At a Glance
- Tasks: Design and build production-grade AI applications that transform customer journeys.
- Company: Established fintech business in Greater Manchester with a focus on real-world AI solutions.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on upskilling and knowledge sharing.
- Why this job: Join a dynamic team at the forefront of AI innovation and make a tangible impact.
- Qualifications: Strong Python skills and experience with AI integration in production applications.
The predicted salary is between 80000 - 98000 £ per year.
Location: Greater Manchester (Hybrid, 2 - 3 Days On-Site)
We're working with an established fintech business in Greater Manchester that is doing something genuinely interesting with AI right now. Not pilots. Not proof of concepts gathering dust. Real, production-grade AI embedded into customer journeys and internal operations, and they're only just getting started. They've recently brought in a Head of Data and AI who has both the vision and the organisational backing to push this forward hard. A small team of agentic AI engineers is already in place. This hire sits right at the heart of that team.
The Role
This is a hands‑on senior engineering role focused entirely on applied AI. Model research and pure data science sit elsewhere. This is about taking foundation models, LLM services, orchestration frameworks, and existing ML capabilities and turning them into robust, production‑ready solutions that work at scale in the real world. Just as importantly, you'll be a genuine voice for AI across the business, helping technical and non‑technical colleagues alike understand what this technology can actually do.
What You'll Be Doing
- Designing and building production‑grade AI application patterns that bring together LLMs, retrieval systems, tools, APIs, and internal platforms into end‑to‑end solutions
- Building and improving agentic AI capabilities across customer‑facing and internal operational use cases, with a sharp focus on reliability, resilience, latency, and observability
- Owning AI architecture decisions and helping the team choose the right approach across vendor capabilities, orchestration frameworks, and integration methods
- Translating emerging AI capabilities into practical implementations, knowing where agentic workflows, tool use, RAG, and LLM‑based decision support genuinely add value
- Establishing and improving engineering practices across orchestration patterns, testing, evaluation, monitoring, guardrails, and release
- Educating and upskilling colleagues across the business, from engineers to operational teams, on what AI can do and how to work with it well
What You'll Need
- A strong software engineering background with excellent Python skills and solid discipline across code quality, testing, version control, and deployment
- Proven hands‑on experience integrating LLMs, AI services, or ML components into production applications
- Hands‑on experience with agentic AI frameworks, orchestration libraries, and workflow engines
- Strong working knowledge of application‑layer AI patterns: tool use, workflow‑based agents, RAG, structured outputs, fallback handling, and human escalation
- Experience designing robust API‑driven integrations between AI capabilities and wider engineering platforms and business systems
- A solid grasp of production AI concerns: latency, scalability, resilience, observability, regression testing, and safety controls
- Experience working in a governed or regulated environment where traceability and risk‑awareness matter
Bonus Points For
- AWS‑based AI and ML services and their integration into broader platform architecture
- Experience in financial services or another regulated sector
- Building conversational, assistant‑style, or autonomous workflow experiences
- Contributing to the wider AI or engineering community through talks, writing, or open source
Senior AI Engineer in Manchester employer: Inara
Join a forward-thinking fintech company in Greater Manchester that is at the forefront of AI innovation, where your contributions will directly impact real-world applications. With a hybrid work model and a culture that fosters collaboration and continuous learning, you'll have the opportunity to grow alongside a passionate team dedicated to pushing the boundaries of technology. The company's commitment to employee development and its dynamic work environment make it an exceptional place for those looking to make a meaningful difference in the AI landscape.
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We think this is how you could land Senior AI Engineer in Manchester
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We think you need these skills to ace Senior AI Engineer in Manchester
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Inara. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Inara
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Inara!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
