3 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Shape enterprise AI strategy and convert business priorities into phased technical roadmaps with CIOs, CTOs, business leaders, and delivery stakeholders.
- Lead AI architecture assessments, target-state definitions, gap analyses, platform selections, modernization planning, and implementation sequencing.
- Define Snowflake-native AI architectures using Cortex, Cortex Agents, Cortex Search, Cortex Analyst, Snowpark, Streamlit, governance controls, and enterprise security standards.
- Own cohesive end-to-end technical solutions covering RAG, multi-agent orchestration, context engineering, model routing, inference, evaluation, observability, and enterprise integration.
- Establish architecture standards for identity, authorization, PII protection, guardrails, auditability, reliability, scalability, performance, cost, and production support.
- Lead cross-domain architecture decisions and integrate the work of domain architects and subject matter specialists.
- Produce blueprints, ADRs, sequence diagrams, design specifications, integration patterns, reference architectures, and governance playbooks.
- Communicate architecture decisions and recommendations to executives, product leaders, security teams, and engineering delivery teams.
Requirements
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- Minimum 18 years of experience is required; the qualifications also specify 12+ years in software, data, AI/ML, cloud, or enterprise technology architecture.
- At least 8 years of experience designing and deploying enterprise-grade advanced AI, data, analytics, or cloud-native solutions using at least one cloud vendor.
- At least 2 years of experience in LLM and generative AI solution architecture, including agentic AI, RAG, prompt engineering, model integration, and evaluation patterns.
- At least 2 years of experience architecting and operationalizing LLM-driven applications 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.
- Senior-architect experience in banking, insurance, retail, healthcare, travel, logistics, or telecom, with understanding of business, risk, regulatory, and compliance requirements.
- Deep hands-on architecture 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 embeddings, vector databases, semantic retrieval, context engineering, multi-agent orchestration, tool calling, memory, model routing, GenAI evaluation, architecture controls, AI gateways, control planes, agent registries, guardrails, model risk controls, and production governance.
- Preferred qualifications include SnowPro Advanced Architect or SnowPro Advanced Data Engineer certification, Snowpark Python, semantic models, dbt, Native Apps, data sharing, Cortex Guardrails, Snowflake cost and performance tuning, open-source AI frameworks, responsible AI, 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.