Forward Deployment Engineer - Agentic AI

About Disseqt AI

Disseqt is the Assurance Layer for Enterprise AI Operations. One platform covers the full deployment lifecycle: pre-production testing, runtime policy enforcement, continuous post-deployment monitoring and compliance reporting.

AI agents are non-deterministic. They hallucinate. They produce unexpected outputs. They behave differently in production than in any test environment. They drift. They degrade. Enterprises deploying AI agents at scale have limited visibility into what those systems are doing after go-live. Legacy GRC tools were built for predictable software and cannot monitor what changes continuously.

Disseqt closes that gap. With regulations like the EU AI Act and ISO 42001 now mandating full lifecycle AI governance, enterprises using Disseqt are winning regulated deals, faster and with less risk.

About the role

We are hiring Forward Deployed Engineers (FDE) in Dublin Ireland to be the technical spearhead for integrating our Service as a software Enterprise Agentic AI Platform with our top-tier financial services clients.

Our FDEs are the critical bridge between our engineering team and the customer

environment, focusing on the safe, scalable, and transparent deployment of Agentic AI applications for IT Service Excellence. You will work with a modern, high-performance stack and contribute directly to cutting-edge MLOps practices, including intelligent server orchestration and automated testing driven by AI models.

This is a unique opportunity to shape the foundational production and deployment strategies for our core product and work directly with global financial services enterprises and their senior technical executives and heads of AI at the cutting edge of complex pre-sales cycles as technical lead and help deliver live deployments .

What you'll do

• Lead the pre sales and post sales technical deployment and be embedded in customer deployments for 3-12 months as part of the partner and customer teams onsite . This role will be face to face onsite providing the technical and architectural support these complex integration projects need to scale prototype to POC to stable enterprise production. Scope work, sequence delivery andremove technical blockers.
• Production Deployment & Integration: Lead the end-to-end deployment of our fully containerised AI platform within client environments, supporting both cloud (GCP, AWS) and on-prem deployments.
• Enable customers and partners on Disseqt Ai’s platform and usage for robust scalable testing, jailbreaking, Redteaming and vulnerabilities and addressing these.
• MLOps and Automation: Design and implement Git-based CI/CD pipelines and automated testing frameworks. Leverage our own Agentic AI models to create intelligent systems for server orchestration and system monitoring.
• Coding and Engineering: Write high-performance core services and orchestration logic using Golang. Develop, debug, and optimize the Python-based Machine
• Learning/AI service layer, which includes hybrid model ensembles (Deep Learning/Classical ML) for customer requests.
• Customer & Technical Leadership: Serve as the primary technical contact for customers, troubleshooting complex production issues, and providing detailed feedback to the core engineering team driving new feature research for R&D to build.
• ML Experimentation and Workflow: Implement and maintain model versioning, tracking, and governance using tools like MLflow and ClearML.

Qualifications

• Strong customer facing skills to work with a variety of roles from AI QA testers to heads of AI at financial institutions as well as liaising with the dev hub team of FDE’s and Disseqt developers in Bangalore on requests and bugs during projects .
• Core Engineering: 3+ years of professional experience in software engineering, with strong proficiency in Golang and Python.
• DevOps & Architecture: Expert-level knowledge of containerization technologies (Docker, Kubernetes) , on premise deployments and experience with infrastructure-as-code principles.
• Cloud Proficiency: Hands-on experience deploying and managing applications on at least one major cloud provider (Google Cloud Platform - Azure, GCP or AWS).
• MLOps Tooling: Experience with model experimentation, tracking, and versioning tools such as MLflow, ClearML, or similar.
• AI/ML Familiarity: Foundational understanding of the principles behind Deep Learning models (e.g., Transformers) and Classical ML models used in our validators.
• NB Must have the ability to travel between Ireland and the UK frequently and be resident in Dublin Ireland, we are not sponsoring visas or relocations from abroad

Bonus Qualifications

• Financial Services Experience: Prior experience working with or deploying solutions for enterprises in the financial services sector (e.g., banks, payment processors like Citibank or Visa ).

• Next-Gen AI Development: Familiarity with modern AI coding assistants and experimentation tools (Cursor, ChatGPT, Claude, Paperspace, Google Colab/Notebooks).
• Front-End Exposure: Working knowledge of modern web application frameworks like Next.js.
• Advanced AI/ML Ops: Direct experience with implementing or managing production systems that use Agentic AI models for operational tasks.