At a Glance
- Tasks: Build and develop cutting-edge AI systems for real financial data.
- Company: Join a forward-thinking tech company in Burgess Hill, UK.
- Benefits: Enjoy competitive salary, mentorship, and opportunities for growth.
- Other info: Work in a dynamic environment with a focus on innovation.
- Why this job: Make a real impact in AI while working with experienced professionals.
- Qualifications: Strong software engineering skills, especially in Python or Java.
The predicted salary is between 63000 - 77000 £ per year.
AI Engineer– Agentic AI
Location
Burgess Hill, UK
Employment Type
Full-time
About the Role
As an AI Engineer– Agentic AI, you will be a hands-on builder contributing to the development of production agentic AI systems that operate on real financial data and serve real customers.
You will work alongside experienced engineers, product managers, and designers to design, build, and ship AI-powered features, while learning how to operate within a regulated, customer-facing environment.
This role offers strong mentorship and opportunities to grow your technical depth in LLMs, agentic systems, and production AI engineering.
- Core engineering stack
- Languages: Python, Go, Type Script
- Cloud and infrastructure: AWS and/or GCP, Kubernetes
- APIs and services: REST, g RPC
- Distributed systems: event-driven architectures, including Kafka
- Orchestration Frameworks: Lang Graph, Lang Chain, Air Flow, etc
- Agentic AI and ML
- Integration of commercial and open-source LLMs into agentic workflows
- Agent and orchestration frameworks such as Lang Chain, Llama Index, Semantic Kernel, or Crew AI, with strong judgment about when to use frameworks versus building lighter-weight primitives
- Model-level work using Py Torch and the Hugging Face ecosystem (embeddings, fine-tuning, inference tooling), with some exposure to Tensor Flow
- Strong schema, validation, and state management practices using tools such as Pydantic (Python) and Zod (Type Script)
- AI-assisted development
- Use of AI-assisted and agentic development tools for design, implementation, testing, debugging, and refactoring
- Learning how to apply these tools responsibly while maintaining production-quality standards
- All systems are built to meet high standards for reliability, security, and auditability, reflecting the responsibility of deploying autonomous AI in a financial services environment.
- What You Need to Have to Be Considered
- Strong software engineering experience with
- Python (preferred) or Java
- Hands‑on experience with
- Large Language Models (LLMs)
, including
- Chat GPT/Open AI
- Google Gemini
- Anthropic Claude
- Experience building and integrating
AI Agents and business workflow automation solutions.
- Development and integration of microservices‑based architectures
- Strong understanding of event‑driven programming and distributed systems.
- Hands‑on experience with
Apache Kafka and messaging platforms.
- Experience working with
Enterprise Data Hubs and data integration platforms.
- Strong Postgre SQL database design and development skills.
- Experience with
AWS and/or GCP cloud platforms.
• Hands‑on expertise in
- Kubernetes
- Docker/Containers
- CI/CD pipelines
• Knowledge of
- Dev Ops
- Dev Sec Ops
- MLOps
- LLMOps
- Experience with Agentic AI frameworks and the Agentic Development Lifecycle (ADLC).
- Additional Eligibility Requirements
- Candidates must currently reside in the United Kingdom.
- Candidates must be available to start within four weeks of receiving an offer.
- Ability to work onsite in
- Burgess Hill, UK, three days per week
Preferred Domain Experience
Financial Services, Banking, Wealth Management, Fin Tech, Insurance, or other highly regulated industries.
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AI Engineer – Agentic AI employer: Cognizant
Cognizant is an excellent employer, offering a dynamic work culture that fosters innovation and collaboration within the UK Public Sector. Employees benefit from comprehensive growth opportunities, including training in cutting-edge AI technologies, while contributing to meaningful projects that impact government services. With a commitment to quality and excellence, Cognizant provides a supportive environment where your contributions are valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer – Agentic AI
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Cognizant or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Cognizant.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Cognizant.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Cognizant that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Engineer – Agentic AI
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Cognizant.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Cognizant and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Cognizant
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Cognizant uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
