Sr. Software Engineer, MarTech

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Sr. Software Engineer, MarTech based in the United States. Join a forward-thinking engineering team at the intersection of artificial intelligence, software development, and marketing technology. In this role, you will design, build, and deploy AI-powered applications that transform how marketing and sales teams operate. You will develop intelligent agents, machine learning pipelines, and advanced search solutions that improve prospecting, data quality, event engagement, and partner experiences. Working across digital marketing, revenue operations, and enterprise platforms, you will turn complex business challenges into scalable, measurable production solutions. You will also help establish responsible AI practices, strengthen system reliability, and integrate emerging technologies into existing workflows. This remote opportunity combines hands-on engineering, cross-functional collaboration, and technical mentorship to accelerate innovation across a global marketing ecosystem.

Discover and prioritize AI opportunities: Collaborate with marketing and sales stakeholders to identify, assess, and scope AI and machine learning use cases, defining success metrics linked to measurable business outcomes. Develop AI-powered applications: Design, build, and deploy LLM-based agents for event invitations, account and contact prospecting, partner workflows, and other marketing initiatives, incorporating orchestration and human oversight where appropriate. Improve lead and contact data quality: Develop machine learning and LLM-assisted pipelines to clean, deduplicate, enrich, validate, and score data across Salesforce, Marketo, and related platforms. Implement techniques to identify bots, fraudulent activity, and unreliable records. Modernize search and retrieval: Enhance website search and partner locator experiences using semantic and hybrid search, embeddings, and retrieval-augmented generation (RAG) grounded in approved content. Strengthen marketing analytics: Apply AI-assisted analysis to improve partner lead return-on-investment reporting and increase the adoption and effectiveness of Adobe Analytics. Establish evaluation and governance frameworks: Define performance metrics, evaluation methodologies, and regression tests. Monitor accuracy, latency, and operating costs while implementing personally identifiable information (PII) protections, consent enforcement, and audit logging in collaboration with Security, Privacy, and Legal teams. Evaluate emerging technologies: Assess AI tools, LLM platforms, and native capabilities within marketing technology ecosystems, making informed recommendations on whether to build, buy, or adopt existing solutions. Integrate enterprise platforms: Connect AI applications with Adobe Experience Cloud, Salesforce, Marketo, and other enterprise systems through APIs and event-driven architectures. Maintain production reliability: Implement monitoring, alerting, and operational procedures for AI services. Support incident response, maintain runbooks, and ensure solutions remain reliable and scalable. Collaborate across engineering teams: Coordinate with Adobe Experience Platform and infrastructure engineers on data access, development environments, and production releases. Drive AI adoption and enablement: Train and mentor engineers, marketing operations professionals, and sales stakeholders on AI tools, prompt engineering, and responsible AI usage. Develop workshops, reusable templates, and practical documentation to encourage effective adoption. Requirements Education: Bachelor's or master's degree in Computer Science, Data Science, or a related discipline, or equivalent practical experience. Professional experience: At least 5 years of software or data engineering experience, including 2 or more years deploying AI, large language model (LLM), or machine learning solutions into production. AI and agent development: Hands-on experience with LLM APIs, agent frameworks, prompt engineering, tool calling, and orchestration. Retrieval and machine learning: Practical knowledge of RAG, embeddings, vector or hybrid search, and machine learning techniques for entity resolution, classification, and scoring. Programming and APIs: Strong proficiency in Python and SQL, plus experience with TypeScript, JavaScript, or Java. Ability to develop and maintain RESTful APIs. Production evaluation and monitoring: Experience with AI evaluation methods, prompt and model versioning, regression testing, and production performance monitoring. Marketing technology knowledge: Familiarity with marketing operations in the high-tech industry and CRM or marketing automation data models, including leads, contacts, and accounts in platforms such as Salesforce and Marketo. Cloud and DevOps: Experience with a major cloud platform, such as AWS or Microsoft Azure, alongside CI/CD tools such as Jenkins or GitLab CI/CD and version control using GitHub. Data governance and responsible AI: Understanding of data governance, privacy regulations such as GDPR and CCPA, and responsible AI development practices. Communication and mentorship: Demonstrated ability to explain technical concepts clearly, train colleagues with different levels of technical expertise, and collaborate effectively across business and engineering teams. Organization and adaptability: Ability to balance project delivery with operational responsibilities, troubleshoot complex problems, and work during Pacific Time (PT) business hours. Preferred marketing technology experience: Familiarity with Adobe Experience Platform, Adobe Analytics, Adobe Target, Journey Optimizer, Adobe Experience Manager (AEM), Firefly, or GenStudio. Additional preferred technical skills: Experience with search platforms such as Elasticsearch, OpenSearch, or Algolia; data technologies such as Snowflake, Databricks, or Kafka; or sales technology tools for engagement, intent, and data enrichment. Additional advantages: Experience with bot and fraud mitigation, leading internal AI training programs, or holding relevant cloud or AI certifications. Benefits Competitive annual salary: Base salary ranging from $125,000 to $180,000 , depending on experience, skills, certifications, job level, and location. Performance-based rewards: Eligibility for bonuses and equity grants, subject to applicable compensation plans and terms. Comprehensive healthcare: Health insurance options designed to support employee well-being. Retirement savings: Access to a 401(k) plan. Paid time off: Paid leave to support personal commitments, rest, and work-life balance. Professional development: Opportunities to strengthen technical expertise, explore emerging AI technologies, and advance your career. Employee well-being: Programs supporting physical and mental health. Parental and adoption leave: Paid leave to support employees and their families. Inclusive workplace culture: Employee networks, community engagement opportunities, and initiatives that promote belonging and collaboration. Remote work flexibility: Work remotely from within the United States while collaborating with distributed teams. Innovation-driven environment: Opportunity to influence AI adoption, build impactful marketing technology solutions, and contribute to a culture of experimentation and continuous improvement.