15 hours ago
Kochi, IndiaStaff+
Responsibilities
- Design end-to-end AI and Generative AI solution architectures that meet scalability, security, performance, reliability, and maintainability requirements.
- Define architecture patterns for Generative AI, Agentic AI, RAG, Machine Learning, Intelligent Automation, Conversational AI, and AI-enabled enterprise applications.
- Lead solution architecture across discovery, feasibility assessment, prototyping, implementation, production deployment, and post-production operations.
- Translate business, functional, and non-functional requirements into architecture designs, diagrams, integration patterns, deployment architectures, and technical specifications.
- Design LLM applications with prompt orchestration, RAG, vector search, embeddings, model routing, grounding, knowledge bases, AI agents, tool calling, and multi-agent architectures.
- Design integrations with APIs, databases, data platforms, SaaS applications, enterprise systems, event-driven systems, and external services.
- Define AI security, identity and access management, privacy, guardrails, content filtering, responsible AI, governance, and compliance approaches.
- Establish standards for AI observability, monitoring, tracing, logging, evaluation, performance management, reliability, and operational support.
- Guide cross-functional engineering teams, lead architecture reviews and technical workshops, and communicate complex concepts to technical and business stakeholders.
- Define reusable AI reference architectures, technical standards, architecture governance frameworks, and implementation roadmaps.
Requirements
- 10+ years of experience in software engineering, application architecture, cloud architecture, data architecture, solution architecture, or related technology roles.
- At least 3 years of experience designing or implementing AI-based solutions involving Generative AI, Machine Learning, Intelligent Automation, Conversational AI, or Agentic AI.
- Experience as a Solution Architect, Technical Architect, Cloud Architect, AI Architect, or equivalent senior architecture professional.
- Enterprise-scale experience delivering production-grade solutions involving multiple applications, platforms, integrations, and data sources.
- Hands-on experience with RAG, embeddings, vector databases, semantic search, document retrieval, and enterprise knowledge bases.
- Strong architecture experience with at least one of AWS, Microsoft Azure, or Google Cloud Platform.
- Understanding of cloud-native architecture, APIs, serverless architectures, containers, event-driven architectures, asynchronous processing, and distributed systems.
- Understanding of REST APIs, API gateways, authentication and authorization, OAuth/OIDC, networking, secrets management, encryption, and enterprise security architecture.
- Experience integrating AI applications with Databricks, Snowflake, BigQuery, Amazon Redshift, Microsoft Fabric, or equivalent data platforms.
- Experience with prompt engineering, context management, grounding, model selection and evaluation, hallucination mitigation, and AI guardrails.
- Understanding of AI orchestration and development frameworks such as LangChain, LangGraph, Semantic Kernel, LlamaIndex, or DSPy.
- Understanding of CI/CD, Infrastructure as Code, DevOps, MLOps, LLMOps, Kubernetes, and automated deployment practices.
- Knowledge of responsible AI, AI governance, model risk management, data privacy, content moderation, explainability, and human-in-the-loop controls.
- Knowledge of MCP and A2A communication is desirable; UCP experience is a plus.
- Strong stakeholder management, communication, presentation, analytical, consulting, and problem-solving skills.
- Cloud architecture certifications, AI/ML or Generative AI certifications, large-enterprise or consulting experience, and experience with AI architecture standards or governance frameworks are advantageous.
Tech Stack
Amazon RedshiftAWSAzureDatabricksDatadogGoogle BigQueryGoogle Cloud PlatformGrafanaKubernetesSnowflake
Categories
AI ApplicationsSolutions Engineering
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.