AI Implementation Engineer in York

AI Implementation Engineer in York

York Full-Time 70000 - 90000 € / year (est.) Home office (partial)
Ema

At a Glance

  • Tasks: Lead the delivery of cutting-edge AI solutions and collaborate with diverse teams.
  • Company: Join Ema, a pioneering tech company transforming enterprise productivity with Agentic AI.
  • Benefits: Competitive salary, equity options, flexible work environment, and growth opportunities.
  • Other info: Dynamic startup culture with a focus on collaboration and continuous learning.
  • Why this job: Be at the forefront of AI innovation and make a real impact in customer success.
  • Qualifications: 5-8 years in technical implementation and strong coding skills in Python or Go.

The predicted salary is between 70000 - 90000 € per year.

Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale.

The AI Implementation Engineer owns the technical delivery and stabilization of Ema's agentic AI solutions in customer environments — from commitment through production rollout and steady state. This is a hands-on, post-sales, customer-facing engineering role: you build, you deliver, and you are the technical anchor the customer leans on. You are equally comfortable writing production code, debugging an integration the night before a go-live, walking a customer's VP of Operations through an architecture decision and translating a messy business problem into a feasible agentic workflow. You thrive in ambiguity, make abstract problems concrete, and reduce chaos rather than amplify it when things go wrong. You'll work closely with Value Engineering, Product, Engineering, Infrastructure, and the customer's IT and business teams to prove that agentic AI can be implemented responsibly — not heroically.

What You'll Work On

  • End-to-End AI Delivery Ownership
    • Own technical delivery from design alignment through production rollout and stabilization.
    • Configure, extend, and integrate Ema's agentic AI platform to meet customer requirements.
    • Ensure solutions align with Ema's agentic architecture and platform capabilities.
  • Hands-On Engineering
    • Write clean, efficient, maintainable code to build customer integrations, custom agents, and workflow extensions.
    • Build and maintain APIs (REST, gRPC) and integrations across enterprise SaaS systems.
    • Work with back-end languages such as Python and Go, and contribute to front-end interfaces (React/Angular, HTML, CSS, JavaScript) where customer-facing tooling is needed.
    • Work with data stores such as PostgreSQL, Clickhouse, Elastic, and Redis to shape scalable, extensible schemas for customer deployments.
  • Feasibility Judgment & Agentic Workflow Translation
    • Develop deep understanding of each customer's business processes, systems, and constraints.
    • Translate business workflows into feasible agentic AI workflows — and push back when something shouldn't be built.
    • Anticipate where AI implementations break: integrations, data quality, scale, edge cases.
  • Customer Leadership (Post-Sales)
    • Be the primary technical point of contact for customer business and IT stakeholders during implementation.
    • Coach customer teams and internal partners during high-stress phases — go-lives, incidents, scope changes.
    • Communicate progress, risks, and decisions clearly across technical and executive audiences.
  • Production Readiness & Stabilization
    • Stand systems up in multi-tenant SaaS environments and harden them for production.
    • Apply security best practices and enterprise integration patterns (auth, RBAC, audit, compliance).
    • Track success through adoption signals and outcome metrics — not just feature shipment.
    • Stabilize systems post go-live under real pressure.
  • Cross-Functional Collaboration
    • Coordinate across Ema Engineering, Product, Data, Infrastructure, and Value Engineering.
    • Feed customer learnings back into product and platform improvements.
    • Contribute to shared standards, delivery discipline, and reusable patterns across the implementation team.

Ideally, You'd Have

  • 5–8 years of relevant experience in technical implementation, post-sales engineering, solutions engineering, or hands-on software engineering with significant customer-facing exposure.
  • Bachelor's degree in Computer Science or related field.
  • Hands-on production experience with agentic AI, automation, LLM applications, or workflow orchestration platforms — beyond pilots.
  • Strong back-end engineering skills in Python and/or Go; solid foundations in algorithms, data structures, and object-oriented programming.
  • Experience designing and building APIs (REST, gRPC) and integrations across enterprise systems.
  • Working knowledge of databases (PostgreSQL, Elastic, Redis, Clickhouse) and front-end frameworks (React or Angular).
  • Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
  • Experience deploying and operating software in multi-tenant SaaS environments.
  • Understanding of security best practices and protocols for enterprise software.
  • Track record of owning customer-facing delivery end-to-end — production, scale, and accountability.
  • Background in fast-growing startups or enterprise platform companies.
  • Strong technical judgment, calm under pressure, and excellent written and verbal communication with both engineers and business stakeholders.
  • Experience working with global, distributed teams.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.

AI Implementation Engineer in York employer: Ema

Ema is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among top-tier talent from leading tech companies. With a strong focus on employee growth, Ema provides opportunities for hands-on experience in cutting-edge AI solutions while supporting a diverse and inclusive environment. Located in the heart of Silicon Valley, employees benefit from access to industry leaders and a vibrant tech community, making it an ideal place for those seeking meaningful and rewarding careers in AI implementation.

Ema

Contact Detail:

Ema Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Implementation Engineer in York

Tip Number 1

Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that AI Implementation Engineer role.

Tip Number 2

Prepare for those interviews by practising common technical questions and scenarios. We recommend doing mock interviews with friends or using platforms that simulate real interview conditions. It’ll help you feel more confident when it’s showtime!

Tip Number 3

Showcase your projects! Whether it’s GitHub repos or personal projects, having something tangible to discuss can really set you apart. We love seeing how candidates have applied their skills in real-world situations.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate individuals ready to dive into the world of agentic AI.

We think you need these skills to ace AI Implementation Engineer in York

Technical Delivery
Production Rollout
Hands-On Engineering
API Development (REST, gRPC)
Back-End Programming (Python, Go)
Front-End Development (React, Angular, HTML, CSS, JavaScript)
Database Management (PostgreSQL, Clickhouse, Elastic, Redis)

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the AI Implementation Engineer role. Highlight your relevant experience with agentic AI, coding skills, and customer-facing roles. We want to see how you fit into our mission!

Showcase Your Technical Skills:Don’t hold back on showcasing your technical prowess! Mention your experience with Python, Go, and any relevant frameworks or databases. We love seeing candidates who can demonstrate their hands-on engineering capabilities.

Communicate Clearly:When writing your application, keep it clear and concise. Use straightforward language to explain your past experiences and how they relate to the role. Remember, we value communication skills just as much as technical ones!

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at Ema!

How to prepare for a job interview at Ema

Know Your Tech Inside Out

As an AI Implementation Engineer, you'll need to be comfortable with various technologies like Python, Go, and APIs. Brush up on your coding skills and be ready to discuss your past projects in detail. Show them you can write clean, efficient code and explain complex concepts simply.

Understand the Customer's Business

Dive deep into the potential customer's business processes and challenges before the interview. Be prepared to discuss how you would translate their workflows into feasible AI solutions. This shows that you’re not just a techie but also someone who understands their needs.

Prepare for Real-World Scenarios

Expect to face questions about handling high-pressure situations, like go-lives or incidents. Think of examples from your experience where you successfully navigated chaos and stabilised systems. This will demonstrate your calmness under pressure and problem-solving skills.

Communicate Clearly and Confidently

Since this role involves liaising with both technical and non-technical stakeholders, practice explaining technical concepts in layman's terms. Clear communication is key, so be ready to showcase your ability to bridge the gap between engineers and business leaders.