Find Software engineer ai tooling Jobs in Dublin, D

AI Native SW Engineer
Accenture —Dublin, County Dublin
- Full-time
- Java
- Master's degree
- AI
10d
Director of Engineering - Generate
RWS Group —Dublin, County Dublin
- Full-time
- Microsoft Excel
- No degree
- Agile
5d
Enterprise Solutions Engineer, Service Management
Asana —Dublin, County Dublin
- €77,000–€98,000 a year
- Sales
- IT
- AI
- Work from home
Quick apply
12d
Lead SRE - Chase UK - Dublin
JPMorganChase —DUBLIN 2, County Dublin
- Full-time
- Java
- AWS
- AI
9d
Director of Cloud, Enterprise Operations
Mastercard —Dublin, County Dublin
- Full-time
- Azure
- DevOps
- English
5d
Senior Lead SRE (DSS)
JPMorganChase —DUBLIN 2, County Dublin
- Full-time
- Azure
- Oracle
- Java
12d
Product Manager - Quality and Regulatory Systems
Life Scientific —Dublin, County Dublin
- Hybrid work
- Product management
6d
Senior Data Engineer
Datavant Ireland —Dublin, County Dublin
- Remote
- Azure
- SQL
- AWS
Quick apply
11d
Applied AI / ML Lead Software Engineer — Employee Platforms
JPMorganChase —DUBLIN 2, County Dublin
- Full-time
- Engineering
- Master's degree
- AWS
2d
Product Software Engineer (Brightflag)
Wolters Kluwer —Dublin, County Dublin
- Full-time
- Remote
- Java
- SQL
- AWS
- Life insurance
3d
Lead Software Engineer- Backend
JPMorganChase —DUBLIN 2, County Dublin
- Full-time
- Computer Science
- DevOps
- System design
2d
Data Engineer
Primark —Dublin, County Dublin
- Azure
- SQL
- Analysis skills
3d
Technical Lead - Commerce Hub
Fiserv —Dublin, County Dublin
- Full-time
- DevOps
- Java
- AWS
3d

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AI Native SW Engineer

Accenture -
Dublin, County Dublin

Apply Now

Job details

Full-time
10 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

Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability

Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets

Integrate and abstract across multiple LLM providers — OpenAI, Anthropic, Vertex AI, and open-source models — with fallback routing, token, cost, and latency management

Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring

Embed directly with client engineering teams to design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with sessions, and architecture walkthroughs

Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster

Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms

Software engineering experience 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

#LI-EU

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Refine Your Search

software engineer ai tooling jobs in dublin, d

AI Native SW Engineer

Director of Engineering - Generate

Enterprise Solutions Engineer, Service Management

Lead SRE - Chase UK - Dublin

Director of Cloud, Enterprise Operations

Senior Lead SRE (DSS)

Product Manager - Quality and Regulatory Systems

Senior Data Engineer

Applied AI / ML Lead Software Engineer — Employee Platforms

Product Software Engineer (Brightflag)

Lead Software Engineer- Backend

Data Engineer

Technical Lead - Commerce Hub

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