Software Engineer, GenAI Platform

Responsibilities

We are representing a leading on-demand logistics company seeking a Software Engineer to join their GenAI Platform team in London. In this role, you will build production infrastructure for Generative AI, with a primary focus on open-weights model platform spanning inference and fine-tuning.

Your responsibilities will include:

• Building infrastructure that helps product teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI
• Working on open-weights serving stack including real-time GPU endpoints, high-throughput batch inference, and fine-tuning (SFT/DPO/LoRA)
• Designing scalable, high-performance systems for model serving, batch inference, GPU autoscaling, and fine-tuning that power real customer and internal automation use cases
• Optimizing cost and latency of GPU inference, turning batch jobs that took days into hours and cutting inference cost by multiples
• Building platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, and operational excellence
• Partnering with ML engineers, product engineers, and data scientists to turn emerging GenAI capabilities into durable platform primitives
• Contributing to LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution systems

What We're Looking For

Required qualifications:

• BSc, MSc, or PhD in Computer Science or equivalent experience
• 3+ years of industry experience in software engineering
• Strong backend engineering fundamentals, especially in Python and distributed systems
• Experience building production services, APIs, data pipelines, or ML infrastructure at scale
• Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization
• Hands-on experience with LLM inference and/or fine-tuning of open-weight models in production
• Ability to work across ambiguous, fast-moving technical areas and turn customer use cases into reusable platform capabilities
• Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle

Preferred qualifications:

• Experience with LLM inference engines and serving frameworks (e.g., vLLM, SGLang, TensorRT-LLM) in production
• Experience with distributed/multi-node fine-tuning and training pipelines (SFT, DPO/RLHF, LoRA)
• GPU performance work including multi-node/distributed inference, KV-cache/memory optimization, quantization (FP8/INT8/AWQ/GPTQ)
• Experience with Kubernetes, cloud infrastructure (AWS/GCP), GPUs, or high-throughput batch systems
• Experience with LLM gateways, model routing, vendor abstraction, or cost attribution
• Experience building developer platforms or self-serve infrastructure
• Experience with eval systems, LLM observability, tracing, RAG, search, or vector databases

How We Work With You

When you apply through Get A Job.ai, our talent team will review your profile and conduct an initial screening to understand your background and career goals. If there's a strong match, we'll submit your candidacy to our client for their consideration. Please do not contact the client directly, as all communication regarding this opportunity will be managed through Get A Job.ai to ensure a smooth and professional process for all parties.

Pay

Compensation details will be discussed during the screening process based on your experience and qualifications.

Equal Employment Opportunity

Get A Job.ai is committed to fair and equitable recruiting practices. We welcome applications from candidates of all backgrounds and provide equal opportunity regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief.