Engineering Manager - Java Full Stack & AI

Tech Stack:

• Backend: Java 17+, Spring Boot, REST APIs, Microservices

• Frontend: Angular and/or React, JavaScript, TypeScript

• AI & Innovation: LLMs, AI Agents, Agentic AI, GitHub Copilot, AI-Assisted Development

• Cloud & DevOps: Azure, AWS or GCP, CI/CD, Infrastructure as Code (IaC)

• Architecture: Distributed Systems, Event-Driven Architecture, Integration Patterns

Required Qualifications:

• 7+ years of commercial software engineering experience.

• Expert-level knowledge of Java (17+) and modern backend development practices.

• Strong hands-on experience with Spring Boot and the Spring ecosystem.

• Commercial Full Stack development experience with Angular and/or React.

• Solid understanding of modern JavaScript/TypeScript frameworks and frontend development.

• Experience designing and developing REST APIs and microservices-based solutions.

• Strong knowledge of software architecture, system design, and integration patterns.

• Experience working with distributed systems, event-driven architectures, and scalable applications.

• Commercial experience with AI-powered solutions, including Large Language Models (LLMs), AI agents, or agentic workflows.

• Experience using AI-assisted development tools such as GitHub Copilot or similar solutions.

• Ability to assess the technical and business feasibility of AI initiatives and contribute to high-level estimations.

• Understanding of AI adoption from both business value and ROI perspectives.

• Commercial experience with at least one major cloud platform (Azure, AWS, or GCP).

• Practical knowledge of DevOps practices, CI/CD pipelines, and Infrastructure as Code (IaC).

• Strong understanding of Software Development Lifecycle (SDLC) and Product Development Lifecycle (PDLC).

• Experience working in Agile delivery environments and applying modern engineering practices.

• Ability to translate business requirements into scalable technical solutions.

• Experience mentoring engineers and/or providing technical leadership.

• Strong stakeholder management and client-facing communication skills.

• Experience supporting recruitment activities, technical interviews, and competency assessments.

• Fluent English (B2+/C1).

Nice to Have:

• Practical experience with Terraform, Kubernetes, Docker, or similar containerization and infrastructure technologies.

• Experience working with Kafka and event-driven architectures.

• Knowledge of Retrieval-Augmented Generation (RAG) and related AI implementation patterns.

• Familiarity with AI orchestration frameworks and enterprise AI integrations.

• Experience supporting presales activities, technical discovery workshops, and solution design.

• Background in Financial Services, Banking, or FinTech projects.

• Experience working in consulting, outsourcing, or multi-client environments.

• Additional foreign language skills, particularly German and/or French.

• Advanced knowledge of DevOps practices and Infrastructure as Code (IaC).

Project Description:

In this role, you will serve as a trusted partner for clients, engineering teams, and internal stakeholders. You will balance hands-on technical involvement with broader responsibilities across delivery management, solution design, team leadership, technical consulting, and business growth. You will be expected to navigate complex project environments, assess both technical and organizational challenges, and help define pragmatic, scalable solutions. A key element of the role is supporting AI-related initiatives by evaluating their feasibility, cost, implementation complexity, and expected business value. This position is ideal for a technical leader who enjoys working close to architecture and code while influencing project success, talent development, and strategic decision-making.

Please note: this is a freelance engagement with a 12-month project duration.

Scope of Services:

• Lead and mentor engineering teams while maintaining technical credibility.

• Participate in architecture discussions and technical decision-making.

• Support project delivery and help resolve complex technical or organizational challenges.

• Act as a trusted technical advisor for clients and stakeholders.

• Evaluate AI opportunities and recommend solutions based on business value and feasibility.

• Support technical recruitment, interviewing, and competency development.

• Collaborate with Hiring Managers on team structures and capability planning.

• Contribute to presales, estimation, and solution design activities.

• Identify training needs and drive knowledge-sharing initiatives across teams.

• Foster engineering excellence, continuous improvement, and long-term business growth