Senior Software Engineer (Forward Deployed)

TrueNorth®; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

TrueNorth® is seeking a Senior Forward-Deployed Engineer in London who will own the customer journey from discovery through deployment. This hands-on role requires building tailored demonstrations, validating model performance, and helping customers run real workloads in production.

You will interact with sales and engineering teams, design evaluations balancing quality, latency, and cost, and lead conversations with CTOs. Travel to customers weekly is expected.

Qualifications

• Hands-on experience with open-weight LLM post-training and tuning.
• Ability to ship models to production for real users.

Responsibilities

• Own the technical journey from discovery to deployment and adoption.
• Build tailored demonstrations and validate model performance for customers.
• Help customers deploy real workloads into production.
• Lead technical conversations with CTOs and commercial stakeholders.

Skills

LLM post-training

LoRA fine-tuning

Supervised fine-tuning

Model evaluation design

Python

GPU infrastructure

Containers

Ray

Kubernetes

CTO-level communication

Forward-deployed / applied engineering

Tools

Ray

Kubernetes

Job description

Senior Forward-Deployed Engineer - AI / LLMs - Early stage Start-up

London, with travel to customers weekly as required.

We’re supporting an AI Infrastructure start-up that helps organisations turn their own data into AI models and deploy them in their chosen environment.

As customers move into production, the team is hiring a Senior Forward-Deployed Engineer to own the technical journey from initial discovery through to deployment and ongoing adoption.

This is a hands-on engineering role with significant customer interaction. You’ll work alongside sales and engineering, building tailored demonstrations, validating model performance and helping customers get real workloads into production.

What we’re looking for:

• Strong hands-on experience with open-weight LLM post-training, including fine-tuning techniques such as LoRA and supervised fine-tuning.
• Experience designing evaluations and balancing model quality, latency and inference costs.
• A track record of shipping models into production for real users.
• Strong Python skills, with experience across GPU infrastructure, containers and distributed workloads using tools such as Ray or Kubernetes.
• Confidence leading technical conversations with CTOs and explaining trade-offs to commercial stakeholders.
• A background in forward-deployed, solutions or applied engineering, or a related role combining technical delivery with customer engagement.
• Based in London and able to travel to customers as needed.

Useful additional experience:

• Financial services or other regulated customer environments.
• Data residency and regulatory requirements.
• Working across multiple GPU providers and sizing workloads to hardware.