Senior Full-Stack AI Engineer

Senior Full-Stack AI Engineer

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Role Summary

We are seeking a
senior full-stack AI/ML engineer
with deep expertise in
agentic AI frameworks
such as LangGraph (or equivalent) and proven commercial experience building
complex, multi-agent systems
with more than at least four agents.

This role blends
cutting-edge AI research
with
hands-on deployment leadership
. You will design and optimise agent-based AI pipelines, deploy them into cloud and edge environments, and own the infrastructure that keeps them secure, scalable, and cost-efficient. You will be as comfortable in a Jupyter Notebook as you are in a Terraform config, with the ability to turn research ideas into production systems that run reliably in constrained environments.

Key Responsibilities

AI & Agentic Development

Architect, build, and optimise multi-agent AI systems using LangGraph or similar frameworks.

Integrate LLMs into agent workflows for search, reasoning, and automation at scale.

Conduct applied research in LLMs, NLP, and agent orchestration, with a focus on edge and offline deployments.

Build production-ready ML pipelines from ingestion to inference.

Infrastructure & Deployment

Implement, and maintain multi-account, multi-region AWS environments using IaC (Terraform, Helm, CloudFormation).

Manage Kubernetes clusters (EKS/OpenShift), service meshes, and container registries.

Implement GitHub Actions / Argo CD pipelines for automated, zero-touch deployments.

Lead security hardening efforts using GuardDuty, CloudWatch, IAM best practices.

Set up observability stacks for proactive monitoring and performance tuning.

Own backup, disaster recovery for services that you've created.

Cross-Functional & Process

Collaborate closely with other engineers, product managers and CTO.

Mentor engineers on agentic AI design best practices.

Present technical findings and research outcomes to technical and non-technical stakeholders.

Required Skills & Experience

MOD Security Clearance (or ability to obtain).

Commercial experience delivering LangGraph or equivalent agentic AI projects with more than four agents in production.

Strong grasp of multi-agent orchestration, memory, and tool integration.

Proficiency in Python for AI development and Bash/Go for automation.

Familiarity with AWS core services (EC2, VPC, IAM, S3, ALB/ELB, CloudFront, ECR/ECS, Elastic Beanstalk, Control Tower).

Familiarity with IaC (Terraform, Terraform Cloud, CloudFormation) and expertise in containerisation (Docker, Docker Compose).

Solid CI/CD engineering with GitHub Actions and/or Argo CD.

Preferred / Bonus

Research experience in edge AI or constrained/offline deployments.

MLOps experience (Sagemaker, Kubeflow, ZenML).

Experience building RESTful services around AI pipelines.

ISO 27001, NIST SSDF, OWASP SAMM, or GDPR compliance literacy.

Experience with AWS Karpenter, Prometheus, or similar observability stacks.

Soft Skills

Research-driven mindset, eager to experiment and iterate.

Able to bridge the gap between cutting-edge AI research and practical deployment.

Strong communicator with the ability to mentor and influence across teams.

Comfortable owning projects from concept through production deployment.

Why This Role?

You'll be working at the intersection of advanced AI research and real-world infrastructure, shaping how Oxford Dynamics brings agentic AI systems to production in challenging environments. If you thrive on building multi-agent systems, deploying them securely at scale, and experimenting with new ways to run AI at the edge, you'll find both the technical depth and creative freedom you're looking for here.