Lead AI Back End Software Engineer (AI Architect Track)

Description

We are looking for a Senior/Lead AI Back End Software Engineer (AI Architect Track) who will drive the architecture and delivery of AI-powered Search solutions, taking ownership of end-to-end system design, model integration, and platform scalability while guiding teams toward production-ready, high-quality outcomes.

About Pwrteams:

Join our fast-growing and diverse team at Pwrteams, where we provide premium IT and engineering nearshore solutions to our global customers. Since 2007, we pursue to become the market leader in assembling cross-border IT and engineering teams for customers. Our operations are strategically positioned within Eastern Europe’s dynamic tech ecosystems, from where we cater the global business landscape. 
We’re at the forefront of travel, media and fintech innovation, healthcare efficiency enhancements, and others. Our goal? To connect interesting customer projects and skilled talent alike. Become a part of our team and take the next step on your personal career journey.

About the project
TUI, is a global business with over 70 000 people on board, great history and challenging plans for building a digital future. TUI is the largest leisure, travel and tourism company globally, and it owns travel agencies, hotels, airlines, cruise ships and retail shops.

You will join a global Search Services team within a large-scale digital platform, responsible for filtering, sorting, and enriching product data for customer-facing systems. The team operates in a highly distributed environment across multiple countries and focuses on building AI-powered search capabilities that enhance user experience through faster, smarter, and more relevant results.

Responsibilities

• Lead the architecture and design of AI-powered Search solutions, covering services, data flows, and model integration

• Drive end-to-end delivery from discovery and validation to production and continuous improvement

• Design and implement solutions using GenAI models, including orchestration, evaluation strategies, and retrieval-augmented generation (RAG)

• Define reference architectures and best practices for secure, scalable, and cost-efficient model usage

• Ensure platform reliability, including latency optimisation, observability, security, and cost control

• Conduct and guide proof-of-concepts (POCs), validating approaches based on performance, accuracy, and cost

• Collaborate closely with architecture, product, data, and engineering teams to align solutions and trade-offs

• Lead technical discussions, workshops, and design reviews across teams

• Mentor engineers and contribute to building a strong engineering culture

• Research and promote new technologies, tools, and approaches in AI and backend engineering

Qualifications

• Strong experience designing and operating large-scale backend systems in production

• Deep proficiency in Java or Kotlin, with hands-on experience in cloud-native development

• Strong experience with microservices architecture, including performance tuning and reliability patterns

• Experience with AWS cloud architecture (networking, IAM, observability, scalability)

• Practical experience delivering AI/LLM-based solutions in production (e.g. RAG, orchestration, evaluation, monitoring)

• Strong understanding of ML/AI concepts (embeddings, retrieval, model evaluation, safety considerations)

• Experience with Python and AI/ML tooling

• Experience with REST and/or GraphQL APIs

• Experience working with SQL and/or NoSQL databases

• Strong DevSecOps mindset and experience with CI/CD pipelines

• Excellent communication skills and ability to work with both technical and non-technical stakeholders

• Leadership mindset with experience mentoring or coaching engineers

• High level of English (written and spoken)

• Proactive, ownership-driven, and comfortable working in ambiguous environments

Nice to Have

• Hands-on experience with AWS Bedrock and GenAI tooling

• Experience with OpenSearch / Elasticsearch and search relevance tuning

• Experience with Terraform and Infrastructure as Code

• Familiarity with GitLab CI or similar CI/CD tools

• Experience defining LLM evaluation frameworks (prompt versioning, testing, red-teaming)

• Understanding of event-driven architectures

• Experience working in global, distributed teams

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