Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Target Resume Now
Tailor your resume to this Sr AI Architect role.
Rezi rewrites your resume against Accenture's job description. Free.
Tailor your resume to this Sr AI Architect role.
Rezi rewrites your resume against Accenture's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Sr AI Architect posting at Accenture — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Sr AI Architect posting at Accenture — free, in seconds.
About the Role
As a Lead or Principal AI Architect, you will be the definitive technical authority on AI architecture, owning the complete, end-to-end architecture of advanced AI platforms and solutions. You will operate at the executive level, shaping enterprise AI strategy and connecting business goals to a coherent technical vision. You will lead and integrate the work of multiple domain architects and specialists, providing architectural vision and governance. Beyond client delivery, you will be a thought leader in AI, staying at the forefront of research and innovation, and shaping the practice's AI architecture point of view.
Responsibilities
- Partner with CIOs, CTOs, and business leaders to shape the enterprise AI strategy, connecting business goals to a coherent, sequenced technical vision
- Lead enterprise AI assessments and build enterprise AI implementation roadmaps that sequence investments for lasting competitive advantage
- Own the complete, end-to-end technical solution for complex AI platforms — ensuring every domain is cohesively designed and aligned to business objectives and enterprise standards
- Translate the governing architecture principles into a concrete, defensible technical solution that domain teams build against
- Build innovative prototypes and proofs of concept hands-on, using emerging technologies to de-risk decisions and prove value early
- Lead the hands-on design and development of full-stack agentic applications when needed, including reusable agentic harnesses, developer frameworks, and reference implementations that enable other teams to build, test, govern, and deploy agents consistently.
- Perform technology assessments and comparisons, making definitive, evidence-based recommendations on tools, frameworks, and platforms
- Set the architectural direction for model- and tool-agnostic multi-agent ecosystems — orchestration, memory, and tool/skill use — governed through a registry-bound AI Gateway
- Establish the agent registry and certification model that mandates no uncertified agent reaches production
- Define memory as a first-class abstracted platform service, decoupled from any underlying vendor engine
- Define the foundation model and inference strategy — adaptation, fine-tuning, and dynamic cost/quality/latency-aware routing
- Set the standards for high-throughput, low-latency inferencing and classical ML deployment within unified, production-ready platforms
- Own the architecture of the enterprise context layer — knowledge graphs, ontologies, vector search, and semantic retrieval — grounding the solution in client knowledge
- Set the design direction for context assembly and memory that manages prompts, context windows, and conversational state across the platform
- Be accountable for security, governance, observability, performance, and scalability addressed holistically and consistently across every domain
- Establish the identity and authorization model — per-agent identity, IAM/IAP binding, and defense-in-depth enforcement
- Define the layered guardrail framework applied at every boundary, balancing protection with performance
- Govern the MCP control plane — registry, gateway, and risk scoring — across all internal and third-party servers
- Mandate adopt-over-build for productized evaluation and observability stacks
- Establish FinOps as a first-class concern — usage labelling, gateway-enforced budgets, and cost-per-archetype as a planning input
- Make the definitive decisions on design patterns, reference architectures, frameworks, and technology selections, balancing innovation with pragmatism
- Lead and integrate the work of domain architects and specialists, resolving cross-domain tensions into a unified, enterprise-ready system
- Build the practice's reusable reference architectures, frameworks, and assets, with a deliberate adopt-over-build stance
- Conduct deep-dive architecture workshops and working sessions with client executives and engineering teams
- Produce and govern the authoritative architecture artifacts — blueprints, reference architectures, ADRs, and integration specifications — that guide delivery at scale
- Serve as a recognized thought leader in AI, shaping the practice's point of view and representing the firm externally through publications and conference engagements
Requirements
- Minimum of 8 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 LLM and Generative AI space.
- Minimum of 2 years of experience architecting and operationalizing LLM driven application architecture patterns.
- Minimum of 6 years in engineering, machine learning, deep learning and NLP solutions and applications.
- Minimum of 6 years of experience as a machine architect in the industry designing big data, machine learning. large scale analytical engineering solutions
- English is required for this position as this role will regularly interact with stakeholders across Canada, US and other countries across our Global footprint where English is the common language.
Skills
- AI architecture
- Classical machine learning
- Generative AI
- Agentic systems
- Enterprise AI strategy
- Agentic application design
- AI security and trust
- AI operations and observability
- Data and knowledge engineering
- Model platforms and inference
- AI agent ecosystems
- Multi-agent orchestration
- Tool use
- Skills use
- Memory systems
- Foundation model integration
- Fine-tuning strategies
- Classical ML model deployment
- Non-functional requirements (security, observability, governance, performance, scalability)
- Architecture decision records (ADRs)
- Reference architectures
- Component and data flow diagrams
- Integration specifications
- Machine learning
- Deep learning
- NLP
- Big data
- Large scale analytical engineering solutions
- LLM
- LLM driven application architecture patterns
- Cloud vendor platforms
Location
- British Columbia
- Ontario
- New Brunswick
Work Type
- Hybrid
Experience Level
- Lead
- Principal
- 8+ years
- 2+ years
- 6+ years
Education Level
- Bachelor's Degree or equivalent
Salary/Compensations
- $142,050 to $292,000
About the Company
- Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale.
- We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries.
- Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships.
- We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability.
- Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships.
- We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
- Visit us at www.accenture.com
Equal Opportunity
- We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law.
- Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.