Technical Lead, External and Scientific Engagement

Job Description

Are you passionate about driving innovation and leading technical initiatives in the realm of AI and IT Join our company a premier research-intensive biopharmaceutical organization where we leverage cutting-edge science to save and improve lives globally. As a Technical Lead you will play a pivotal role in guiding discovery-driven IT projects mentoring engineering teams and ensuring successful project delivery.

Responsibilities

• Lead and own technical execution of discovery IT initiatives and AI projects from ideation through POC pilot and handover to development teams.
• Architect design and implement POCs to validate business value technical feasibility and scalability for discovery use cases.
• Guide and mentor cross-functional engineering teams (onshore and offshore) providing technical direction code reviews best practices and hands-on support as needed.
• Collaborate closely with business stakeholders product owners and research teams to translate scientific and business requirements into technical solutions and project roadmaps.
• Serve as primary technical liaison between business data science infrastructure and offshore development teams to ensure alignment and timely delivery.
• Drive adoption of modern development practices: CI/CD pipelines infrastructure as code secure coding standards and observability.
• Lead technical evaluations and vendor/tool selection related to AI data platforms and application infrastructure.
• Provide hands-on development in Python (or guide developers) and ensure high quality implementation of backend and frontend components.
• Ensure data integrity lineage and governance when integrating with systems such as Veeva Vault and enterprise data platforms.
• Oversee deployment and management of solutions on cloud platforms (AWS Azure) and collaborate with cloud/infrastructure teams for scalability security and cost optimization.
• Track and report project status risks and mitigation plans to leadership; escalate when necessary.
• Promote knowledge sharing establish technical standards and build repeatable patterns for discovery POCs and AI initiatives.

Qualifications

Required

• 10 years of professional IT experience with progressively increasing technical and leadership responsibilities.
• Full-stack development
• Frontend technologies: Expertise in modern frontend frameworks such as React (including Hooks state management libraries and performance optimization) and experience with rapid prototyping/visualization frameworks like Streamlit for data-driven UIs.
• Backend: Strong experience with (Express NestJS or similar) RESTful and GraphQL API design authentication/authorization (OAuth2 JWT) middleware and microservices patterns.
• Language proficiency: Advanced Python for backend services scripting ML integration and automation.
• AI / Machine Learning: Practical experience building prototyping and productionizing ML/AI models (supervised unsupervised NLP and generative-model POCs).
• Familiarity with ML frameworks and libraries (PyTorch Hugging Face GPPTeal Claud Gemini).
• Knowledge of model evaluation validation feature engineering experiment tracking (MLflow) and model deployment patterns.
• Experience integrating AI models into applications and APIs and working with data scientists on model lifecycle.
• Data engineering & analytics: Hands-on with Databricks/Spark for large-scale data processing.
• ETL/ELT: Experience with dbt (transformations testing modularity) building reliable data pipelines and mature data models.
• Databases: Strong SQL skills and experience with Oracle (query tuning schema design indexing) plus familiarity with modern analytical stores (Snowflake Redshift) is a plus.
• Data governance: Knowledge of lineage cataloging metadata quality checks and compliance in regulated environments.
• Integration & domain systems: Understanding of Vault architecture document and metadata models Vault APIs Vault SDKs and integration patterns for ingesting synchronizing and securing regulated content.
• API integrations: Robust experience in designing integrations between cloud services SaaS systems and on-prem systems; message queues and streaming (Kafka SQS Event Hubs) knowledge preferred.
• Cloud platforms: Strong practical experience with AWS and/or Azure (compute storage networking IAM managed data services).
• Infrastructure as Code: Experience with Terraform ARM templates or CloudFormation for reproducible environments.
• Containerization & orchestration: Docker and Kubernetes (deployment patterns Helm charts observability).
• Security & compliance: Identity and access control encryption in transit/at rest secrets management and secure deployment practices.
• CI/CD: Design and implement pipelines (GitHub Actions Jenkins GitLab CI) for build test security scanning and deploy across environments.
• Automated testing: Unit integration contract and end-to-end tests; test frameworks for Python/Node/React.
• Observability: Logging monitoring alerting (ELK/Elastic Stack Prometheus Grafana) and tracing (OpenTelemetry).
• GitHub/Git workflows: Branching strategies pull request policies code review best practices dependency management.
• Collaboration tools: Jira/Azure DevOps for backlog and sprint management Confluence or similar for documentation.
• System architecture: Design scalable resilient microservices and data pipelines; trade-off analysis for latency throughput cost and security.
• API-first design: Contract-first development versioning backward compatibility.
• Event-driven architecture: Designing loosely coupled services using events/streams.
• Scalability and performance: Load testing caching strategies database partitioning/sharding query optimization.
• Experience coordinating and leading offshore development teams and third-party vendors with demonstrated success in distributed team delivery.
• Excellent stakeholder management and communication skills; ability to translate technical concepts to non-technical audiences.
• Strong problem solving architectural design and decision-making skills.
• Knowledge of data governance security and compliance requirements relevant to discovery and regulated industries.

Preferred

• Prior experience in life sciences or pharmaceutical discovery IT or closely related scientific domains with an understanding of discovery workflows data sensitivity and regulatory considerations.
• Demonstrated experience working on AI/ML projects using common frameworks and tooling for example: MLflow for experiment tracking TensorFlow or PyTorch for model development and Hugging Face or similar libraries for NLP/transformer work.
• Hands-on familiarity with modern data platforms and analytics warehouses such as Databricks or equivalent cloud-native data stores.
• Experience deploying and managing ML workloads on cloud ML platforms (AWS SageMaker Azure ML or equivalent) including model training tuning serving and monitoring in production.
• Proven track record of delivering software products using Agile methodologies (Scrum Kanban) including hands-on experience managing product backlogs running sprint ceremonies and working closely with product owners and stakeholders.
• Prior experience integrating or implementing regulated content systems (e.g. Veeva Vault) within discovery or R&D environments is a plus.
• Experience with containerization and orchestration (Docker Kubernetes) for scalable application and model deployments.
• Familiarity with MLOps practices and tooling (CI/CD for ML model governance automated testing for models model drift detection).
• Strong knowledge of data privacy security and compliance standards relevant to life sciences (e.g. data encryption access controls auditability).
• Experience leading or coordinating distributed and offshore engineering teams in multi-vendor environments.

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
• Competitive salary & incentive pay
• Pension and health insurance contributions
• Internal reward system and referral scheme
• 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 sport culture health travel etc.) Multisport Card
• Vodafone Raiffeisen Bank Foodora and discount programmes
• Up-to-date laptop and iPhone
• Parking in the garage showers refreshments massage chairs library music corner

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Merck & Co. Inc. Rahway NJ USA also known as Merck Sharp & Dohme LLC Rahway NJ USA does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place introductions are position specific. Please no phone calls or emails.

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