AI Native Software Engineering

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

Job summary

Hackajob Ltd is seeking an AI Engineer (Software) in the United Kingdom to design, build, and ship production‑grade full‑stack software for real client programs across industries, connecting application layers to agentic AI systems and enterprise AI pipelines. You will use AI coding assistants daily, integrate LLM APIs in live code, and lead AI-driven delivery across Agile sprints with client teams.

Accenture is cited as a direct partner, offering exposure to enterprise tech stacks and a path

Qualifications

• Bachelor's degree in CS/CE/SWE or related field.
• Commercial software engineering experience in production or equivalent demonstrated via projects.
• Proficiency in Python, Java, or TypeScript.
• Hands-on AI tools usage in day-to-day engineering work.
• Experience calling LLM APIs in production code; token management and latency awareness.
• Basic understanding of web tech: JavaScript, HTML, CSS.
• Familiarity with AWS/Azure/GCP, Docker, and CI/CD pipelines.
• Understanding of Agile delivery fundamentals.
• Experience with databases (SQL or NoSQL).
• Ability to validate and improve AI outputs and understand AI limitations.
• Familiarity with agentic system concepts (LangChain, LangGraph, RAG).

Responsibilities

• Use AI coding assistants daily with demonstrable impact on productivity and output quality.
• Integrate LLM APIs into production apps, manage token limits and latency, build abstraction layers.
• Apply AI across the full software delivery lifecycle: AI tests, debugging, and prompt engineering.
• Own the quality of AI-generated outputs and assess reliability and failure modes.
• Define and track KPIs to evaluate AI-driven workflows and present metrics.
• Own end-to-end delivery in Agile sprints with client engineering teams.
• Contribute to shared knowledge bases and internal AI tooling standards.
• Build and connect application layers, APIs, and interfaces to agentic backends.

Skills

AI tooling usage

LLM API integration

Python

Java

TypeScript

Web fundamentals

Cloud fundamentals

CI/CD

Agile delivery

Database knowledge

Agentic AI concepts

Education

Bachelor's degree in CS/CE/SWE or related field

Tools

LangChain

LangGraph

Docker

SQL/NoSQL

AWS

Azure

GCP

Job description

Salary: £61,000 - 101,000 per year

Requirements

• We require a bachelors degree in Computer Science, Computer Engineering, Software Engineering, or a related field.
• We require commercial software engineering experience in production environments, or equivalent experience demonstrated through academic projects, internships, or shipped personal projects.
• We require proficiency in at least one primary backend language: Python, Java, or TypeScript.
• We require hands-on experience using AI tools actively in day-to-day engineering work, including practical examples of solving real problems, iterating on outputs, and improving delivery.
• We require direct experience calling LLM APIs in production code, with an understanding of token management, latency, and cost tradeoffs.
• We require a basic understanding of web technologies including JavaScript, HTML, and CSS.
• We require familiarity with cloud fundamentals such as AWS, Azure, or GCP, containers such as Docker, and CI/CD pipelines.
• We require understanding of Agile delivery fundamentals.
• We require experience with databases, SQL or NoSQL.
• We require the ability to validate, evaluate, and improve AI-generated outputs, and an understanding of AI limitations and responsible use.
• We require familiarity with agentic system concepts, including orchestration frameworks such as LangChain, LangGraph, or equivalent, RAG pipelines, and how full-stack applications connect to agent-based architecture; production experience is preferred, and conceptual understanding is required.

Responsibilities

• We use AI coding assistants daily as a standard part of delivery, actively and frequently, with demonstrable impact on productivity and output quality.
• We integrate LLM APIs into applications in production, including calling AI provider APIs in live code, managing token limits and latency, and building initial abstraction layers.
• We apply AI across the full software delivery lifecycle, including AI-generated tests, AI-assisted debugging, AI-accelerated code review, and prompt engineering for development tasks.
• We own the quality of AI-generated outputs in our delivery scope and exercise engineering judgment about reliability, limitations, and failure modes.
• We define and track KPIs to evaluate the effectiveness and ROI of AI-assisted workflows, and present AI productivity and quality metrics to project stakeholders.
• We own delivery end-to-end from design through production support in Agile sprint cycles alongside client engineering teams.
• We contribute to shared knowledge bases, reusable components, and internal AI tooling standards that benefit the wider team.
• We build and integrate the application layers, APIs, and interfaces that connect full-stack systems to agentic backends, understanding data flows, context handoffs, and integration points between our code and AI pipelines.

Technologies

• Agentic AI
• AI
• AWS
• Azure
• Backend
• CI/CD
• Cloud
• CSS
• Docker
• GCP
• Support
• Java
• JavaScript
• LLM
• NoSQL
• Python
• RAG
• SQL
• TypeScript
• Web

More

We are partnering directly with Accenture to hire for this role. We are building the next generation of AI-native engineering talent: engineers who use AI as a core part of how they work, not as an add-on. As an AI Engineer (Software), you will help design, build, and ship production‑grade full‑stack software for real client programs across industries, connecting application layers to agentic AI systems and enterprise AI pipelines. This is a core engineering role with a direct pathway to the Forward Deployed Engineer program for those who develop agentic depth. We offer breadth across industries and enterprise technology stacks, along with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams, structured AI certification pathways, and a clear development track toward agentic and forward‑deployed engineering. Accenture is a leading global professional services company with approximately 791,000 people serving clients in more than 120 countries. We combine strength in technology, cloud, data, and AI with deep industry experience and global delivery capability, helping clients reinvent and build trusted, lasting relationships. We are committed to creating 360 value and to an inclusive workplace where our diversity helps us better serve our clients and communities.

last updated 40 week of 2026