About the job

We have one open position of AI Engineer with one of our client based in Dublin, Ireland. This is a permanent/fulltime/Contract/B2B position. Below is the full job description for your reference. Please share your application once you are interested

Role: AI EngineerMode: Permanent/Fulltime/Contract/B2BLocation: Dublin, Ireland(Remote with AdHoc travel to client office)

• Job Description:Position Responsibilities:As a part of Persistent Services, you will build innovative products that help businesses around the world unlock more value from their data. As a Senior Software Engineer within BE&O, you will contribute to full-stack, data-intensive, analytics-driven applications that support sophisticated business experimentation and decision-making for some of the world’s largest organizations. You will:Lead team level system design, including high level design, detailed design, API contracts, data flows, service interactions, integration patterns, and nonfunctional requirements such as scalability, reliability, performance, security, and operability.
• Partner with lead engineers and architects to align team level implementations with broader platform architecture, modernization goals, engineering standards, and long term maintainability.
• Develop and optimize data intensive applications and analytics capabilities using Databricks, Spark, and related technologies to process and deliver data at scale.
• Develop, and deploy AI-powered products, intelligent agents, and agentic workflows utilizing Large Language Models (LLMs), retrieval systems, orchestration frameworks, tool-calling patterns, and context-aware workflows.
• Implement advanced agentic systems incorporating planning, reasoning loops, memory management, grounding, evaluation frameworks, safety mechanisms, and human-in-the-loop controls.
• Identify and resolve performance bottlenecks across services, APIs, data processing workloads, and user experiences.
• Collaborate with cross-functional teams to translate business requirements into scalable technical solutions.
• Mentor junior and midlevel engineers through technical guidance, pairing, code reviews, design feedback, documentation, and knowledge sharing.
• Contribute to a collaborative engineering culture by modeling ownership, clear communication, continuous learning, pragmatic decision making, and high standards for software quality.
• Improve engineering quality through code reviews, design reviews, automated testing, secure coding practices, observability, performance tuning, CI/CD practices, and production readiness.
• Troubleshoot complex issues across application, service, API, data, and cloud layers, driving root cause analysis and implementing durable solutions that improve platform reliability and supportability.
• Ideal qualifications include:6+ years of software engineering experience delivering scalable, high performance, and reliable software in an agile environment.
• Strong hands on experience designing and building distributed systems, microservices, RESTful APIs, and cloud native applications.
• Strong programming experience with modern engineering stacks such as Java/Spring Boot, TypeScript/React, SQL, and related frameworks and technologies.
• Experience with Python, Databricks, Spark, or PySpark is highly desirable, particularly for working with data pipelines and analytics driven applications.
• Experience building or supporting cloud native applications on AWS and/or Azure, with familiarity in CI/CD, containerization, Kubernetes, observability, automated testing, and production support practices.
• Demonstrated ability to lead team level design discussions, evaluate technical tradeoffs, and guide implementation through technical influence.
• Ability to translate product and business needs into scalable, secure, and maintainable technical solutions.
• Strong collaboration and communication skills, with the ability to work effectively across cross-functional teams.
• Strong problem solving skills with the ability to work through ambiguity, make sound technical decisions, and drive results through hands on execution.

·        Generative AI and LLM Engineering: LLM Application Development, Retrieval Augmented Generation (RAG), Prompt Engineering, LangChain, LangGraph, AI Agents, Multi Agent Systems, Model Context Protocol (MCP), Hugging Face Transformers, OpenAI GPT, Anthropic Claude, Google Gemini, Meta Llama, Groq

·        Vector Search and Data Engineering: ChromaDB, FAISS, Pinecone, Sentence Transformers, Semantic Search, Python, SQL, PostgreSQL, Pydantic

·        Machine Learning and Deployment: Deep Learning, TensorFlow, PyTorch, Natural Language Processing, Computer Vision, FastAPI, SQLAlchemy, Alembic, Docker, Docker Compose, MLOps, Microsoft Azure, CI/CD

·        Analytics, Tools and Methods: Tableau, Power BI (DAX), Git, GitHub, JWT Authentication, REST API Design, Agile Delivery