AI Engineering Manager
First seen by Alion on Oct 23, 2026.
Location: Remote (Full-time)
ExpoPlatform is the AI-powered events and 365 community platform used by the world’s leading conference and exhibition organizers. Make a real impact by joining a fast-paced and fast-growing company! ExpoPlatform’s technology is a complete Networking and Matchmaking and a turnkey Event Management System for online, hybrid, and in-person events.
The role
We're looking for a hands-on AI Engineering Manager who still writes code, reviews architecture and ships, while leading a team of engineers. You've already built an AI-driven development workflow, not just used one, and you know how to turn individual AI usage into a standardized, organization-wide engineering workflow with clear procedures, shared tooling and measurable outcomes.
You'll lead by example. Your own output is multiplied by AI agents, and you'll help every engineer on your team do the same, with measurable results.
What you'll do
AI-driven delivery
Own and evolve our AI SDLC: spec-driven development, agent-assisted coding, AI code review, automated testing and release.
Build reusable AI artifacts for the team: skills, prompts, agent configurations, MCP integrations, specs and templates that others pick up and use daily.
Set clear guardrails for AI usage: code quality, security, PII handling and when a human must stay in the loop.
Measure AI impact with real data (cycle time, throughput, defect rate, DORA) and target significant efficiency gains you can prove, not estimate.
Hands-on engineering
Stay close to the code: build prototypes, unblock hard problems, review PRs and take part in architecture decisions.
Support the migration from our PHP monolith to microservices, using AI to speed up code analysis, refactoring and test coverage.
Raise the technical bar through design reviews, RFCs, ADRs and post-mortems.
Leadership
Lead and mentor engineers, building a culture of ownership and accountability.
Coach engineers to work with AI agents effectively, moving them from occasional use to AI-first habits.
Run predictable, agile delivery: planning, prioritization and expectation management that reduce last-minute requests.
Track engineering health with SLOs, DORA and SPACE metrics and act on what they show.
Grow a proactive, bottom-up team where people bring ideas and automations, not only execute tickets.
Work closely with Product, Design and leadership to align execution with the roadmap.
Requirements
3+ years leading software engineering teams, with a strong hands-on engineering background before and during that time.
You still code. Solid experience with backend systems (PHP, TypeScript/Node.js or similar) and modern architecture: microservices, DDD, event-driven design.
Proven experience designing and rolling out an AI-assisted SDLC in a real team, not only personal use. Be ready to show what you built.
Daily, deep use of AI coding agents (Claude Code, Codex) and a clear view of where they help and where they fail.
Experience creating AI artifacts: specs, prompts, skills, agents or MCP-based integrations used by others.
Good grasp of how LLMs work in practice: context, hallucinations, evaluation, cost and security risks.
Experience with AWS or GCP, CI/CD pipelines and test automation.
Strong Agile delivery background and comfort with engineering metrics.
Excellent communication and stakeholder management in English.
Nice to have
Experience building internal automations with tools like n8n, AWS Lambda or agent frameworks.
Experience leading a legacy-to-modern platform migration.
Background in event tech, SaaS or marketplace products.
Public work you can share: talks, posts, open-source tools or internal playbooks on AI-driven engineering.
We offer
A real mandate to shape how a 50-person engineering organization builds software with AI.
Access to leading AI tools and the freedom to try new ones.
Fast professional growth in an international team.
A product with real demand, used by major event organizers worldwide.
Mon-Fri, 8 hours, semi-flexible.
Salary based on interview results.
Recruitment process
HR Intro Call
Interview with the Head of Engineering
Final Interview (CTO, if applicable)
Decision
Tech stack
- Team Leadership
- Backend
- AI coding
- AWS
- GCP
- CI/CD
- LLMs
- Microservices