AI Implementation Engineer

Ovii's Interpretation of the Role

The AI Implementation Engineer drives end‑to‑end delivery of Ema’s agentic AI solutions for enterprise customers. This hands‑on, post‑sales role blends production‑grade software engineering with customer‑facing technical leadership to ship, stabilize, and scale AI‑enabled workflows.

Role Snapshot

• Customer‑facing technical delivery
• End‑to‑end AI solution implementation
• Production code & integration engineering
• Cross‑functional stakeholder coordination
• Post‑sales support & stabilization
• Cloud & multi‑tenant SaaS expertise

Must-Have Requirements

• Python
• Go
• REST API development
• gRPC
• React
• Angular
• PostgreSQL
• ClickHouse
• Elastic
• Redis
• AWS
• GCP
• Azure
• Docker
• Kubernetes
• Agentic AI workflow orchestration
• Security best practices
• Production‑grade software engineering
• technical implementation
• post‑sales engineering
• customer‑facing delivery
• Bachelor's degree in Computer Science or related field

Nice-to-Have Signals

• Background in fast‑growing startups or enterprise platform companies
• Experience working with global, distributed teams
• startup or enterprise platform background

Work Setup

• Location: London, United Kingdom
• Work mode: REMOTE
• Remote scope: COUNTRY_RESTRICTED
• Remote countries: United Kingdom
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility details beyond UK
• Notice period
• Travel requirements
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Own the full delivery lifecycle—from design alignment to production rollout and post‑go‑live stabilization
• Configure, extend, and integrate Ema’s agentic AI platform to satisfy customer requirements while adhering to platform architecture
• Write clean, maintainable code for custom agents, workflow extensions, and API integrations (REST, gRPC)
• Develop and manage data schemas using PostgreSQL, ClickHouse, Elastic, and Redis for scalable deployments
• Build and harden multi‑tenant SaaS environments on AWS/GCP/Azure, applying security, RBAC, and audit controls
• Serve as the primary technical liaison for customer business and IT stakeholders, coaching teams through high‑stress phases
• Translate complex business processes into feasible AI workflows and push back on unviable designs
• Collaborate across Engineering, Product, Data, Infrastructure, and Value Engineering to feed learnings back into the platform

Good Fit If You Have

• Comfortable working in ambiguous, fast‑paced environments
• Strong technical judgment and calm under pressure
• Excellent written and verbal communication with both engineers and business leaders