Software Developer; Python AI ML Specialist

This post sits within the Senior Software Engineer job family and provides specialist expertise in Python and AI/ML engineering day‑today. In this role, you will design, build, maintain and support robust software solutions that underpin our digital products and internal services. You will be responsible for developing and operating scalable data pipelines, APIs and cloud‑native infrastructure, and for applying AI/ML techniques, including OCR, large language models and computer vision, to automate processes and improve efficiency.

Working across the full delivery lifecycle, you will contribute to discovery, design, implementation, testing, deployment and ongoing support. You will collaborate closely with multidisciplinary teams, ensuring solutions are secure, reliable, maintainable and aligned to architectural and engineering standards, while continuously improving performance and user outcomes.

• Design, build, and operate scalable ETL and data pipelines handling structured and unstructured data for AI/ML workloads.
• Develop and maintain robust API services, including FastAPI, RESTful APIs, Web Sockets, model‑serving endpoints, integrating AI/ML capabilities with existing digital platforms.
• Implement authentication/authorization using JWT, OAuth 2.0, API keys, and maintain API versioning and documentation.
• Deploy and operate cloud‑native infrastructure using AWS Lambda, S3, RDS/Aurora, SQS, IAM, Cloud Watch, with infrastructure‑as‑code tools: CDK, Terraform, Cloud Formation.
• Containerize applications using Docker, orchestrate with Kubernetes (EKS/ECS), and maintain automated CI/CD pipelines.
• Implement monitoring and observability using Cloud Watch, Grafana, telemetry frameworks, including experiment tracking tools like MLflow and Weights & Biases.
• Research, prototype, and implement AI/ML solutions using Transformers/Hugging Face, PyTorch, OpenCV, PIL/Pillow, YOLO, including LoRA/QLoRA fine‑tuning, RLHF, and multi‑modal AI/ML systems.
• Collaborate with team members to optimise platform and AI/ML workflow performance, reliability, and scalability.
• Ensure compliance with security, accessibility, performance, and operational standards.
• Participate in agile ceremonies, contribute to team knowledge‑sharing, and support process improvements.
• Support disaster‑recovery procedures and maintain high‑availability, resilient system standards.
• Use Python 3.9+, object‑oriented programming, async/await, decorators, context managers, structured logging, pytest, performance optimisation.
• Process data with Pandas, Num Py, SQL, SQL Alchemy/psycopg2, ETL orchestration (Apache Airflow, Dagster).
• Apply AI/ML frameworks:
  Transformers/Hugging Face, PyTorch, OpenCV, PIL/Pillow, YOLO; model fine‑tuning (LoRA/QLoRA), RLHF, experiment tracking (MLflow, Weights & Biases).
• Develop web/API services:
  FastAPI, RESTful APIs, Web Sockets, authentication/authorization (JWT, OAuth 2.0, API keys), API versioning, documentation, model‑serving endpoints.
• Use cloud & Dev Ops tools: AWS Lambda, S3, RDS/Aurora, SQS, IAM, Cloud Watch; infrastructure as code with CDK, Terraform, Cloud Formation;
  Docker, Kubernetes (EKS/ECS); CI/CD pipelines.
• Monitor & observe:
  Cloud Watch, Grafana, telemetry frameworks for production systems.
• Design systems: event‑driven and microservices architectures, high availability, resilient systems, multi‑modal AI/ML systems.
• Follow professional software engineering practices:
  Git workflows, unit/integration testing, code review, agile delivery (Scrum/Kanban).

• Developing production‑grade AI/ML and data platforms, ensuring reliability, maintainability, and performance for public sector services.
• Designing, building, and operating scalable ETL/data pipelines handling structured and unstructured data.
• Delivering secure, cloud‑native AI solutions, integrating with existing infrastructure, managing lifecycle via IaC.
• Developing, supporting, and integrating APIs and microservices, including AI/ML model‑serving endpoints.
• Deploying and operating containerised applications in production, with automated CI/CD and environment management.
• Implementing monitoring, alerting, and incident response processes for…