The Core Engineering - AI Solutions Engineer (AI)

Location: London, Greater London, England, United Kingdom; office-based role

Company

hirify.global is a global investment banking, securities, and investment management firm with engineering teams supporting risk, reporting, compliance, treasury, and human capital functions.

What you will do

• Design, build, deploy, and operationalize cloud-native AI applications using modern software engineering, CI/CD, and automated testing.
• Partner with business and engineering stakeholders to identify high-impact AI opportunities and translate requirements into scalable architectures, data models, and technical specifications.
• Embed with internal business teams to map workflows, assess agentic automation opportunities, define approval boundaries, run pilots, and measure adoption.
• Integrate LLM APIs, retrieval-augmented generation, embeddings, vector search, structured outputs, response validation, and evaluation harnesses into production applications.
• Apply cloud, DevOps, observability, lifecycle management, and MLOps practices to deliver secure, resilient, cost-aware, and supportable systems.
• Document solutions, mentor receiving teams, and transfer code, integration patterns, data models, and operational practices into long-term ownership.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
• 9+ years of hands-on software engineering experience building, deploying, and supporting production applications.
• Strong proficiency in Python, Java, or Go, including software engineering, testing, data modelling, and system design.
• Experience translating complex business requirements into cloud-optimized architectures and scalable production solutions.
• Experience with forward-deployed or internal client-facing engineering, stakeholder engagement, rapid prototyping, pilot execution, adoption measurement, and production handoff.
• Extensive experience with AWS, Azure, or GCP and production AI/ML integrations, including RAG pipelines, embeddings, vector databases or search indexes, secure data access, deployment automation, and monitoring.

Nice to have

• Experience building agentic AI systems with multi-step planning, approved tool or API calls, state management, permission checks, failure handling, and auditable action trails.
• Experience with agent observability, trace capture, prompt and tool-call logging, hallucination checks, human-in-the-loop approvals, and incident handoff.
• Experience optimizing production AI systems through model routing, retrieval tuning, caching, batching, streaming, asynchronous execution, cost controls, and quality regression testing.

Culture & Benefits

• Access to training and development opportunities and firmwide professional networks.
• Benefits, wellness, personal finance, and mindfulness programs.
• Commitment to diversity, inclusion, and reasonable accommodations during the recruiting process.