to AWS
  - Develop and optimize data models for data warehouse/data lake (Redshift, S3)
  - Build and orchestrate data workflows (Glue, Step Functions, Lambda, EMR)
  - Implement data quality checks, validation, and reconciliation processes
  - Optimize pipeline performance and manage compute/storage costs
  - Ensure data security and access control (IAM, KMS, encryption)
  - Monitor and troubleshoot pipeline failures (CloudWatch, logging)
  - Collaborate with data analysts, BI developers, and architects on data requirements
  - Document data pipelines, architecture, and operational runbooks

• Mandatory Skills Description:

  - 5+ years of experience
  - Hands-on experience building data pipelines on AWS (Glue, EMR, Lambda, Step Functions)
  - Strong SQL and experience with data warehousing (Redshift, dimensional modeling)
  - Proficiency in Python or Scala for data engineering
  - Experience with S3-based data lake architecture (partitioning, cataloging, formats like Parquet)
  - Experience migrating data pipelines from on-prem or other cloud platforms
  - Understanding of data governance, security, and access control on AWS
  - Experience with CI/CD for data pipelines

• Nice-to-Have Skills Description:

  - AWS certification (Data Analytics Specialty or Data Engineer Associate)
  - Experience with streaming data (Kinesis, MSK/Kafka)
  - Familiarity with Infrastructure as Code (Terraform/CloudFormation)
  - Experience with orchestration tools (Airflow, dbt)
  - Experience in financial domain

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

• Responsibilities:

  - Agentic AI Migration Framework development — design and build an agentic AI framework to automate and accelerate migration workflowsж
  - Pattern library build — develop and maintain a library of reusable migration patterns/templates for common conversion scenarios;
  -Automated conversion pipeline — build pipelines that automatically convert/transform code and configurations (e.g., Matillion jobs) as part of the migration process;
  -GitHub Copilot integration for code generation — integrate GitHub Copilot into the migration workflow to accelerate code generation and conversion tasks;
  -Support factory pods — provide technical support, tooling, and troubleshooting to migration factory pods executing migrations at scale

• Mandatory Skills Description:

  - Python — strong hands-on Python development experience for building tools and automation
  - GenAI/LLM integration — experience integrating GenAI/LLM capabilities into applications, workflows, or tooling
  - Prompt engineering — hands-on experience designing, testing, and optimizing prompts for LLM-based tools
  - AWS Bedrock — hands-on experience with AWS Bedrock for building GenAI-powered applications
  - GitHub Copilot — practical experience using and/or integrating GitHub Copilot into development workflows
  - Automation frameworks — experience designing and building automation frameworks/tooling from scratch
  - Testing — strong experience with test automation and validation frameworks to ensure conversion accuracy
  - Matillion JSON parsing — experience parsing, interpreting, and transforming Matillion job definitions (JSON format)

Cloudfresh ⛅️ is a Global Google Cloud Premier Partner, Zendesk Premier Partner, Asana Solutions Partner, GitLab Select Partner, Hubspot Platinum Partner, Okta Activate Partner, and Microsoft Partner.

Since 2017, we’ve been specializing in the implementation, migration, integration, audit, administration, support, and training for top-tier cloud solutions. Our products focus on cutting-edge cloud computing, advanced location and mapping, seamless collaboration from anywhere, unparalleled customer service, and innovative DevSecOps.

We're looking for an AI Architect to become our lead technical expert for client AI solutions and to help stand up our AI Competence Centre and internal AI Lab.

This is a client-facing technical role first, with a build-and-lead dimension. Expect roughly 60% solution architecture and pre-sales engineering for enterprise clients, and 40% establishing the AI Lab and mentoring engineers. You'll technically lead and raise the bar for the team - this is a technical leadership role, not a people-management line.
Reports to: Head of AI.

Requirements

• Experience & seniority. 5+ years in software, data, or ML engineering, including 3+ years delivering ML/AI in production and 2+ years in a client-facing architect or technical lead capacity.
• Cloud & AI infrastructure. Production-level experience on Google Cloud Platform, especially the Vertex AI suite, plus integrating third-party model providers such as Anthropic.
• GenAI engineering. Strong hands-on knowledge of RAG, agentic workflows, orchestration frameworks (LangChain, LlamaIndex), vector databases, and prompt/context engineering.
• Production & MLOps. Hands-on with the ML lifecycle, CI/CD for models, automated deployment, and cloud cost management - including right-sizing models (lighter vs. heavier) to control spend.
• Evaluation, guardrails & observability. Practical experience building LLM evaluations, guardrails, and monitoring for accuracy, safety, latency, and cost in production.
• AI governance & security. Familiarity with data governance, model risk, and EU regulation (EU AI Act, GDPR) as it applies to enterprise AI — we're primarily EU-based.
• Pre-sales & client experience. Proven experience presenting to enterprise clients, scoping technical projects, and translating complex AI concepts into clear business value.
• Technical leadership. Experience guiding engineers, reviewing architecture and code, and raising team capability.
• Languages. Native Ukrainian — required, as you'll run Ukrainian-language pre-sales — and strong English (B2+/C1 minimum).

• Mindset & agility. An intrapreneurial drive to build an AI Lab from scratch inside an established business, plus the agility to move smoothly between client pre-sales and deep technical architecture.

   

Responsibilities

• Solution architecture. Design and own end-to-end AI systems for strategic enterprise clients - reference architectures, data and retrieval pipelines, agentic layers, and integration with existing enterprise systems - with a clear path from prototype to scalable, secure, observable production.
• Pre-sales & consulting. Partner with sales to qualify and win AI opportunities: run technical discovery, scope solutions, size effort and cost, and translate AI into business value, ROI, and risk for C-level stakeholders.
• Technical leadership & mentorship. Set architecture and engineering standards, run design and code reviews, and level up engineers across the AI practice.
• AI Lab & R&D. Stand up and run the internal AI Lab - rapid client prototypes and cost-effective internal AI tooling - with a clear bar for what graduates into production.
• Partner collaboration. Work with our core AI partners (Google Cloud / Vertex AI, Anthropic) to build joint solutions, access early capabilities, and shape our technical roadmap.
• Governance, security & cost. Build guardrails, evaluation, and observability into every solution; keep architectures compliant (EU AI Act, GDPR) and cost-aware through right-sized model selection.

Would be a plus

• Google Cloud Professional Machine Learning Engineer and/or Professional Cloud Architect certification.
• Hands-on enablement or certification with Anthropic and Vertex AI generative-AI stacks.
• Direct experience mapping solutions to the EU AI Act risk framework.
• Fine-tuning, distillation, or model-optimization experience.
• Production experience with voice/multimodal AI (e.g., ElevenLabs) or AI-assisted engineering tooling (e.g., Cursor).
• Contributions to the open-source GenAI ecosystem.

Work conditions

• Flexible Work Format: Work remotely, allowing you to balance your professional and personal life efficiently.
• Training with Leading Cloud Products: Access in-depth training on cutting-edge cloud and AI solutions, enhancing your expertise and equipping you with the tools to succeed in an ever-evolving industry.
• International Collaboration: Work alongside A-players and seasoned professionals in the cloud industry.
• Global Exposure: Expand your expertise by engaging with international markets across the EMEA and CEE regions.
• Vibrant Team Environment: Be part of an innovative, dynamic team that fosters both personal and professional growth, creating opportunities for you to advance in your career.
  
  When applying to this position, you consent to the processing of your personal data by CLOUDFRESH for the purposes necessary to conduct the recruitment process, in accordance with Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016 (GDPR).
  Additionally, you agree that CLOUDFRESH may process your personal data for future recruitment processes. You can withdraw this consent at any time.

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

• Responsibilities:

  -Target-state architecture design — define and own the target-state AWS architecture across compute, data, and orchestration layers
  -HLD/LLD ownership — produce and own High-Level Design and Low-Level Design documentation for migration workloads
  -ARB submissions — prepare and present architecture proposals to the Architecture Review Board for approval
  -Technical decisions — make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)
  Pattern definition — define reusable architecture and migration patterns for use across teams/pods
  -Agentic AI framework architecture — design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

• Mandatory Skills Description:

  - 5+ years experience
  - hands-on experince with AWS Migration
  - AWS Glue, Step Functions, Lambda, EventBridge — deep hands-on experience designing solutions using these core AWS services
  - IaC (Terraform) — strong experience defining and managing infrastructure as code with Terraform
  - Data platform architecture — proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale
  - PySpark — hands-on experience with PySpark for large-scale data processing
  - CI/CD — experience designing and implementing CI/CD pipelines for infrastructure and data workflows
  - AI/ML frameworks — working knowledge of AI/ML frameworks and their application within architecture design
  - GitHub Copilot — practical experience using GitHub Copilot within development/architecture workflows

• Nice-to-Have Skills Description:

  - AWS certification (Data Analytics Specialty or Solutions Architect)
  - Experience with BI tools (QuickSight, Tableau, Power BI)
  - Infrastructure as Code experience (Terraform/CloudFormation)
  - Industry experience relevant to your business
  - Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)
  - experince in financial domain