Find Forward deployed engineer Jobs in Donnybrook, D

AI Native SW Engineer - Manager
Accenture —Dublin, County Dublin
- Full-time
- Java
- Master's degree
- AI
2d
Devops Engineer
Mifinity —Dublin, County Dublin
- Full-time
- Hybrid work
- DevOps
- AWS
- Scripting
- Free parking
Quick apply
Deployment Strategist - Polish Speking
Salesforce —Dublin, County Dublin
- Full-time
- Oracle
- Computer Science
- Sales
Engineering - Internal AI Transformation
ElevenLabs —Dublin, County Dublin
- Full-time
- Remote
- DevOps
- System design
- Master's degree
Product Manager
Siena AI —Dublin, County Dublin
- Full-time
- Remote
- Master's degree
- AI
GTM Automation Specialist
Supermetrics —Dublin, County Dublin
- Sales
- AI
Quick apply
LV Switchgear Field Service Engineer
Eaton —Dublin, County Dublin
- Continuous improvement
Senior Software Engineer, Forward Deployed AI Engineer
MongoDB —Dublin, County Dublin
- Hybrid work
- Azure
- Oracle
- Java

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Devops Engineer
Mifinity —Dublin, County Dublin
Remote work allowance post probation beginning at 3 weeks in year 1 and increasing with tenure. Continuous Development Program sponsoring further education…
Quick apply
Principal DevOps Engineer - Decision Management Platform
Mastercard —Dublin, County Dublin
In this role you will design systems to enable deployment and management of critical high-volume, low-latency financial systems into public and private cloud…

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AI Native SW Engineer - Manager

Accenture -
Dublin, County Dublin

Apply Now

Job details

Full-time
2 days ago

Qualifications

CI/CD
Law
Kubernetes
Java
Master's degree
Docker
Terraform
AI
Python
Debugging

Full job description

You build the systems that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent system in production, you have owned the eval harness, and you know what happens when your agent fails at 2am because you have lived it.

As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements.

This sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.

Key Responsibilities

Architect and govern production-grade agentic systems at enterprise scale: multi-agent orchestration across complex environments, RAG pipelines, policy-based routing, memory management, and programme-level lifecycle observability

Define RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure metric-backed tradeoff decisions are documented and transferable

Set multi-LLM integration standards: vendor-agnostic architecture by default, fallback routing and cost governance as standard design practice across providers including OpenAI, Anthropic, Vertex AI, and open-source models

Own LLMOps at programme scale: eval strategy, prompt governance, observability tooling standards, safety monitoring and cost controls across multiple concurrent systems

Lead client engineering engagements at senior level — facilitate architecture design sessions, lead proof-of-concept delivery, and drive alignment between client technology leadership and delivery teams

Shape and publish reusable patterns, accelerators, and engineering standards that scale across the practice and reduce ramp-up time on new client engagements

Own the measurement framework for agentic system quality: define accuracy, latency, safety, and cost metrics; present programme-level AI impact in business terms to senior client stakeholders

Extensive experience in software engineering in production environments

Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiable

Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level

Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs

RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering

LLMOps fundamentals: eval harness design, prompt versioning, and production observability

Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)

Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience

Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure

People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations

#LI-EU

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forward deployed engineer jobs in donnybrook, d

AI Native SW Engineer - Manager

Devops Engineer

Deployment Strategist - Polish Speking

Engineering - Internal AI Transformation

Product Manager

GTM Automation Specialist

LV Switchgear Field Service Engineer

Senior Software Engineer, Forward Deployed AI Engineer

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