Job Summary
Avalara's Marketing Technology team is scaling its execution capabilities and expanding its AI capabilities to keep pace with a growing go-to-market engine. The systems that power campaign execution, lead lifecycle management, and marketing operations, Workfront, Marketo, and our leads pipeline, require strong, hands-on technical talent to build, maintain, and continuously improve them.
This IC4 MarTech Engineer role is for a strong technical leader who can transition marketing capabilities from a digital marketing paradigm to an agentic marketing approach by integrating, automating, and configuring new agentic models and solutions across our enterprise capabilities, building reliable integrations, automating marketing workflows, and ensuring lead data flows accurately from capture to CRM handoff.
Job Details
Build and maintain integrations
between Marketo, Salesforce CRM, Workfront, and adjacent MarTech systems, delivering reliable, well-documented solutions.Engineer and optimize the lead lifecycle
from capture and enrichment through scoring, routing, and CRM handoff, reducing lead leakage and improving data accuracy across the pipeline.Develop and maintain automation
for campaign operations, asset management workflows in Workfront, and lead management processes in Marketo, replacing manual effort with reliable, auditable automation.Translate business requirements into technical solutions
by working closely with Marketing Operations, Demand Generation, and Sales Operations to understand needs and deliver working solutions on time.Troubleshoot and resolve platform issues
across Workfront, Marketo, and the leads pipeline, performing root cause analysis and implementing fixes that prevent recurrence.Write clean, maintainable code and configurations
following team standards for API design, data handling, error management, and security best practices.Contribute to technical documentation
by keeping integration maps, data flow diagrams, and runbooks current so the team can operate and onboard efficiently.Support peers
through code reviews, knowledge sharing, and hands-on collaboration, raising the technical quality of the team's output.Monitor platform health
and proactively flag performance issues, data anomalies, or integration failures before they impact marketing operations
Qualifications
- B.S. in Computer Science, Engineering, or a related technical discipline.
8+ years
of hands-on experience in marketing technology, enterprise systems engineering, or a closely related technical discipline have recent hands-on work building AI/ML systems- Solid hands-on experience with
Marketo
, including program setup, smart list logic, API integrations, lead lifecycle configuration, and data management. - Hands-on experience with
Adobe Workfront
, including workflow configuration, template management, and automation for marketing or creative operations. - Experience building and maintaining
lead management pipelines
, including capture, enrichment, deduplication, and scoring. - Demonstrated production experience with LLMs, RAG pipelines, vector search/embeddings, or recommendation systems not prototypes, but systems that served real traffic
- Proficiency in Python, SQL, and JavaScript/Node.js, with experience owning AWS Lambda data pipelines from design to deployment.
- Experience with cloud infrastructure (AWS) and modern ML tooling (e.g., MLflow, SageMaker, or equivalents)
Bar Raiser Expectations
This role is a Bar Raiser hire. The successful candidate will:
- Hold themselves and others to high standards of technical quality, data integrity, and operational accountability
- Demonstrate strong judgment when making platform and technical tradeoffs, especially those that affect campaign performance, lead data quality, or system reliability.
- Raise the performance of those around them through mentorship, rigorous code reviews, and clear documentation.
- Simplify complexity, translating ambiguous marketing requirements into clean, maintainable technical solutions.
- Challenge assumptions respectfully and bring data into technical decisions.
- Leave every system, process, and team they touch stronger than they found it.
AI Expectations
AI Bar Raiser
Specifically, this role is expected to:
Use AI to accelerate development and troubleshooting
, including AI-assisted code generation, API debugging, and automated testing for MarTech integrations.Apply AI to lead intelligence
, leveraging AI/ML-based lead scoring and intent signal processing to improve pipeline quality and Sales efficiency.Automate content and campaign operations
using AI tools to reduce manual effort in asset creation, QA, and campaign setup within Marketo and Workfront.Identify and quantify AI-driven improvements
, e.g., reduction in lead processing time, improvement in MQL-to-SQL conversion, or hours saved through intelligent workflow automation.Share AI best practices
with the MarTech team and Marketing Operations, helping peers adopt AI tools responsibly and effectively.Apply AI responsibly
, with awareness of data privacy, governance, and ethical use standards relevant to marketing data and customer information.
