7 hours ago
London, United KingdomSenior
Responsibilities
- Design and implement Agentic AI architectures for enterprise workflows.
- Integrate LLMs and multimodal models into client solutions and deliver AI systems from ideation through production deployment.
- Build, fine-tune, evaluate, and improve LLM-based Q&A models, prompt templates, retrieval strategies, data pipelines, and evaluation tooling.
- Develop autonomous agents with state management, persistent memory, secure tool execution, planning, reasoning, and multi-agent orchestration.
- Extend Microsoft 365 Copilot with custom plugins and declarative agents through Microsoft Copilot Studio, Teams, Office apps, and Power Platform connectors.
- Operationalize AI solutions using Microsoft AI Foundry, including model catalog management, Prompt Flow evaluation, and lifecycle governance.
- Architect and deploy scalable agents using Azure Container Apps, Azure Kubernetes Service, Azure Functions, and event-driven triggers.
- Implement AI security, ethics, governance, monitoring, error analysis, performance tuning, and reproducible engineering practices.
- Engage clients and stakeholders through use-case discovery, workshops, assessments, solution roadmaps, executive presentations, and business-value discussions.
- Develop reusable Agentic AI and GenAI frameworks and accelerators, provide thought leadership, and mentor junior engineers.
Requirements
- Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related discipline, or equivalent experience.
- Strong experience with Agentic AI frameworks such as LangGraph, AutoGen, and CrewAI.
- Hands-on expertise with generative AI, LLMs, prompt engineering, and fine-tuning.
- Proficiency in Python and familiarity with LangChain, PyTorch, TensorFlow, and HuggingFace Transformers.
- Experience building Q&A systems, retrieval-augmented generation pipelines, vector or semantic search solutions, and data or evaluation tooling.
- Familiarity with AWS Bedrock, Azure OpenAI, and GCP Vertex AI.
- Knowledge of MLOps practices, deployment pipelines, Git, collaborative development workflows, and cloud infrastructure across AWS, Azure, GCP, or Domino.
- Experience building custom copilots and plugins with Microsoft Copilot Studio and Power Platform connectors.
- Experience deploying AI workloads to Azure Container Apps, Azure Kubernetes Service, or Azure Functions.
- Experience implementing RAG with Azure AI Search and OneLake/Microsoft Fabric.
- Ability to articulate AI business value, lead client conversations, manage stakeholders, conduct workshops, and translate technical concepts into business outcomes.
- Preferred: Microsoft Certified: Azure AI Engineer Associate or similar Azure OpenAI training.
- Preferred: experience with Azure Managed Identities, Private Endpoints, Content Safety filters, Azure Monitor, and App Insights.
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About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.