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- 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: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Why this job: Lead transformative AI projects that make a real difference in business outcomes.
- Qualifications: Strong experience in AI frameworks, Python, and cloud platforms required.
- Other info: Dynamic team environment with mentorship opportunities and career advancement.
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.
- 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 employer: Cognizant
Contact Detail:
Cognizant Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer – Agentic & Generative AI Specialist
✨Tip Number 1
Network like a pro! Reach out to folks in the AI space on LinkedIn or at meetups. We can’t stress enough how important it is to make connections; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Agentic and Generative AI. We love seeing real-world applications of your work, so make sure to highlight any impactful use cases you've tackled.
✨Tip Number 3
Prepare for interviews by practising common AI-related questions and scenarios. We recommend doing mock interviews with friends or mentors to get comfortable articulating your thought process and technical expertise.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate individuals ready to dive into the world of AI with us.
We think you need these skills to ace AI Engineer – Agentic & Generative AI Specialist
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. Share specific examples of how you've delivered impactful AI solutions in the past.
Showcase Your Technical Skills: Don’t forget to mention your hands-on experience with Python, deep learning libraries, and cloud platforms. We want to see how you’ve applied these skills in real-world scenarios, so be specific!
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 brush up on your knowledge of Agentic AI frameworks like LangGraph and AutoGen. Be ready to discuss how you've used these technologies in past projects, as well as their business implications.
✨Showcase Your Technical Skills
Prepare to demonstrate your hands-on expertise with Generative AI and deep learning libraries. Bring examples of Q&A systems or retrieval-augmented generation pipelines you've built, and be ready to explain the technical details behind them.
✨Articulate Business Value
Practice explaining how your AI solutions can drive business outcomes. Think of specific use cases where you've identified high-value opportunities and how you communicated these benefits to stakeholders.
✨Engage in Consultative Conversations
Be prepared for a consultative approach during the interview. Think about how you would lead workshops or assessments to align AI strategies with organisational goals, and be ready to share your experiences in client-facing roles.
