Software Engineering Technical Lead – DevX AI

Job Description

Based in Prague join a global healthcare biopharma company and be part of a 130year legacy of success backed by ethical integrity forward momentum and an inspiring mission to achieve new milestones in global healthcare.

Be part of an organisation driven by digital technology and databacked approaches that support a diversified portfolio of prescription medicines vaccines and animal health products.

Help drive our AI strategy and implementation. Join a team with a passion for using data analytics and modern AI techniques to build solutions that support critical decisions and help us tackle some of the worlds greatest health threats.

Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our companys IT operating model Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations in addition to other sites are essential to supporting our business and strategy.

A focused group of leaders in each Tech Center helps to ensure we can manage and improve each location: from investing in the growth success and wellbeing of our people to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. Together we leverage the strength of our global team to collaborate optimize connections and share best practices across the Tech Centers.

Join our company as a Software Engineering Technical Lead DevX AI as we innovate across the application lifecycle. You will be a handson engineer and technical contributor responsible for designing building and operationalizing AIpowered products and platforms using modern technologies such as Python AWS/Azure/GCP containerization (Docker Kubernetes/EKS) eventdriven architectures RetrievalAugmented Generation (RAG) vector databases and LLM orchestration frameworks.

What will you do

> In sum

• Drive the endtoend implementation of AI solutions from discovery and prototyping through production deployment and lifecycle management

• Work closely with product owners data scientists architects and business stakeholders to identify use cases design scalable solutions and deliver measurable value

• Help shape our AI engineering best practices patterns and reusable components that can be leveraged across teams and use cases

• Act as a flagship practitioner for AIaugmented software development demonstrating how developers can responsibly and effectively use AI tools (code assistants documentation agents test generators etc.) across the full development lifecycle

> Design and build AI solutions

• Design develop and maintain AIenabled applications and services using Python and AWS (e.g. Lambda ECS/EKS S3 API Gateway Step Functions DynamoDB RDS; experience with SageMaker or Bedrock is a plus)

• Implement RAGbased systems and other LLM integration patterns including document ingestion indexing retrieval pipelines grounding on internal data sources and prompt orchestration

• Work with vector databases (e.g. OpenSearch pgvector or similar) and embedding models to build semantic search and knowledge retrieval capabilities

• Leverage LLM orchestration / tooling frameworks (such as LangChain LlamaIndex or equivalent) to build robust AI workflows and agents

• Build reusable microservices APIs and SDKs that expose AI capabilities to other products and teams

> Own the AI solution lifecycle

• Drive solutions from proofofconcept to productiongrade implementations including performance reliability observability and cost optimization

• Implement robust CI/CD pipelines (e.g. GitHub Actions) automated testing and infrastructureascode (e.g. Terraform AWS) for AI solutions

• Use containerization (Docker) and orchestration (Kubernetes / AWS EKS) to ensure scalable and portable deployments

• Monitor and continuously improve AI features in production (quality latency stability usage) using logging tracing and metrics

> Champion AI in the developer workflow

• Serve as a role model for AIassisted development using AI tools for tasks such as code generation refactoring test creation documentation and troubleshootingwhile maintaining strong engineering discipline

• Help define standards and guidelines for responsible use of AI tools by developers (e.g. code review practices IP considerations data sensitivity)

• Coach other engineers on how to integrate AI into their daily workflows to increase productivity and quality without compromising security or compliance

• Experiment with and evaluate new AI capabilities (e.g. code copilots test bots documentation assistants monitoring agents) and provide recommendations for wider adoption across the organization

What should you have

> Education & experience

• Bachelors or Masters degree in Computer Science Information Technology Engineering or a related technology field

• Relevant software engineering experience including building and operating production systems

• Handson experience delivering AI/ML or LLMpowered solutions in a production environment is strongly preferred

> Technical skills

• Strong proficiency in Python for backend development and scripting.

• Practical experience with AWS services for building cloudnative applications (e.g. Lambda ECS/EKS S3 API Gateway IAM CloudWatch Step Functions Bedrock)

• Experience implementing RAG architectures and integrating LLMs (opensource or commercial) into applications

• Handson experience with vector databases / embeddings and document processing with LLM orchestration frameworks (e.g. LangChain LlamaIndex or similar)

• Experience with RESTful APIs eventdriven architectures (SNS/SQS Kafka/Kinesis or similar) and microservices

• Experience with containerization and orchestration (Docker Kubernetes AWS EKS)

• Strong grounding in software engineering fundamentals: design patterns code quality testing observability performance and security

• Handson experience with Gitbased source control CI/CD pipelines and modern DevOps practices

• Practical exposure to AIassisted development tools (e.g. code copilots AI test generators documentation assistants) and a perspective on how to use them effectively in a team setting

> Nice to have

• Exposure to MLOps practices and tools (model packaging deployment monitoring model registry)

• Experience with prompt engineering LLM orchestration frameworks or AI agents

• Experience building tools that support the software development lifecycle (e.g. AIassisted coding testing documentation or operations)

> Soft skills

• Strong problemsolving mindset with the ability to translate complex business problems into practical AI solutions

• Comfort working in a global crossfunctional environment with distributed teams

• Good communication skills able to explain technical concepts to both technical and nontechnical stakeholders

• Curiosity and a continuous learning mindset especially around emerging AI technologies and practices

What we offer

• Exciting work in a great team global projects international environment

• Opportunity to learn and grow professionally within the company globally

• Hybrid working model flexible role pattern

• Pension and health insurance contributions

• Internal reward system plus referral program

• 5 weeks annual leave 5 sick days 15 days of certified sick leave paid above statutory requirements annually 40 paid hours annually for volunteering activities 12 weeks of parental contribution

• Cafeteria for tax free benefits according to your choice (meal vouchers Lítačka sport culture health travel etc.) Multisport Card

• Vodafone Raiffeisen Bank Foodora and other discount programs

• Up-to-date laptop and iPhone

• Parking in the garage for drivers or showers for bikers

• Competitive salary incentive pay and many more

Ready to take up the challenge Apply now!
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