AI/ML Full Stack Engineer

Berkley Group; Dublin; Hybrid; EUR 90,000 - 140,000; Full time

Job summary

Berkley Group is seeking a Senior Software Engineer to transition AI concepts into secure, scalable production applications. You will own end-to-end development from data ingestion to LLM-powered interfaces, with a strong emphasis on reliability, observability, and cost efficiency.

You will work across back-end, data, and front-end stacks (FastAPI, PostgreSQL, React) in a hybrid Ireland-based role, delivering robust AI-powered platforms and ensuring high SLA compliance.

Qualifications

• Senior software engineer with 5+ years in software engineering and 2+ years shipping production AI & LLM systems.
• Experience turning AI prototypes into enterprise-grade microservices with SLAs and resilience.
• Proficient in building async backends with FastAPI and streaming frontends with React/Next.js.

Responsibilities

• Production AI engineering and agentic workflows.
• POC-to-production conversion with automated fallbacks and on-call readiness.
• Design and implement multi-step autonomous workflows using function calls and tool graphs.
• Optimize performance and cost via caching, routing, and efficient data handling.
• Develop typed FastAPI backends with OpenAPI specs and observability.

Skills

AI/LLM Systems

Agentic Workflows

RAG Pipelines

PostgreSQL

Python

Frontend React

CI/CD

Cloud Platforms

Tools

Docker

Kubernetes

Terraform

GitHub Actions

FastAPI

pgvector

Weaviate

Milvus

Job description

Target Location: Ireland (Hybrid - Cork, Limerick or Dublin)

Role Type: Permanent - Excellent Salary + Benefits

Expertise Level: Senior (5+ Years Software Engineering | 2+ Years Production AI & LLM Systems)

Candidate Profile Summary

A Senior Software Engineer specializing in transitioning prototype AI concepts-including LLMs, multi-agent frameworks, RAG architectures, and Text-to-SQL interfaces-into secure, scalable, and cost-efficient production applications. Experience covers the complete software lifecycle: high-throughput data ingestion, vector retrieval optimization, agentic orchestration, API design, responsive frontend interfaces, CI/CD automation, and full-stack LLMOps observability.

Primary Expertise & Deliverables

Production AI Engineering & Agentic Workflows

• POC-to-Production Conversion: Experienced in taking research-grade AI prototypes and engineering them into enterprise-ready microservices with strict SLAs, automated fallback paths, and on-call resilience.
• Agent Orchestration: Architecting multi-step autonomous workflows using function calling, tool execution graphs, dynamic retries, timeouts, and circuit-breaker patterns.
• Advanced RAG Pipelines: Designing end-to-end retrieval frameworks-including adaptive document chunking, metadata filtering, hybrid search index strategies, cross-encoder re-ranking, and grounded generation.
• Performance & Cost Optimization: Implementing semantic caching, response caching, token usage budgets, and model routing to lower query latency and operational overhead.
• Asynchronous Backends: Building typed FastAPI applications with OpenAPI specifications, Pydantic DTOs, async I/O, rate limiting, connection pooling, and idempotent background processing.
• Modern Streaming Frontends: Developing React and Next.js interfaces optimized for streaming LLM responses, multi-step agent status tracking, complex state management, and continuous user workflows.
• Relational & Vector Data: Extensive work with PostgreSQL, pgvector, standalone vector databases, and SQL query tuning.

LLMOps, Reliability & Security

• Evaluation & Testing: Building continuous evaluation gates (CI eval gates, custom golden datasets, automated regression suites, trace replays) to prevent quality degradation prior to release.
• Full-Stack Observability: Instrumenting applications with OpenTelemetry to track token burn rates, cache hit ratios, end-to-end latency traces, and custom SLO/SLI metrics.
• AI Security & Governance: Applying defense-in-depth strategies against prompt injection, data leakage, and unauthorized tool invocation, while maintaining RBAC/ABAC and audit readiness.
• DevOps & Infrastructure: Containerizing workloads via Docker and Kubernetes, managing cloud infrastructure (AWS/Azure/GCP) using Terraform, and building automated GitHub Actions pipelines.

Core Technical Matrix

Domain

Key Technologies & Frameworks

AI / LLM Frameworks

RAG, Agentic Tool Chains, Multi-Agent Orchestration (LangGraph / CrewAI / AutoGen), Text-to-SQL, Structured Generation (Pydantic / JSON Schema)

Retrieval & Vector Search

Hybrid Search (Dense + BM25), Cross-Encoders, Semantic Caching, Re-ranking, pgvector, Milvus, Weaviate

Python 3.10+, FastAPI (Async), PostgreSQL, Task Queues (Celery / RQ / Arq), SSE, WebSockets, REST / OpenAPI

Frontend & UI

DevOps & Cloud

LLMOps & Observability

Security & Compliance

Prompt Injection Defense, DLP, Secrets Management (Vault / Cloud KMS), RBAC/ABAC, SOC2/ISO Alignment

Experience & Track Record

• 5+ years in full-stack web software engineering, backend service architecture, and cloud operations.
• 2+ years dedicated to shipping LLM-driven applications, RAG pipelines, and autonomous agent workflows to live production users.
• Proven history establishing testing strategies (unit, integration, contract, load testing), prompt versioning, canary deployment flows, and incident response playbooks.