AI Engineer – Marketing Intelligence & Automation

Overview

Design and build the AI engineering layer behind SS&C Intralinks' AI-enabled marketing intelligence model, connecting marketing data, digital experiences, automation, and AI services into reusable, scalable systems.

What you'll do

• Design, build, evaluate, and maintain AI agents that retrieve trusted marketing and business context, analyze information, recommend actions, and execute approved workflows across marketing systems.
• Build services and pipelines that unify first-party marketing and CRM data, website behavior, campaign performance, search/AI visibility, intent signals, and attribution inputs into an accessible intelligence layer.
• Connect marketing, data, CMS, CRM, analytics, AI, and workflow platforms through secure APIs, event-driven integrations, and reusable services.
• Create RAG and related retrieval patterns that let AI systems work from approved messaging, product information, campaign assets, customer insights, brand standards, and governed enterprise knowledge.
• Help develop models and decisioning services that combine first-party and third-party signals to identify in-market accounts, prioritize opportunities, and recommend next actions.
• Build technical capabilities for adaptive website and digital experiences, including profile- and account-aware messaging, content recommendations, calls-to-action, and journey logic.
• Develop LLM-powered conversational experiences that engage and qualify visitors, answer questions using approved enterprise knowledge, route inquiries, and integrate with downstream sales and marketing workflows.
• Engineer data and AI services that improve multi-touch measurement, channel contribution analysis, pipeline intelligence, forecasting, and executive decision support.
• Build systems connecting AI-assisted content creation, governance, CMS workflows, structured data, localization/personalization, and distribution, with human review where required.
• Support SEO/AEO/GEO systems that monitor traditional and AI search visibility, structured data, content performance, citations, and optimization opportunities at scale.
• Create test harnesses, observability, quality controls, and evaluation frameworks for prompts, agents, models, workflows, and digital experiences.
• Codify successful patterns into components, templates, documentation, and playbooks that allow the broader Marketing organization to scale AI safely and consistently.

What you'll need

• 4+ years of experience in AI engineering, software engineering, data engineering, ML engineering, marketing engineering, or a similar role building production technical systems.
• Strong programming skills in Python and experience with JavaScript/TypeScript or another modern application language.
• Hands-on experience building with LLMs, including APIs, tool/function calling, structured outputs, prompt design, agent frameworks, and production evaluation.
• Experience designing RAG or enterprise knowledge-retrieval systems, including embeddings, vector search, metadata, chunking, permissions, and source grounding.
• Experience building data pipelines, APIs, event-driven integrations, and workflow automations across SaaS and enterprise platforms.
• Working knowledge of cloud architecture and data platforms; experience with AWS and Amazon Redshift is particularly relevant.
• Understanding of data modeling, identity resolution, data quality, observability, security, access controls, and governance.
• Systems thinker who favors durable architecture and reusable services over isolated scripts or one-off solutions.
• Able to translate ambiguous business problems into technical designs, prototypes, production systems, and measurable outcomes.
• Clear communicator who can explain architecture, tradeoffs, risk, and business impact to both technical and non-technical partners.
• Comfortable testing emerging AI capabilities while applying appropriate controls for accuracy, privacy, security, and brand risk.

Nice to have

• Experience with marketing technology, CRM, CMS, analytics, digital experience, or marketing automation platforms.
• Experience in B2B, enterprise software, financial technology, or regulated environments.

Details

• Location: Remote - Massachusetts, US.