AI Engineer - European Portfolio

Aspire Software

We re looking for AI Engineers to build the technically complex systems that no-code tools can t handle across our portfolio SaaS companies. You ll tackle the hardest automation problems: CI/CD and security engineering, upstream developer tooling, AI product features, and log intelligence. You ll write production code, build infrastructure, and handle escalations from Automation/p>

Specialists when workflows require custom code or deep system integration.

WHAT YOU WILL DO

Developer Tooling & Ticket Quality

• Build AI pre-screening for incoming R&D tickets flag vague requirements, missing acceptance criteria, and ambiguous descriptions before developer assignment; root cause of downstream rework
• Automate ticket quantification and code impact analysis surface affected code areas and generate initial requirement breakdowns
• Automate the dev lifecycle upstream: requirements validation, ticket quality gates, and spec generation

Security Engineering

• Implement automated CI/CD failure analysis root cause identification, proposed fixes, and validated resolutions
• Run automated dependency vulnerability scans and implement validated fixes
• Deploy OWASP Top 10 automated scanning with proposed and validated security fixes
• Build log analysis (SIEM/CloudTrail) with smart anomaly alerting beyond what standard tooling provides
• Automate client security audit questionnaire completion from internal knowledge bases with mandatory R&D review before any submission

AI Product Features

Build and maintain AI-powered product features: LLM integrations, RAG systems, intelligent/p>

automation, and custom AI agents

Evaluate and integrate LLM providers based on cost, quality, and latency

Establish lightweight tooling governance new tools can be challenged and validated, not/p>

unilaterally adopted

Log Intelligence & Deployment Infrastructure

• Build AI-assisted log file collection, parsing, and pre-analysis to accelerate ticket resolution and reduce manual investigation time
• Automate CI/CD deployment pipelines and build error scraping and real-time KPI reporting pipelines

Knowledge Systems & RAG

• Build internal ticket knowledge systems from historical data pre-classification, pre-routing, and automated resolution infrastructure
• Consolidate product documentation; auto-suggest documentation updates when code changes

Production Infrastructure & Escalations

• Build and maintain production AI pipelines model serving, evaluation, monitoring, and shared infrastructure
• Handle complex escalations from Automation Specialists workflows requiring custom code or deep integration

• Strong software engineering in Python and/or TypeScript clean, tested, production-ready code
• Hands-on experience building and deploying LLM-based applications in production
• RAG architecture, prompt engineering, and AI evaluation frameworks
• API design, microservices, and CI/CD pipelines (GitHub Actions, GitLab CI)
• Security engineering awareness OWASP, dependency scanning, and SIEM tooling are a strong advantage
• Collaborative works with engineering teams, not as an isolated AI function

Nice to Have

• MLOps/LLMOps: model serving, evaluation, monitoring, and versioning
• Vector databases (Pinecone, Weaviate, Qdrant, pgvector)
• Infrastructure-as-code, container orchestration, multi-model architectures
• Experience with enterprise SIEM tooling (Wazuh, CloudTrail, or equivalent