AI LLM Architect

YOU ARE   As an experienced and Senior AI/ LLM  Architect , you will play a pivotal role in designing and delivering end-to-end AI platform architectures that power the modern, reinvented enterprise. Operating at the intersection of business and engineering, you will own the technical design of advanced AI systems spanning classical machine learning, generative AI, and agentic systems ensuring they are purposefully architected to meet client business   objectives   and enterprise-grade standards .    Within this scope, you will take deep ownership of one or more critical architecture domains such as agentic application design, AI security and trust, AI operations and observability, data and knowledge engineering, or model platforms and inference serving as the lead authority in your domain across client engagements. THE WORK   Translate business strategy into a technical vision by defining the non-functional requirements (NFRs) necessary to meet operational goals for performance, reliability, and cost.   Lead stakeholder workshops to   align on   technical feasibility, define project scope, and manage expectations with clients and leadership.   Drive the technology selection process, evaluating build-vs-buy decisions for AI platforms (e.g.,   Arize ,   LangSmith ) and foundational models.   Architect model- and tool-agnostic multi-agent systems governed by an MCP Control Plane.   Design and implement the Agent Registry as the mandatory system of record and the AI Gateway for runtime policy enforcement.   Design and implement a certification gate to ensure no uncertified agents enter production,   validating   identity, policies, and   evaluation   metrics.   Design, implement, and abstract core agent services, including a first-class abstracted memory service with semantic, episodic, and procedural endpoints.   Architect the end-to-end data pipeline for AI systems, including data ingestion, preprocessing, and synchronization for fine-tuning and RAG.   Design and implement the context layer—spanning knowledge graphs, vector search, and semantic retrieval—to create reliable, grounded RAG pipelines.   Architect foundation model adaptation strategies, including dynamic, cost-and-performance-aware model routing and selection.   Design, implement, and prototype high-throughput, low-latency inferencing solutions using techniques like response caching and request batching.   Define security, governance, and observability as   centrally-enforced , by-design controls for all AI systems.   Architect   a robust, defense-in-depth security framework, including per-agent identity with IAM/IAP binding and layered guardrails.   Design and implement FinOps controls enforced at the AI Gateway, including token budgets, cost-center labeling, and threshold alerts.   Establish the framework for comprehensive system evaluation, adopting productized tools and instrumenting observability with   OTel   Define and   maintain   the enterprise-wide AI reference architecture, reusable design patterns, and a library of approved software components.   Independently design, implement, build, and deliver proof-of-concept prototypes and foundational software components to   validate   architectural decisions.   Produce and own authoritative architecture artifacts, including blueprints, sequence diagrams, design specifications, and Architectural Decision Records (ADRs).   Mentor and guide cross-functional engineering teams (data, ML, application) on architectural best practices and design patterns.   Continuously research and integrate emerging AI patterns, frameworks, and technologies to   maintain   a forward-looking architecture.   EDUCATION   Bachelor's Degree or equivalent   BASIC (REQUIRED) QUALIFICATION   Minimum of 2 years of experience in designing & deploying enterprise grade advanced ai solutions using agentic,   generative   and classical AI/ML using at least one cloud vendor.   Minimum of 2 years of experience in the Agentic,   LLM   and Generative AI space.   Minimum of 4 years of coding experience using python   Minimum of 2 years of experience architecting and operationalizing LLM driven application architecture patterns.   Minimum of 4 years in coding engineering, machine learning, deep learning and NLP solutions and applications.   Minimum of 4 years of experience as a machine learning architect in the industry designing big   data,   machine learning. large scale analytical engineering solutions.   Benefits of working at Accenture: ·       18 weeks paid parental leave ·       Long & short-term career break opportunities ·       Structured career development program ·       Local and international career opportunities. ·       Certified as a Family Inclusive Workplace™ ·       Flexible Work Arrangements - centered around Accenture’s Truly Human ethos and our commitment to supporting the health and wellbeing of our people. ·       We are proud to be in the top 3 of last year’s Diversity & Inclusion Index! We are a WORK180 Endorsed Employer, to see our benefits and policies click here All our consulting professionals receive comprehensive training covering business acumen, technical and professional skills development. You’ll also have opportunities to hone your functional skills and expertise in an area of specialization. We offer a variety of formal and informal training programs at every level to help you acquire and build specialized skills faster. Learning takes place both on the job and through formal training conducted online, in the classroom, or in collaboration with teammates. The sheer variety of work we do, and the experience it offers, provide an unbeatable platform from which to build a career.  Accenture is a an EEO and Affirmative Action Employee of Females/Minorities/Veterans/Individuals with Disabilities.  Equal Employment Opportunity Statement for Australia: At Accenture, we reco