FlexSolution

About the Product & Team

The primary objective is to mirror an external candidate database into internal infrastructure to remove external API bottlenecks and provide a centralised data layer for downstream AI workflows.

• The Build: Focuses on continuous synchronisation, database replication, and high-volume data ingestion.
• Team Structure: Engineers will work directly with the Head of AI & Technology, a Technical Product Owner, and the existing backend and DevOps teams.
• Lead Expectations: The Lead Engineer is expected to take technical ownership of the workstream, driving architecture and partnering with leadership to unblock teams.

Responsibilities

• Platform Engineering: Build and maintain a custom API using Python and design services for large-scale data ingestion and replication.
• Cloud-Native Delivery: Deploy containerised services via Docker and Kubernetes while integrating AWS services (S3, API Gateway, Lambda, SQS).
• System Architecture: Implement event-driven patterns using queues and asynchronous processing.
• Quality & Reliability: Implement automated testing (unit, integration, performance) and ensure robust monitoring, logging, and failure recovery patterns.
• Collaboration: Work within agile ceremonies and align closely with DevOps on infrastructure and release processes.

Requirements

Technical Experience

• Core Stack: Advanced proficiency in Python and strong API design experience.
• Cloud & Infrastructure: Mandatory AWS experience alongside Kubernetes and Docker.
• Systems Design: Experience with distributed systems, high-throughput services, and messaging/queue-based architectures. 
• Preferred Skills: Experience with data replication or ETL-style pipelines and schema design/evolution.
• Typically 8+ years of experience; proven technical ownership of platform initiatives with the ability to set direction and drive architecture.

Business & Soft Skills

• Market Experience: Background in B2B SaaS platforms, data-intensive products, or AI-enabled environments.
• Mindset: Ownership mentality with clear technical communication and the ability to operate effectively with partial requirements.
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Assessment Process

1. Stage 1: CV Review.

2. Stage 2: Screening Interview (30 mins).

3. Stage 3: Technical Assessment (1 hour) including pair-programming.

4. Stage 4: Interview with the Head of AI & Technology.

Target Start Date: Immediate.

Engagement Length: 6 months (3 months on custom API build + 3 months integrated into the core team).

What We Offer:

• Full remote with flexible business hours;
• Three weeks of vacation per year (15 working days);
• Paid sick leave per year (5 working days);
• Amazing opportunities for professional growth within a top-notch team of professionals;
• Competitive compensation commensurate with your experience and skills;
• English lessons;
• Co-working compensation;
• An excellent team with a friendly atmosphere.

About the Product & Team

The primary objective is to mirror an external candidate database into internal infrastructure to remove external API bottlenecks and provide a centralised data layer for downstream AI workflows.

• The Build: Focuses on continuous synchronisation, database replication, and high-volume data ingestion.
• Team Structure: Engineers will work directly with the Head of AI & Technology, a Technical Product Owner, and the existing backend and DevOps teams.
• Lead Expectations: The Lead Engineer is expected to take technical ownership of the workstream, driving architecture and partnering with leadership to unblock teams.

Responsibilities

• Platform Engineering: Build and maintain a custom API using Python and design services for large-scale data ingestion and replication.
• Cloud-Native Delivery: Deploy containerised services via Docker and Kubernetes while integrating AWS services (S3, API Gateway, Lambda, SQS).
• System Architecture: Implement event-driven patterns using queues and asynchronous processing.
• Quality & Reliability: Implement automated testing (unit, integration, performance) and ensure robust monitoring, logging, and failure recovery patterns.
• Collaboration: Work within agile ceremonies and align closely with DevOps on infrastructure and release processes.

Requirements

Technical Experience

• Core Stack: Advanced proficiency in Python and strong API design experience.
• Cloud & Infrastructure: Mandatory AWS experience alongside Kubernetes and Docker.
• Systems Design: Experience with distributed systems, high-throughput services, and messaging/queue-based architectures. 
• Preferred Skills: Experience with data replication or ETL-style pipelines and schema design/evolution.
• Typically 5+ years of experience; strong individual contributors

comfortable owning services end-to-end.

Business & Soft Skills

• Market Experience: Background in B2B SaaS platforms, data-intensive products, or AI-enabled environments.
• Mindset: Ownership mentality with clear technical communication and the ability to operate effectively with partial requirements.

Assessment Process

1. Stage 1: CV Review.

2. Stage 2: Screening Interview (30 mins).

3. Stage 3: Technical Assessment (1 hour) including pair-programming.

4. Stage 4: Interview with the Head of AI & Technology.

Target Start Date: Immediate.

Engagement Length: 6 months (3 months on custom API build + 3 months integrated into the core team).

What We Offer

• Full remote with flexible business hours;
• Three weeks of vacation per year (15 working days);
• Paid sick leave per year (5 working days);
• Amazing opportunities for professional growth within a top-notch team of professionals;
• Competitive compensation commensurate with your experience and skills;
• English lessons;
• Co-working compensation;
• An excellent team with a friendly atmosphere.