3 days ago
Coimbatore, IndiaStaff+
Responsibilities
- Shape enterprise AI strategy and convert business priorities into phased technical roadmaps.
- Lead AI architecture assessments, target-state definition, gap analysis, platform selection, modernization planning, and implementation sequencing.
- Define Snowflake-native AI architectures using Cortex, Snowpark, Streamlit, governance controls, data security, and operational standards.
- Own cohesive end-to-end technical solutions across AI platforms, domains, business objectives, enterprise standards, and non-functional requirements.
- Define model- and tool-agnostic multi-agent architectures covering orchestration, memory, tool use, agent registries, gateways, and control planes.
- Establish context-layer architectures for knowledge graphs, ontologies, vector search, semantic retrieval, prompt assembly, and conversation state.
- Set standards for security, governance, observability, performance, scalability, reliability, identity, authorization, PII protection, guardrails, auditability, and evaluation.
- Drive architecture for inference, model routing, model adaptation and fine-tuning, caching, cost controls, and production deployment platforms.
- Produce authoritative architecture blueprints, ADRs, sequence diagrams, design specifications, integration patterns, reference architectures, and governance playbooks.
Requirements
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- Minimum 15 years of experience is required.
- At least 12 years of overall experience in software engineering, data engineering, AI/ML engineering, cloud architecture, or enterprise technology architecture.
- At least 8 years designing and deploying enterprise-grade advanced AI, data, analytics, or cloud-native solutions using at least one cloud vendor.
- At least 2 years of LLM and generative AI solution architecture experience, including agentic AI, RAG, prompt engineering, model integration, and evaluation patterns.
- At least 2 years architecting and operationalizing LLM-driven application architectures in production or enterprise-scale environments.
- At least 6 years of experience in engineering, machine learning, deep learning, NLP, data engineering, or large-scale analytical engineering applications.
- Demonstrated senior architect experience in domains such as banking, insurance, retail, healthcare, travel, logistics, or telecom.
- Deep experience with Snowflake Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, Cortex AI Functions, Snowpark, Streamlit in Snowflake, Dynamic Tables, Tasks, Streams, Snowflake ML, RBAC, masking policies, access history, lineage, and observability capabilities.
- Experience with RAG, embeddings, vector databases, semantic retrieval, context engineering, multi-agent orchestration, tool calling, memory, model routing, and generative AI evaluation.
- Experience defining non-functional requirements and controls for performance, scalability, security, privacy, governance, observability, resiliency, cost optimization, and operational readiness.
- Ability to evaluate platforms, frameworks, foundation models, and deployment patterns and make defensible architecture recommendations.
- Experience with AI gateway and control-plane patterns, agent registries, certification gates, authorization models, layered guardrails, model risk controls, and production governance.
- Strong stakeholder management, executive communication, and technical thought leadership skills.
- Preferred qualifications include SnowPro Advanced Architect or SnowPro Advanced Data Engineer certification, Snowpark Python, Streamlit, semantic models, dbt, Native Apps, data sharing, Cortex Guardrails, and Snowflake cost/performance tuning.
- Preferred experience includes LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel, MLflow, FastAPI, Docker, Kubernetes, responsible AI, model risk management, red-teaming, synthetic data, human-in-the-loop review, A/B testing, and GenAI FinOps.
Tech Stack
Categories
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.