Responsibilities

• Architect, build, and deliver solution architectures for content & digital platforms and the Marketing AI platform — hands-on writing production-grade backend code (Python, Node.js), APIs (REST/GraphQL), data pipelines, and infrastructure-as-code.
• Serve as Technical Lead for the end-to-end Azure-to-AWS migration of the Marketing AI platform — including service mapping, data migration, workload re-platforming, and cutover — and design the target-state AWS architecture using Bedrock, SageMaker, Lambda, Step Functions, ECS/EKS, API Gateway, DynamoDB, and EventBridge.
• Build and deploy agentic AI applications — autonomous marketing agents for content generation, audience segmentation, campaign orchestration, and real-time personalization — using frameworks such as LangChain, LangGraph, CrewAI, or custom orchestration, with proper governance including human-in-the-loop checkpoints and responsible AI practices.
• Support the north-star vision of automating end-to-end marketing workflows working with the Marketing AI & Innovation Engineering Lead — from insight generation and content creation through approval, distribution, channel activation, and performance measurement — to increase speed-to-market and enable personalized marketing at scale.
• Drive DevOps and cloud infrastructure — design and maintain CI/CD pipelines (GitHub Actions, CodePipeline, Jenkins), manage Infrastructure-as-Code (Terraform, CDK/CloudFormation), container orchestration (ECS/EKS/Kubernetes), serverless deployments, environment strategy (dev/staging/prod), and enforce best practices for automated testing, blue/green deployments, monitoring, logging, and incident response.
• Ensure platform security, compliance, and cost optimization — hands-on with IAM, secrets management, VPC/network security, encryption, and data privacy controls; monitor resource utilization, implement auto-scaling, right-size compute, and establish cost governance.
• Lead full-stack and backend engineering — design and build microservices, event-driven architectures, database solutions (PostgreSQL/RDS, DynamoDB/DocumentDB), data pipelines (AWS Glue, PySpark, Airflow), and AI/ML pipelines (SageMaker, Bedrock); build frontend components (React.js, TypeScript) as needed.
• Implement robust integration patterns connecting the Marketing AI platform and content/digital platforms with the broader ecosystem (Veeva, AEM, DAM, CRM, CDP, analytics tools) via APIs, event streams, and middleware such as MuleSoft or webMethods.
• Lead PoCs and pilots—from ideation to working prototype—for agentic marketing use cases (e.g., AI-driven personalization, automated MLR pre-checks, intelligent content repurposing), and scale successful pilots to production.
• Lead by example — actively contributing code, conducting architecture reviews, pair-programming, and providing hands-on technical mentorship to elevate team engineering quality and maintain alignment with architectural standards and best practices.

Requirements

• Bachelor's or Master's degree in Computer Science or a related field with 8+ years of hands-on IT engineering and architecture experience, including 6+ years in a hands-on technical architect / lead engineer role for content, digital, and/or AI platforms.
• 4-5 years of heavy backend engineering—building production-grade APIs, microservices, event-driven systems, and data pipelines using Python, Node.js, or Java.
• 4-5 years of hands-on DevOps and AWS cloud infrastructure—CI/CD pipeline design, Infrastructure as Code (Terraform, CDK/CloudFormation), container orchestration (ECS/EKS/Kubernetes), serverless architectures, and environment management—with demonstrated experience in cloud migration (Azure-to-AWS preferred) and/or AI/ML platform development.
• Strong full-stack capabilities—backend and DevOps as core strengths—with working proficiency in frontend (React.js, JavaScript/TypeScript) and hands-on experience with both relational (PostgreSQL, RDS) and NoSQL databases (DynamoDB, DocumentDB).
• Experience with AI/ML and GenAI - Amazon Bedrock, SageMaker, LLM-based application development, prompt engineering, RAG, and agentic AI frameworks (LangChain, LangGraph, CrewAI, or similar).
• Strong understanding of IT governance processes including data architecture, data privacy, cyber security reviews, risk assessments, Git-based workflows, and modern software engineering standards.
• Excellent communication and stakeholder management skills—ability to distill complex technical concepts into simple business language, present confidently to senior leaders, and work cooperatively across boundaries within a matrix organization.
• Familiarity with the Pharmaceutical Industry.

Preferred

• Digital marketing and commercialization domain experience—including MarTech ecosystems.
• AI/ML for marketing use cases—content personalization, audience segmentation, campaign optimization, and understanding of agentic AI architectures including multi-agent orchestration, tool-use patterns, and human-in-the-loop design.
• Experience with ETL tools (AWS Glue, Informatica) and integration platforms (MuleSoft, webMethods).
• Enterprise application integration experience - designing large-scale system-to-system integrations across CRM, ERP, CDP, CMS, MLR & DAM, using middleware, API gateways, event-driven architectures, and message brokers (Kafka, SQS/SNS), including enterprise integration patterns (EIP), iPaaS solutions, and integration architecture governance (API standards, versioning, SLA management, observability).
• Expertise in SDLC methodologies (Agile, Lean, Waterfall) and ability to manage business process analysis, cost-benefit estimation, and post-implementation KPI delivery.
• Ability to scan the technical landscape for leading-edge solutions, create business cases for new investments, and potential to develop into a recognized thought-leader for content, digital, and AI capabilities.