About the Opportunity

We are hiring a Senior Personalization Solution Architect with deep domain expertise in personalization and experimentation to join Contentful’s Professional Services team. This role is designed for a practitioner who has built, operated, and scaled personalization programs in production, and who also brings the hands-on technical skills required to implement those programs in modern, composable architectures.

This is not a generalist Solution Architect role with light exposure to personalization. Success in this role requires strong opinions and real-world experience across audience strategy, decisioning, experimentation, and measurement—paired with the ability to design and deliver high-quality technical implementations using Contentful Personalization.

You will work directly with customer engineering, product, and marketing teams to design and implement advanced personalization and experimentation solutions, while also serving as a customer-facing extension of Contentful’s Product and Engineering teams. Your work will help reduce implementation risk, accelerate time to value, and create tighter feedback loops into product development—specifically for complex personalization use cases.

What to expect? 

Personalization & Experimentation Domain Leadership 

• Own the end-to-end design of personalization and experimentation programs, including:
• audience and segmentation strategies grounded in behavioral, contextual, and first-party data
• experience decisioning models that balance relevance, performance, and governance
• experimentation frameworks (A/B, multivariate, holdouts) with clear hypotheses and success criteria
  
  
• Design personalization strategies that scale responsibly, including:
• guardrails to prevent over-personalization, bias, and degraded user experience
• approaches for global, multi-brand, or multi-region deployments
• tradeoffs between targeting precision, latency, and operational complexity
  
  
• Define measurement approaches that connect:
• user behavior → decisioning logic → exposure → business outcomes
  
  
• Act as a domain authority for personalization and experimentation in customer engagements, confidently guiding technical and non-technical stakeholders through best practices, limitations, and tradeoffs.

Technical Solution Architecture & Hands-On Delivery

• Architect and implement end-to-end personalization solutions using Contentful Personalization, including:
• user identification and profile stitching
• audience evaluation and decisioning
• personalized content and experience delivery
  experimentation and uplift measurement
  
  
• Lead hands-on implementation activities such as:
• building proof-of-concepts and reference implementations
• configuring personalization models and decision logic
• developing integration services and APIs
• supporting production deployments and performance optimization
  
  
• Integrate personalization solutions with enterprise platforms including:
• CDPs (Segment, Tealium, mParticle, etc.)
• CRMs (Salesforce, Dynamics)
• analytics platforms (GA4, Adobe Analytics, Snowplow)
• identity, consent, and privacy tooling
  
  
• Design personalization delivery patterns across modern rendering strategies:
• SSR, CSR, SSG, ISR
• edge and CDN-based personalization
• hybrid static + runtime personalization approaches
  
  
• Ensure solutions meet enterprise requirements for:
• performance and scalability
• reliability and fallback behavior
• security and privacy compliance

Technical Discovery & Customer Enablement

• Lead technical discovery sessions to assess customer readiness across:
• data quality, identity maturity, and event instrumentation
• architectural constraints (latency, caching, edge delivery)
• content model alignment and operational workflows
  
  
• Translate personalization requirements into detailed technical designs, including:
• integration patterns and API contracts
• data and event schemas
• deployment and observability considerations
  
  
• Enable customer teams through:
• implementation workshops and pair-programming
• architecture and code reviews
• developer documentation and operational runbooks

Cross-Functional Collaboration & Feedback Loops

• Partner closely with Contentful Product and Engineering teams to:
• surface implementation challenges and recurring customer pain points
• provide feedback that influences roadmap, developer experience, and documentation
• validate new personalization capabilities against real customer use cases
  
  
• Contribute to internal enablement by:
• mentoring Solution Architects and delivery team members
• developing reusable accelerators, patterns, and reference architectures
• supporting Sales and Solution Engineering with technical expertise in complex personalization opportunities

What you need to be successful?

Required: Personalization & Experimentation Domain Expertise

• Demonstrated, hands-on experience designing and operating personalization and experimentation programs in production, including:
• ownership of audience strategy and decisioning logic
• designing and running A/B or multivariate experiments beyond basic UI testing
• interpreting experiment results and translating them into iterative improvements
  
  
• Strong understanding of personalization challenges such as:
• identity resolution and anonymous vs known users
• data sparsity and cold-start scenarios
• experimentation validity, bias, and statistical tradeoffs
• privacy, consent, and regulatory constraints

Required: Technical & Architectural Skills

• Advanced proficiency with modern web technologies:
  • JavaScript / TypeScript
  • React with Next.js (preferred), or Vue/Nuxt, Angular
  • REST and GraphQL APIs
    
    
• Deep understanding of web rendering and delivery patterns:
  • SSR, CSR, SSG, ISR
  • caching strategies and personalization at scale
• Strong experience integrating SaaS platforms and enterprise systems via APIs
• Experience designing or implementing cloud-native architectures (AWS, Azure, or GCP), including:
  • serverless or microservices-based systems
  • event-driven or streaming architectures

Professional Services & Collaboration Skills

• Experience delivering customer-facing technical engagements in a consulting or professional services context
• Comfortable leading technical deep dives with engineering teams and explaining experimentation concepts to non-technical stakeholders
• Strong written communication skills, especially technical documentation

Nice to Have

• Experience with CDPs, tag management systems, and event pipelines
• Familiarity with ML-driven personalization approaches (e.g., propensity models, recommenders), even if models are externally managed
• Experience working in composable DXP ecosystems (CMS, personalization, experimentation, commerce)

What Success Looks Like

• Customers successfully deploy production-grade personalization and experimentation programs using Contentful Personalization.
• Personalization solutions you design are:
• measurable and outcome-driven
• performant at enterprise scale
• governed and extensible over time
• Customer engineering teams trust your guidance because you bring deep personalization domain expertise backed by hands-on implementation experience.
• Product and Engineering teams benefit from clear, actionable feedback rooted in real customer implementations.
• Contentful is consistently seen as a credible personalization partner, not just a technology vendor.

What's in it for you?

• Join an ambitious tech company reshaping the way people build digital experiences
• Full-time employees receive Stock Options for the opportunity to share in the success of our company
• Comprehensive healthcare package covering 100% of monthly health premiums for employees  and 85% of costs for your dependents. 
• Fertility and family building benefits, including a lifetime reimbursable wallet to support your growing family.
• We value Work-Life balance and You Time! A generous amount of paid time off, including vacation days, sick days, compassion days for loss,  education days, and volunteer days
• Company paid parental leave to care for and focus on your growing family 
• Use your personal annual education budget to improve your skills and grow in your career
• Enjoy a full range of virtual and in-person events, including workshops, guest speakers, and fun team activities, supporting learning and networking exchange beyond the usual work duties 
• An annual wellbeing stipend to care for your physical, financial, or emotional health
• A monthly communication stipend and phone hardware upgrade reimbursement.
• New hire office equipment stipend for hybrid or distributed employees. Get the gear you need to work at your best.

This role will need to be conducted in a state in which we are currently registered to do business. In addition, this position is not eligible for visa sponsorship. Applicants must be authorized to work without the need for visa sponsorship by the start date of employment.

This position is eligible for equity awards in accordance with the terms of Contentful’s equity plans.

Director, Software Engineering

Department: Product Development

Reports to: SVP, Software Engineering

The Director, Software Engineering is responsible for the delivery of Enterprise SaaS products supporting the Clinical Trial industry, overseeing multiple on-shore and off-shore development teams and the delivery of multiple products and initiatives. The Director, Software Engineering provides strategic planning and tactical execution management, agile release planning across multiple teams, process and tool design, resource management, and continuous improvement. The role demands a blend of technical and business acumen, strategic and tactical focus, and an ability to balance architectural best practice and innovation pragmatism. In a typical business day, the Director, Engineering may find themselves pair-programming with developers on a priority feature or defect and briefing the C-suite on roadmap direction and key technical decisions.  

Responsibilities:

• Works with the SVP of Engineering to build a technical vision for the product line.
• Explores new technologies for future planning and potential implementation and evaluates and identifies appropriate technology to deliver business objectives.  
• Ensures engineering best practices are defined and met across teams and develops and governs technical standards to ensure adherence. 
• Collaborates with architects and principal engineers in the technical design of initiatives and business priorities. 
• Experience leading distributed or cross-functional teams globally, including recruiting, mentoring, and retaining team members in a continuous improvement environment. Provides leadership and professional growth with the goal to build our next generation of engineering leaders. 
• Extensive knowledge of enterprise architecture patterns, microservices, and distributed systems design 
• Experience with enterprise SaaS architecture and development in a product-driven environment, including multi-tenancy, scalability, and platform reliability at scale 
• Fluency in data architecture concepts including data models, data warehouses, analytical platforms, and modern data mesh or lakehouse patterns 
• Familiarity with service portfolio management, API governance, and technical debt prioritization at the enterprise level 
• Works closely with Product Management and Architecture to discover business requirements and technical approach for product initiatives and features. 
• Supports teams in the discovery and design of product backlog items and identifies and manages cross organization dependencies. 
• Develop Proof of Concept solutions to demonstrate technical design and can dive into the code and pair program with engineers as necessary.  
• Initiates and drives continuous improvement initiatives, challenges self and teams to continuously grow and achieve new levels of success. 
• Will be held accountable for the design, development, and delivery of Suvoda product and solutions.  
• A “team-player” with the ability to work within a highly collaborative environment. 
• A creative and critical thinker that is able to confidently express ideas in an articulate, concise manner. 

Requirements:  

• Bachelor’s degree in Computer Science, Information Systems, Mathematics, Engineering or equivalent relevant work experience and/or training. 
• At least 10 years of progressive experience in the software industry, including at least 5 years in a leadership position. 
• Proven experience delivering cloud-native applications on AWS, including IaC tooling (Terraform), container orchestration (EKS), and cloud cost optimization
• Good working knowledge of Python, Django ORM, Django REST Framework, and Angular for building and maintaining scalable backend and frontend services; hands-on familiarity with event-driven cloud service architectures leveraging AWS Lambda, DynamoDB, ElastiCache (Redis), and Postgres RDS 
• Strong experience managing people and teams; setting goals, providing clear technical direction, and holding teams accountable for delivering business value. 
• Strong experience with software development best practices and tooling, agile testing, developer operations, continuous integration and delivery, and site reliability engineering. 
• Relevant technical knowledge of enterprise architecture, cloud services, cloud development, containerization, business domain modelling, data warehouses and analytical platforms. 
• Proven experience in Agile Software Development methodology. 

Nice to Have:

• Hands-on experience adopting and governing AI coding assistants (e.g., Claude, GitHub Copilot, Cursor) across engineering teams, including establishing standards for responsible use, prompt engineering best practices, and measuring productivity impact
• Familiarity with Anthropic's Claude API or Claude Code for agentic developer workflows, including task automation, code generation pipelines, and AI-assisted code review
• Experience integrating LLM-powered tooling into the SDLC — such as AI-assisted test generation, documentation automation, or intelligent PR summarization
• Demonstrated ability to lead organizational change around AI adoption — including upskilling teams, establishing guardrails, and balancing developer autonomy with governance
• Familiarity with prompt engineering principles and the ability to coach engineers on effective human-AI collaboration patterns