Responsibilities
- Serve as the first point of contact for client technical requests and advanced automation needs
- Lead client discovery sessions to identify high-leverage opportunities for AI, LLMs, and agentic workflows
- Design integrated data and AI architectures connecting marketing platforms to data warehouses and LLM services
- Present technical recommendations to client stakeholders, focusing on the ROI of automation and agentic systems
- Troubleshoot integration issues, data discrepancies, and technical blockers across AI stacks
- Build trusted advisor relationships: clients should see you as their go-to expert in AI and Automation
- Design end-to-end agentic data and workflow architectures: data sources → automation platform / LLM → actions / dashboards
- Implement integrations and automation using tools like n8n, Make, Flowise, AWS Step Functions, custom APIs, and orchestration platforms (Airflow, Prefect, Temporal)
- Design and deploy agentic workflows for automated marketing tasks, data quality checks, and predictive analytics
- Develop and fine-tune LLM applications for data enrichment, content generation, and data segmentation
- Collaborate with data engineering teams on MLOps and automation pipeline development
- Document technical solutions, agent architecture patterns, and best practices for reusable deployment
- Test and validate the accuracy and performance of automation and AI-driven outputs
Requirements
- 5+ years of experience in technical roles focused on software engineering, data integration, or analytics
- Agency, consultancy, or client services background with a strong understanding of client delivery
- Deep hands-on experience with data warehousing platforms such as Snowflake and BigQuery
- Proficiency with ETL / data integration tools including Glue, AirByte, Python, and custom APIs
- Strong SQL skills and experience with data modeling
- Proficiency in Python for scripting, data manipulation, and deploying AI / ML models
- Proven experience working with AI / ML / LLM technologies in a data or workflow automation context
- Client-facing experience including leading discovery sessions, presenting solutions, and managing stakeholder expectations
- Familiarity with cloud platforms (AWS, GCP, or Azure) and their AI / ML services
- Understanding of Generative AI use cases and prompt engineering best practices
- Strong written and verbal communication skills in English
Benefits
- Competitive salary and bonuses, including performance-based salary increases.
- Generous paid-time-off policy
- Flexible working hours
- Work remotely
- Continuing education, training, conferences
- Company-sponsored coursework, exams, and certifications
Compensation
Competitive salary and bonuses, including performance-based salary increases.
Additional Information
- Work remotely
- Flexible working hours
- Strong written and verbal communication skills in English
