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.

WE’RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further.

Further is a data, cloud, and AI company whose focus is helping companies turn raw data into the right decisions. We have an award winning culture of extraordinary people. Our purpose is to enable people to thrive so that businesses can thrive. We believe that the work you do should matter - it should be meaningful to you professionally and personally, and it should have a positive impact on both you and our clients.  If this sounds exciting to you, let’s chat!

SENIOR AI ENGINEER

We are hiring a Senior AI Engineer to lead the development of our cloud-based (Google Cloud), commercial AI products. You will bridge the gap between experimental data science prototypes and production-grade software. You will architect the robust systems and LLMOps workflows necessary to transform AI models into reliable, enterprise-ready applications. By designing stable backend architectures and seamless integration layers, you will ensure our AI solutions are not just functional, but ethical, efficient, and high-value products that meet the rigorous demands of our commercial clients.

What experience should you have:

• 6+ years of software engineering experience with at least 3 years dedicated to AI/ML application development.
• Expert proficiency in Python AI application development and modern API architecture (REST, GraphQL, gRPC) using enterprise standards like static type checking and data validation.
• Deep experience building production applications with LLM frameworks such as LangChain, LangGraph or LlamaIndex.
• Hands-on expertise with vector databases (Pinecone, Weaviate, PostgreSQL) and search algorithms.
• Strong understanding of LLMOps principles, including model registry, versioning, and serving infrastructure specifically in Google Cloud.
• Experience in Typescript development for prototyping and integrations
• Proficiency with git workflows and understanding of standard application development processes

Preferred Qualifications

• Knowledge of advanced prompt engineering and fine-tuning techniques (LoRA, PEFT).
• Experience optimizing inference costs and latency for large-scale deployments.
• Previous experience in a client-facing consulting role, managing diverse stakeholders and navigating complex organizational structures.
• Any Google Cloud Professional Certification

What you’ll be doing in this role:

• Lead the implementation of rigorous evaluation frameworks to monitor model performance, drift, and cost in real-time.
• Architect and develop high-performance backend services and APIs using Python (FastAPI) to serve large language models at scale.
• Design advanced Retrieval-Augmented Generation (RAG) systems, selecting and managing vector databases and optimizing embedding strategies for accuracy and speed.
• Establish comprehensive model observability and guardrail systems to monitor real-time performance, detect distribution drift, and implement automated safety filters that mitigate hallucinations, bias, and toxic outputs in production environments.
• Build robust integration layers that connect AI agents securely to external enterprise systems, CRMs, and legacy databases.
• Conduct code reviews, provide technical guidance, and foster a culture of continuous learning and innovation within the engineering team.
• Collaborate with infrastructure teams to define deployment strategies, ensuring solutions scale dynamically under load.
• Define the end-to-end architecture for AI products on cloud platforms (preferably Google Cloud Platform), ensuring high availability, security, and cost-effectiveness.

What you’ll need to accomplish in your first year:

• Develop reusable internal libraries and architectural patterns and standards to accelerate the delivery of AI solutions across multiple client engagements.
• Mentor engineers on best practices for building deterministic software around probabilistic AI models.

Our total rewards program is designed for your protection, peace of mind, and overall well-being. In addition to our outstanding basics, we offer a net-zero cost medical option, company contributions to your HSA, fertility support, fully-paid parental leave, a monthly stipend for your lifestyle spending account, and much more.

Apply today or check out all our opportunities!

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