3 days ago
Ahmedabad, 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, Cortex Agents, Cortex Search, Cortex Analyst, Snowpark, Streamlit, and related governance capabilities.
- Design model- and tool-agnostic multi-agent systems, including orchestration, memory, tool use, agent registries, AI gateways, and control-plane patterns.
- Establish context-layer architectures covering knowledge graphs, ontologies, vector search, semantic retrieval, prompt and context assembly, and conversation state.
- Set standards for security, governance, observability, performance, scalability, reliability, privacy, identity, authorization, PII protection, 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.
- Lead and integrate work across domain architects and subject-matter specialists while communicating decisions to executives, security teams, product leaders, and engineering 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 overall 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 designing LLM and generative AI solution architectures, including agentic AI, RAG, prompt engineering, model integration, and evaluation patterns.
- At least 2 years architecting and operationalizing LLM-driven applications in production or enterprise-scale environments.
- At least 6 years in engineering, machine learning, deep learning, NLP, data engineering, or large-scale analytical engineering applications.
- Demonstrated senior architecture 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/LLM Functions, Snowpark, Streamlit in Snowflake, Dynamic Tables, Tasks, Streams, Snowflake ML, RBAC, masking policies, access history, lineage, and observability.
- Experience with RAG, embeddings, vector databases, semantic retrieval, context engineering, multi-agent orchestration, tool calling, memory, model routing, and GenAI evaluation.
- Experience defining non-functional requirements and architecture controls for performance, scalability, security, privacy, governance, observability, resiliency, cost optimization, and operational readiness.
- Ability to compare platforms, frameworks, foundation models, and deployment patterns and make evidence-based architecture recommendations.
- Experience with AI gateway and control-plane patterns, agent registries, certification gates, authorization models, layered guardrails, model risk controls, and production governance.
- Preferred qualifications include SnowPro Advanced Architect or SnowPro Advanced Data Engineer certification, Snowpark Python, Streamlit, semantic models, dbt, Native Apps, data sharing, Cortex Guardrails, Snowflake tuning, open-source AI frameworks, responsible AI, model risk management, red-teaming, synthetic data, human 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.