Platform Engineering Technical Manager

At BBH, Partnership is more than a form of ownership—it’s our approach to business and relationships.  We know that supporting your professional and personal goals is the best way to help our clients and advance our business. We take that responsibility seriously. With a 200-year legacy and a shared passion for what’s next, this is the right place to build a fulfilling career.

Location: Kraków

Hybrid model: 3 days per week in the office /2 days for a parent of a child up to 4 years old

About the team:

Platform Engineering Technical Manager is one of the most critical foundational hires on our team. You’ll own the non-AI core of the platform - the workflow orchestration engine, data processing layer, API services, and the infrastructure that makes everything reliable at scale. You’ll lead and grow the platform engineering team, set technical standards, and define the architecture that underpins how financial services firms create and execute their data integrations and transformations.

This is a player-coach role. In the near term you’ll be deeply hands-on - making architecture decisions, writing code, and establishing the patterns the team will build on. As the team grows, your focus shifts increasingly to technical leadership, and cross-functional alignment with AI Engineering, Design, and Product.

The platform you build is what makes our product trustworthy to enterprise financial services customers. Audit trails, high performance, data lineage, fault tolerance, and governance are not features - they are the foundation.

In our team, you will be responsible for:

Technical Leadership

• Lead and mentor the platform engineering team; establish coding standards, architectural patterns, and engineering practices that scale
• Own the technical roadmap for platform engineering, aligned with product goals and customer requirements
• Recruit and grow the team as the company scales
• Partner with the Head of AI Engineering to ensure the AI layer integrates cleanly with platform services

Workflow & Data Architecture

• Design and own the workflow orchestration layer using Temporal - the engine that drives how integrations and transformations are created, managed, and executed
• Build and evolve the core data processing pipeline - idempotent, fault-tolerant, and fully observable
• Design the Postgres data model supporting integration configuration, transformation versioning, execution history, and lineage tracking

Platform Development

• Build and maintain core platform services - REST and GraphQL APIs, integration framework, and the connector layer that links customer source and destination systems
• Design and implement the audit trail and immutable logging infrastructure that enterprise customers require
• Establish reliability practices: SLA definitions, monitoring, alerting, and incident response

Scalability & Governance

• Ensure all platform systems are highly available, performant, and cost-effective at scale
• Build the governance layer - access controls, data masking, encryption at rest and in transit - that makes the platform enterprise-grade
• Work with the Cloud Engineer on infrastructure needs, deployment architecture, and security posture

What we’re looking for:

• 7+ years software or platform engineering; 3+ years in technical leadership roles
• Player-coach track record - has led teams while remaining hands-on technically

Technical Skills

• Strong Python proficiency
• Production experience with Temporal or Cadence
• Distributed systems and microservices at scale
• Azure (primary) or AWS
• PostgreSQL - data modeling, schema design, query optimization
• Kubernetes and Docker
• REST and GraphQL API design
• Infrastructure as Code familiarity (Terraform)

Financial Services Data Processing (Highly Valued)

• Experience building systems that handle sensitive financial data at scale
• Understanding of data lineage, audit trails, and immutable logging
• Familiarity with event sourcing and CQRS patterns
• Data encryption at rest and in transit, tokenization, data masking
• Building systems with strict SLAs, disaster recovery, and business continuity requirements

Practices

• Cloud/SaaS - has built and operated multi-user production systems in cloud environments
• Active user of AI coding assistants in engineering workflow

Nice to Have

• Kafka or event streaming (Azure Service Bus, Kinesis)
• Mul…