AI Implementation Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Take charge of technical delivery from the alignment of design to the rollout and stabilization of production.

• Configure, extend, and integrate Ema's agentic AI platform to fulfill customer needs.

• Ensure that solutions are consistent with Ema's agentic architecture and platform capabilities.

• Write clean, efficient, and maintainable code to create customer integrations, custom agents, and workflow extensions.

• Develop and maintain APIs (REST, gRPC) and integrations across enterprise SaaS systems.

• Work with back-end programming languages such as Python and Go, and contribute to front-end interfaces (React/Angular, HTML, CSS, JavaScript) when customer-facing tools are required.

• Collaborate with data stores like PostgreSQL, Clickhouse, Elastic, and Redis to design scalable and extensible schemas for customer deployments.

• Gain a comprehensive understanding of each customer's business processes, systems, and constraints.

• Convert business workflows into practical agentic AI workflows and challenge any proposals that are not feasible.

• Predict potential issues in AI implementations related to integrations, data quality, scalability, and edge cases.

• Serve as the main technical point of contact for customer business and IT stakeholders during the implementation phase.

• Mentor customer teams and internal partners during high-pressure situations such as go-lives, incidents, and changes in scope.

• Clearly communicate progress, risks, and decisions to both technical and executive audiences.

• Set up systems in multi-tenant SaaS environments and ensure they are robust for production use.

• Implement security best practices and enterprise integration patterns (authentication, RBAC, audit, compliance).

• Measure success through adoption signals and outcome metrics, focusing on more than just feature delivery.

• Stabilize systems after going live under real-world pressure.

• Coordinate efforts across Ema Engineering, Product, Data, Infrastructure, and Value Engineering.

• Incorporate customer insights into product and platform enhancements.

• Contribute to shared standards, delivery discipline, and reusable patterns within the implementation team.

⛳️ Requirements

• 5–8 years of relevant experience in technical implementation, post-sales engineering, solutions engineering, or hands-on software engineering with substantial customer-facing exposure.

• A Bachelor's degree in Computer Science or a related field.

• Practical production experience with agentic AI, automation, LLM applications, or workflow orchestration platforms — beyond pilot projects.

• Proficient back-end engineering skills in Python and/or Go; a solid understanding of algorithms, data structures, and object-oriented programming principles.

• Experience in designing and building APIs (REST, gRPC) and integrations across enterprise systems.

• Familiarity with databases (PostgreSQL, Elastic, Redis, Clickhouse) and front-end frameworks (React or Angular).

• Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).

• Proven record of deploying and managing software in multi-tenant SaaS environments.

• Understanding of security best practices and protocols relevant to enterprise software.

• A history of taking ownership of customer-facing delivery from start to finish — including production, scalability, and accountability.

• Experience working in fast-paced startups or enterprise platform companies.

• Strong technical judgment, ability to remain calm under pressure, and excellent written and verbal communication skills with both engineers and business stakeholders.

• Experience collaborating with global, distributed teams.

🏝️ Benefits

• Health insurance

• Retirement plans

• Paid time off

• Flexible work arrangements

• Professional development