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For Companies At a Glance
- Tasks: Design and implement cutting-edge AI solutions using Agentic and Generative AI technologies.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Lead transformative AI projects that make a real impact on businesses.
- Qualifications: Experience in AI frameworks, Python, and strong consultative skills required.
- Other info: Dynamic environment with mentorship opportunities and a focus on ethical AI practices.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking an experienced AI Engineer who specialises in delivering end-to-end AI solutions using Agentic AI frameworks and Generative AI technologies. This role demands consultative skills, technical expertise, and the ability to identify impactful use cases and articulate business benefits while implementing scalable AI solutions.
Key Responsibilities
- Design and implement Agentic AI architectures for enterprise workflows.
- Integrate Generative AI capabilities (LLMs, multimodal models) into client solutions.
- Deliver end-to-end AI solutions from ideation to production deployment.
- Build, fine-tune, and evaluate LLM-based Q&A models using frameworks like AWS Bedrock, LangChain, HuggingFace Transformers, or OpenAI API.
- Design prompt templates and implement retrieval strategies to increase answer precision and factuality.
- Assist in creating data pipelines for training and testing, including annotation and evaluation tooling.
- Collaborate with product managers to translate user requirements into technical features.
- Participate in error analysis, iterative model improvement, and performance tuning.
- Document code and workflows clearly; follow best practices for reproducibility and code quality.
- Engage with clients to identify high-value AI use cases and define business benefits.
- Conduct workshops and assessments to align AI strategies with organisational goals.
- Provide thought leadership on AI adoption and emerging trends.
- Develop reusable frameworks and accelerators for Agentic AI and GenAI.
- Ensure compliance with AI ethics, security, and governance standards.
- Mentor junior engineers and guide cross-functional teams.
- Stay ahead of industry developments in Agentic AI, autonomous agents, and LLM ecosystems.
- Develop and deploy autonomous agents using Azure AI Agent Service, ensuring state management, memory persistence, and secure tool execution.
- Orchestrate complex multi-agent workflows to handle tasks requiring planning, reasoning, and tool use.
- Extend Microsoft 365 Copilot by building custom plugins and declarative agents within Microsoft Copilot Studio to surface enterprise data in Teams and Office apps.
- Operationalize AI solutions using Microsoft AI Foundry for model catalog management, Prompt Flow evaluation, and lifecycle governance.
- Architect scalable deployment patterns for agents using Azure Container Apps or Azure Functions, ensuring low-latency responses and cost-effective scaling.
Required Skills
- Strong experience in Agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI).
- Hands-on expertise with Generative AI (LLMs, prompt engineering, fine-tuning).
- Proficiency in Python and familiarity with deep learning/NLP libraries (LangChain, PyTorch, TensorFlow, HuggingFace Transformers).
- Experience with building Q&A systems and retrieval-augmented generation pipelines.
- Knowledge of vector databases or semantic search concepts.
- Familiarity with cloud AI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
- Knowledge of MLOps practices and deployment pipelines.
- Ability to articulate business value of AI solutions and drive client conversations.
- Experience with Git, collaborative development workflows, and cloud infrastructure (AWS, Azure, GCP, Domino).
- Experience building custom copilots and plugins using Microsoft Copilot Studio and integrating them with Power Platform connectors.
- Proficiency in deploying AI workloads to Azure Container Apps (ACA), Azure Kubernetes Service (AKS), or serverless functions (Azure Functions) for event-driven agent triggers.
- Experience implementing RAG using Azure AI Search (vector, semantic, and hybrid search) and OneLake/Microsoft Fabric.
Nice to Have Skills
- Certification: Microsoft Certified: Azure AI Engineer Associate or similar specialized training in Azure OpenAI.
- Experience implementing Azure Managed Identities, Private Endpoints, and Content Safety filters for enterprise-grade agent security.
- Familiarity with tracing agent thought processes (tracing chains/flows) and monitoring token usage in Azure Monitor/App Insights.
Consultative & Business Skills
- Excellent stakeholder management and communication skills.
- Ability to translate technical concepts into business outcomes.
- Experience in workshops, solution roadmaps, and executive presentations.
Education & Experience
- Bachelor's/Master's in Computer Science, AI/ML, or related discipline (or equivalent experience).
- Experience in AI solution delivery and client-facing consulting roles.
Why This Role Matters
Agentic AI and Generative AI are redefining automation and decision-making. This role offers the opportunity to lead transformative projects that combine autonomous agents, LLM-powered Q&A systems, and consultative expertise to deliver measurable business impact.
AI Engineer – Agentic & Generative AI Specialist in London employer: Cognizant
Contact Detail:
Cognizant Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer – Agentic & Generative AI Specialist in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI space, attend meetups, and join online forums. The more connections we make, the better our chances of hearing about job openings before they even hit the market.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Agentic AI and Generative AI. We want to see your work in action, so don’t be shy about sharing it on platforms like GitHub or your personal website.
✨Tip Number 3
Prepare for interviews by practising common AI-related questions and scenarios. We can even do mock interviews with friends or mentors to get comfortable discussing our experience and how we can add value to potential employers.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we often have exclusive roles listed there that you won’t find anywhere else.
We think you need these skills to ace AI Engineer – Agentic & Generative AI Specialist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the AI Engineer role. Highlight your expertise in Agentic AI frameworks and Generative AI technologies, as well as any relevant projects you've worked on.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI and how your background aligns with our mission at StudySmarter. Be specific about your experience with LLMs and how you can contribute to our team.
Showcase Your Projects: If you've worked on any AI projects, especially those involving Q&A systems or cloud platforms, make sure to include them. We love seeing practical examples of your work and how you've tackled challenges in the past.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Cognizant
✨Know Your AI Frameworks
Make sure you’re well-versed in Agentic AI frameworks like LangGraph and AutoGen. Be ready to discuss how you've used these technologies in past projects, as this will show your hands-on expertise and understanding of the role.
✨Showcase Your Problem-Solving Skills
Prepare to articulate specific use cases where you've identified impactful AI solutions. Think about how you can translate technical concepts into business outcomes, as this is crucial for engaging with clients and stakeholders.
✨Demonstrate Your Technical Proficiency
Brush up on your Python skills and be familiar with deep learning libraries like PyTorch and TensorFlow. You might be asked to solve a coding problem or discuss your experience with building Q&A systems, so be ready to dive into the technical details.
✨Engage in Thought Leadership
Be prepared to discuss emerging trends in AI and how they could impact the industry. Showing that you stay ahead of developments in Agentic AI and Generative AI will demonstrate your passion and commitment to the field.
