Staff Software Engineer – AI

Hackajob Ltd; Leeds; On-site; GBP 61,000 - 101,000; Full time

Job summary

Hackajob Ltd in Leeds seeks a senior AI Platform Engineer to design, code, and lead delivery of scalable AI systems powering AI-powered products. You will contribute production code, guide technical direction, and partner across product, data science, and engineering teams.

You will mentor engineers, implement MLOps practices, and help shape reusable AI platforms while ensuring reliability, security, and cost efficiency in large-scale deployments.

Qualifications

• 8 years of experience in software engineering with backend systems and cloud-native services.
• Expert-level coding in Python, TypeScript, Go, or similar with production code contributions.
• Hands-on enterprise AI experience with LLMs, AI agents, retrieval‑augmented generation, and model optimization.
• Ability to balance performance, scalability, reliability, security, maintainability, and cost.
• Expert knowledge of AWS, GCP, or Azure with production Docker/Kubernetes usage.
• Experience with APIs, distributed systems, event-driven architectures, data pipelines, PostgreSQL, MongoDB, Redis, vector DBs.
• Mentoring engineers through design reviews, code reviews, debugging, and hands-on problem solving.
• Deep expertise in AI and leading innovation initiatives; governance and responsible AI.
• Experience using AI tools to drive innovation and impact.
• Leadership in managing AI risks and governance across the organization.
• Bachelor's degree or higher in CS, SWE, AI, or related field or equivalent practical experience.

Responsibilities

• Design, code, and lead delivery of scalable AI platforms and intelligent applications.
• Act as a hands-on technical leader, designing, coding, reviewing, debugging production AI systems.
• Design and build scalable backend services, APIs, data pipelines, and inference pipelines at enterprise scale.
• Implement advanced LLM applications using retrieval-augmented generation, prompting, evaluation frameworks, model optimisation, agentic workflows, and tool integration.
• Make key technical decisions while ensuring maintainability, performance, reliability, security, scalability, and cost efficiency.
• Establish engineering best practices through hands-on contribution, code reviews, testing, observability, and deployment.
• Champion MLOps practices including model lifecycle management, evaluation, and deployment pipelines.
• Partner with product managers, data scientists, ML engineers, and business stakeholders to translate priorities into solutions.
• Build reusable frameworks, libraries, tooling, and platform components to accelerate AI development.
• Evaluate emerging AI technologies through prototypes and production-readiness assessments; guide teams on patterns and trade-offs.
• Mentor engineers through coaching, pairing, reviews, and example-setting as a senior contributor.

Skills

Python

TypeScript

Go

AI applications

Cloud platforms

Education

Bachelor's degree or higher in CS/SWE/AI or related field

Tools

Docker

Kubernetes

PostgreSQL

MongoDB

Redis

Vector databases

Job description

Salary: £61,000 - 101,000 per year

Requirements:

• 8 years of experience in software engineering, with deep hands‑on experience designing, coding, testing, and operating scalable, resilient, production‑grade backend systems and cloud‑native services.
• Expert‑level coding capability in modern programming languages such as Python, TypeScript, Go, or similar, with the ability to personally contribute high‑quality production code while guiding technical direction.
• Deep hands‑on expertise building enterprise AI applications using large language models, AI agents, retrieval‑augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniques.
• Proven ability to take complex AI solutions from prototype to production, making practical engineering trade‑offs across performance, scalability, reliability, security, maintainability, and cost.
• Expert knowledge of cloud platforms such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure, with strong experience using Docker, Kubernetes, Elastic Container Service, or equivalent technologies in production environments.
• Strong experience designing and implementing application programming interfaces, distributed systems, event‑driven architectures, data pipelines, PostgreSQL, MongoDB, Redis, vector databases, observability, and automated deployment pipelines.
• Demonstrated ability to influence technical direction while remaining close to the codebase, mentoring engineers through design reviews, code reviews, pairing, debugging, and hands‑on problem solving.
• Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency.
• Strong experience using AI tools to lead innovation initiatives.
• Demonstrated leadership in managing AI‑related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization.
• Bachelors degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience.

Responsibilities:

• Design, code, and lead delivery of scalable AI platforms and intelligent applications that bring emerging AI capabilities into production.
• Act as a hands‑on technical leader, spending significant time designing, coding, reviewing, debugging, and improving production systems that support AI‑powered products and services.
• Design and build scalable backend services, application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real‑time and batch AI workloads at enterprise scale.
• Implement advanced large language model applications using retrieval‑augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration.
• Make key technical decisions while remaining accountable for practical implementation quality, including code maintainability, system performance, reliability, security, scalability, and cost efficiency.
• Establish engineering best practices through hands‑on contribution, code reviews, technical design reviews, automated testing, observability, monitoring, and operational excellence.
• Champion machine learning operations practices including model lifecycle management, prompt versioning, automated evaluation, deployment pipelines, monitoring, and continuous improvement.
• Partner with product managers, data scientists, machine learning engineers, engineering leaders, and business stakeholders to translate strategic priorities into robust, buildable technical solutions.
• Build reusable frameworks, libraries, developer tooling, and platform components that accelerate AI development across multiple teams without creating unnecessary abstraction or complexity.
• Evaluate emerging AI technologies through practical prototypes, proof‑of‑concept builds, and production‑readiness assessments, then guide teams on implementation patterns and trade‑offs.
• Mentor engineers through practical technical coaching, pairing, code reviews, design feedback, documentation, and example‑setting as a senior individual contributor.

Technologies:

• AI
• AI Agents
• Azure
• Backend
• Cloud
• Docker
• Support
• Kubernetes
• Machine Learning
• MongoDB
• PostgreSQL
• Python
• Redis
• Security
• TypeScript
• Web

More:

Our Digital Content and Innovation (DC&I) team builds next‑generation internal and external products powered by cutting‑edge artificial intelligence technologies, including large language models, AI agents, machine learning, and natural language processing. We bring together engineers, data scientists, and AI specialists to solve complex challenges and turn breakthrough ideas into practical products that enhance productivity, unlock insights, and create measurable business impact. Collaboration is central to how we work. Our engineers contribute across the full AI lifecycle, from experimentation and prototyping through to large‑scale production deployment, while helping shape reusable platforms, frameworks, and responsible AI practices. By joining our team, you will work on exciting challenges in applied AI, contribute directly to production code and architecture, and be part of a culture that values curiosity, innovation, knowledge sharing, and continuous growth.

last updated 40 week of 2026