• Design, develop, and deploy autonomous AI agents capable of reasoning, planning, and executing complex business workflows • Build and orchestrate agent-based solutions using LangChain, LangGraph, and modern AI agent frameworks • Develop scalable backend services, APIs, and integrations using Java and Python • Integrate AI agents with enterprise systems, databases, third-party APIs, and SaaS platforms • Design and implement advanced prompt engineering, memory architectures, and tool-use capabilities • Deploy, monitor, and optimize AI agents in production environments for performance, reliability, and cost efficiency • Establish evaluation frameworks, testing strategies, logging mechanisms, and feedback loops to continuously improve agent behavior • Design cloud-native AI architectures leveraging Azure AI and Machine Learning services • Collaborate with product, engineering, and data teams to embed AI capabilities into business-critical applications • Troubleshoot complex technical issues across AI, application, integration, and cloud environments • Provide technical leadership, conduct architecture reviews, and mentor engineering teams • Stay current with emerging AI technologies, LLM advancements, agent frameworks, and industry best practices • Ensure successful delivery of AI solutions that meet business, scalability, security, and operational requirements.

• Designing and delivering robust, scalable, and secure technical solutions across corporate platforms and customer‑facing services. • Translating requirements into high‑quality technical architectures that can be built, operated, and supported with confidence. • Working closely with delivery teams to support implementation, including knowledge transfer and hands‑on assistance where needed. • Participating in the architecture peer review process, helping maintain high design quality across the practice. • Presenting technical designs to the Technical Assurance Board and supporting assurance discussions with specialist knowledge. • Contributing to technology roadmaps, investigating new and existing technologies to enable controlled adoption. • Collaborating with Security Architects to ensure designs provide appropriate protection for workloads. • Maintaining awareness of emerging technologies, platforms, and industry trends relevant to NEC’s services and customers.

• Build and deliver the chat-style Q&A interface (Vue.js SPA, served via S3/CloudFront) • Implement RBAC enforcement in the frontend: role-based access, filtered views, and permission-scoped display logic • Develop the reporting and pilot analytics UI: query clustering views and audit log access for authorised roles • Integrate the frontend with the Python/FastAPI backend via AWS API Gateway • Implement the SSO login flow: Cognito-backed identity provider integration on the frontend • Collaborate with UX Designer on component implementation; ensure designs are faithfully and precisely translated • Contribute to end-to-end integration testing with the QA Automation Engineer

• Build and maintain the BFF/Backend API layer (Python/FastAPI, ECS/Lambda) • Implement SSO / identity provider integration and the tenant-based authentication schema (AWS Cognito) • Build the audit logging layer, from minimal dev logging through to full document lifecycle tracking • Develop core API services supporting the chat Q&A interface and retrieval orchestration • Integrate with AWS services: API Gateway, Cognito, DynamoDB, S3, CloudWatch • Write unit and integration tests; support the QA Automation Engineer with testable, documented service contracts • Participate in code reviews and contribute to maintaining backend code quality standards alongside the Tech Lead