ജോലി വിവരണം

Role overview

This position is for a senior AI and machine learning engineer who will help turn generative AI ideas into production-ready products for a leading name in application security and traffic management. The work is deeply hands-on and focused on building dependable systems that perform reliably under real-world latency, scale, and uptime expectations.

The role sits within an expanding AI Core team in the UK. Rather than working on isolated experiments, you will own the systems and services that make GenAI usable in production, including multi-agent workflows, retrieval-augmented generation, anomaly detection, model fine-tuning, and the live inference layer that serves these capabilities.

This opportunity is best suited to someone who prefers shipping robust infrastructure over demo-only prototypes and wants measurable impact from systems that customers actually rely on.

Responsibilities

Develop and launch end-to-end generative AI functionality, covering model choice, fine-tuning, and the serving path that delivers results to users.
Architect multi-agent, retrieval-augmented generation, and anomaly detection solutions that remain accurate, observable, and cost-efficient as usage grows.
Own the real-time inference stack built on Triton and TensorRT, with a focus on reducing latency, increasing throughput, and improving GPU utilisation.
Build the supporting microservices in Python and FastAPI, ensuring they are containerised and deployed in a way that supports reliability.
Raise the engineering standard by contributing to architecture choices, improving code quality, and guiding other engineers.
Work closely with research and product stakeholders to move ideas from experimentation into customer-facing services.

Requirements

Between 5 and 10 years of relevant professional experience, including a demonstrated history of technical leadership and mentoring.
Strong Python engineering skills with recent experience building and delivering production services, preferably using FastAPI or a similar framework.
Practical, current experience with generative AI, including LLMs, RAG, agentic or multi-agent systems, anomaly detection, and fine-tuning methods such as LoRA or PEFT.
Hands-on real-time inference experience with NVIDIA Triton and TensorRT, with a solid understanding of latency, throughput, and cost trade-offs.
A microservices-oriented approach, with services built in Python and FastAPI and deployed in containerised, reliable environments.
Strong knowledge of Docker and Kubernetes, plus experience with distributed systems on a major cloud platform.
Must have the right to work in the UK.
Applicants from all backgrounds are encouraged, and the employer states a commitment to equal opportunity.
Nice-to-have experience: vLLM or similar serving frameworks; work in security, networking, or other high-reliability environments; big-data tools such as Spark, Databricks, or Snowflake; and modern MLOps practices.

Benefits

Genuine opportunity to build within an established AI Core team, rather than working on a prototype that never reaches production.
Fully remote working across the UK, with delivery outcomes valued more than physical presence.
Competitive pay, strong benefits, and a route to greater staff- and principal-level technical influence.
End-to-end backing from C-Serv during the hiring process and beyond, including full-cycle accountability.
A values-driven, woman-owned delivery partner with an emphasis on empathy, integrity, collaboration, and growth.

Additional information

This role is available as a full-time position and can be performed remotely anywhere in the UK. The employer is looking for a senior or staff-level engineer and places importance on production impact, technical ownership, and long-term growth into higher levels of influence.

Equal opportunity

The hiring team states that it welcomes applicants from all backgrounds and supports equal opportunity in hiring.

AI/ML Engineer