AI Technical Architect

About the CompanyAcronotics is a global consulting, services and a product company specialising in Hyper Automation (IPA & Low Code Process Automation), Data Science & Artificial Intelligence (AI). We design, develop and implement cognitive automation solutions by applying a combination of RPA & AI technologies such as ML, NLP, NLG for clients across industries and around the globe.The company is headquartered in the UK and has subsidiaries in the US and India. The company's offices are in UK (London), India (Bangalore and Pune) and USA (New Jersey).Job Title: AI Technical ArchitectBriefWe are looking for an AI Technical Architect who has deep expertise in multi-agent Generative AI frameworks to design, build, and scale enterprise-grade AI solutions. The ideal candidate will architect AI systems that orchestrate multiple specialized agents (e.g., query agents, orchestration agents, forecasting agents) to deliver advanced conversational analytics, data integration, and predictive insights. The candidate should have experience designing software solutions from the ground up, making high-level decisions about each stage of the process and leading a team of engineers to create the final product. To be successful as an AI Technical Architect, you should be an expert problem solver with a strong understanding of the broad range of software technologies and platforms available. Top candidates will also be excellent leaders and communicatorsThis role involves working with Azure AI Foundry, OpenAI, RAG pipelines, and enterprise datasets (Structured like Power BI and unstructured like Legal contracts) to deliver solutions.ResponsibilitiesSolution Architecture- Design end-to-end architecture for multi-agent AI systems including orchestration, communication, and memory layers. - Select and design frameworks (LangGraph, Semantic Kernel, etc.) for agent workflows and orchestration. - Architect RAG pipelines to enable retrieval, reasoning, and response generation from structured, semi-structured, and unstructured sources. - Design scalable, modular, and secure system architecture using microservices and modern design patterns. - Create high-level product specifications, architecture diagrams, and technical documentation. - Provide architectural blueprints, guidance, and technical leadership to development teams. - Architect and deploy scalable, secure solutions on Azure Cloud, using services like Azure Kubernetes Service (AKS), Azure Functions, Azure Storage, and Azure DevOps. - Ensure robust CI/CD and DevSecOps practices in place to streamline deployments and enforce compliance. - Guide the team in troubleshooting, code reviews, performance tuning, and ensuring adherence to software engineering best practices. - Conduct regular technical reviews, present progress updates, and ensure timely delivery of milestones.AI/LLM Engineering- Design and implement specialized AI agents (e.g., KPI query agent, forecasting agent, data integration agent). - Optimize LLM usage with prompt engineering, fine-tuning, and tool integration. - Ensure scalability, modularity, and fault tolerance in multi-agent workflows.Data Integration & Analytics- Integrate AI agents with corporate datasets both structured and unstructured - Work with financial KPIs across Key Figures, Financial Statements, Cash Flow, and Global Cost Benchmark reports. - Enable predictive analytics, what-if scenarios, and simulations using ML models.Enterprise Readiness- Ensure compliance with enterprise security, RBAC, and data governance policies. - Define monitoring, observability, and cost optimization strategies for AI workloads. - Collaborate with business SMEs and data engineers to align AI outputs with functional requirements.Requirements· 10+ years in technology with 4+ years in AI/ML and 2+ years in Generative AI/LLM solutions· 3+ years of experience in a Software or Solution Architect role.· Proven experience in designing and building production-grade solutions using microservices architecture.· Proficiency in Python for AI/ML and agent development.· Hands-on experience with Azure AI Foundry / Azure OpenAI Service (or AWS Bedrock, GCP Vertex AI).· Strong knowledge of retrieval-augmented generation (RAG) design patterns.· Experience integrating AI with structured and unstructured data sources· Solid experience with Prompt Engineering, RAG pipelines, and Vector Database integration.· Experience deploying AI/ML solutions on Azure Cloud, leveraging PaaS components and cloud-native patterns.· Proficiency with containerization and orchestration tools (Docker, Kubernetes).· Knowledge of architectural patterns: event-driven, domain-driven design, CQRS, service mesh, etc.· Familiarity with NLP tools, frameworks, and libraries (spaCy, Hugging Face, Transformers, etc.).- · Strong communication and leadership skills to work cross-functionally with technical and non-technical teams.