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Purview is a global leader in IT Engineering and Talent Solutions, trusted by Fortune 500 and mid-market clients across 21+ countries. Headquartered in Edinburgh, with delivery centres in India, our 1,200+ professionals drive meaningful digital transformation worldwide.
As a certified Ethnic Minority Business and Premier Member of MSDUK, we proudly blend diversity with deep technical expertise to deliver results that matter.
We’re currently hiring for the below role with one of our valued clients. If it aligns with your experience and aspirations, we’d love to hear from you!
Key Responsibilities
- Engineer robust data and cloud foundations to support AI workloads and automation at scale across AWS environments.
- Design and implement agentic AI systems as part of a broader automation stack—developing self-orchestrating workflows, APIs, and reusable platform components.
- Build automation and observability solutions using Infrastructure-as-Code (Terraform/CDK) and modern monitoring frameworks.
- Integrate data pipelines with intelligent orchestration layers to enable autonomous experimentation and deployment.
- Collaborate across disciplines—partnering with data engineers, AI scientists, and platform specialists to embed AI capabilities into core operations.
- Champion responsible and scalable AI automation, ensuring compliance, reliability, and transparency by design.
Required Experience & Skills
- Strong software engineering background with Python, TypeScript, or similar languages.
- Proven experience building and automating cloud infrastructure using AWS (EC2, IAM, S3, Lambda, CloudWatch, etc.) and Infrastructure-as-Code tools (Terraform/CDK).
- Solid understanding of data engineering principles—pipeline design, data flow orchestration, and API integration.
- Experience with CI/CD pipelines and Git-based workflows.
- Demonstrated experience in use of AI tools (e.g., claude, Copilot, LangChain, agent frameworks) to enhance productivity.
- A self-driven, curious problem solver who experiments and iterates toward impactful solutions.
- Experience deploying or integrating agentic AI architectures, such as orchestration frameworks or autonomous agents.
- Knowledge of RAG pipelines, embeddings, and vector databases (e.g., Weaviate, Qdrant).
- Familiarity with Kubernetes/EKS and observability tools (New Relic, OpenTelemetry).
- Understanding of model hosting and optimization (vLLM, Triton, HuggingFace).
- Awareness of data governance and responsible AI practices in enterprise or regulated settings.
Key Skills
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