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Agentic Solutions Architect

Job in Shelton, Fairfield County, Connecticut, 06484, USA
Listing for: BMG360
Full Time position
Listed on 2026-03-06
Job specializations:
  • IT/Tech
    AI Engineer, Data Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

We're hiring an Agentic Solutions Architect to be the technical expert and first point of contact for our clients' advanced AI, automation, and agentic workflow needs within the marketing data and analytics space. If you thrive on solving complex data and process automation challenges, deploying machine learning models, and designing elegant, autonomous solutions, this role is for you.

You'll be THE technical face to our clients—leading discovery sessions, architecting data and AI/LLM integrations, implementing automation solutions, and becoming their trusted advisor on all things Mar Tech, data analytics, and Generative AI. This is a hands‑on role: you'll design the agentic systems AND implement them, working across our data engineering, analytics, and product engineering teams to deliver high‑impact, automated client outcomes.

This is NOT a pure sales engineering or pre‑sales role. You own delivery. You'll get your hands dirty with LLM integration, prompt engineering, MLOps pipelines, data modeling, and designing autonomous workflow agents. You must also be comfortable in client meetings, translating ambitious business needs into technical blueprints for agentic solutions, and explaining complex AI/automation concepts to non‑technical stakeholders.

Perfect for someone who's done agency/consultancy work in the martech or data analytics space and is passionate about applying cutting‑edge AI and automation to solve real‑world client business problems.

Send your resume and a brief cover letter (or email) that includes:
  • 1.
    ** A client project you're proud of**:
    Describe the challenge, your solution, and the outcome. Be specific about your role and the technologies used.
  • 2.
    ** Your martech philosophy**:
    How do you approach integrating marketing platforms? What's your framework for designing data architectures?
  • 3.
    ** A time you had to explain something complex**:
    Give us an example of translating technical concepts for a non‑technical client. What was the situation and how did you approach it?
  • Please include:
    • • Links to any technical writing, presentations, or thought leadership
    • • Examples of dashboards, architectures, or solutions you've built (screenshots or case studies)
    • • Relevant certifications or technical credentials
WHAT YOU'LL DO
CLIENT-FACING TECHNICAL LEADERSHIP (50% of role)
  • First point of contact for client technical requests and advanced automation needs.
  • Lead client discovery sessions to understand business objectives and high‑leverage opportunities for AI, LLMs, and agentic workflows.
  • Design integrated data and AI architectures connecting marketing platforms to data warehouses and specialized LLM services.
  • Present technical recommendations and solutions to client stakeholders, focusing on the ROI of automation and agentic systems.
  • Troubleshoot integration issues, data discrepancies, and technical blockers across both traditional Mar Tech and new AI stacks.
  • Build trusted advisor relationships—clients should see you as their expert in Marketing AI and Automation.
SOLUTION DESIGN & IMPLEMENTATION (50% of role)
  • 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, Python, orchestration tools (e.g., Airflow, Prefect, Temporal), and LLM/AI services.
  • 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 sophisticated data segmentation.
  • Collaborate with data engineering team on MLOps and automation pipeline development.
  • Document technical solutions, agent architecture patterns, and best practices for reusable deployment.
  • Test and validate the accuracy and efficacy of automation and AI‑driven outputs.
REQUIRED EXPERIENCE:
  • 3‑5+ years in technical roles focused on marketing technology, data integration, or analytics.
  • Agency, consultancy, or client services background—you understand client delivery.
  • Deep hands‑on experience with:
    • Data warehousing (Snowflake, Big Query).
    • ETL/data integration tools (Glue, Air…
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