Ai Architect

About the Company Acronotics is a global consulting services and a product company specializing 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 the UK London India Bangalore and Pune and the USA New Jersey Job Title AI Technical Architect Brief We 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 communicators This 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 Responsibilities Solution 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 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