Consulting Principal (AI Architect — Frontier AI)

Cognizant; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Cognizant Consulting is seeking an Associate Director, AI Architect to lead enterprise AI solutions built on frontier models. You will join the AI & Digital Engineering team and collaborate with architects, engineers, hyperscalers, and clients.

This is a hybrid leadership role; you will architect advanced AI platforms and guide delivery, while mentoring engineers and partnering with client CTOs on strategic roadmaps.

Qualifications

• 10+ years in software engineering, data engineering, or solution architecture with AI/ML focus.
• Hands-on architecture experience with frontier LLMs and multi-modal models.
• Experience with governance, safety, and regulatory considerations for AI.

Responsibilities

• Architect enterprise-grade AI solutions across use cases with frontier models.
• Lead pre-sales discovery, translate client challenges into scalable AI roadmaps.
• Define AI governance, bias mitigation, and risk frameworks for clients.
• Mentor AI engineers and architects; manage relationships with hyperscalers and partners.
• Advise CxOs on AI strategy, architecture, and delivery quality.

Skills

Solution architecture

Client-facing consulting

Technical leadership

LLMOps / MLOps

Frontier models / multi-modal

Education

Bachelor's degree in CS/Engineering or related field

Tools

LangGraph

AutoGen

CrewAI

Model Context Protocol

Job description

About Cognizant Consulting

Cognizant Consulting is more than Cognizant's consulting practice—we're a global community of 6,000+ experts dedicated to helping clients reimagine their business. Blending our deep industry and technology advisory capability, we create innovative business solutions for Fortune 500 clients. And now, we're looking for our next colleague who'll join us in shaping the future of business. Could it be you?

About the role

As an Associate Director, AI Architect, you will make an impact by leading the design and delivery of enterprise-grade AI solutions built on frontier foundation models. You will be a valued member of the AI & Digital Engineering team and work collaboratively with architects, engineers, hyperscaler and frontier model partners, and clients.

This is a hybrid technical-leadership role: you'll architect solutions that push what frontier models — large language models, multi-modal models, and agentic systems — can responsibly do inside a large enterprise, while leading a team of architects and engineers and acting as a trusted technical advisor to client stakeholders. You'll sit at the intersection of deep technical credibility and client delivery — equally comfortable designing an agent orchestration layer and explaining its risk profile to a client's CTO.

In this role, you will:

• Architect enterprise-grade AI solutions using frontier foundation models (e.g. Claude, GPT, Gemini family) across use cases including agentic automation, retrieval-augmented generation (RAG), copilots, and multi-modal applications
• Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architecture and delivery roadmaps; design and govern the AI platform architecture including model orchestration, prompt and context management, retrieval pipelines, vector stores, agent frameworks, and tool/context integration (including emerging protocols such as MCP)
• Define and enforce responsible AI, governance, and assurance frameworks — covering bias, safety, data privacy, and model risk — aligned to client and regulatory requirements (including the EU AI Act, UK AI regulatory principles, NIST AI RMF, or regional equivalents)
• Lead and mentor a team of AI engineers and architects, building technical capability and clear career pathways within the practice; own technical relationships with hyperscaler and frontier model partners (Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic, OpenAI) to stay ahead of platform capability
• Act as a trusted advisor to client CxOs and senior stakeholders on AI strategy, architecture, and roadmap; own end-to-end delivery quality including architecture reviews, technical governance boards, production readiness, post-go-live scaling, reusable accelerators/IP, and thought leadership

Work model

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring [X] days a week in a client or Cognizant office in the United Kingdom. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you must have to be considered

• 10+ years in software engineering, data engineering, or solution architecture, including at least 3–5 years focused specifically on applied AI/ML or generative AI, with proven hands-on architecture experience with frontier large language models and multi-modal models — including prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design
• Strong grounding in LLMOps/MLOps: evaluation frameworks, observability, cost and latency optimisation, guardrails, and safe deployment at enterprise scale
• Direct experience with major frontier model providers (Anthropic Claude, OpenAI, Google Gemini, or equivalent) and cloud AI ecosystems (Azure AI/OpenAI Service, AWS Bedrock, Google Vertex AI), plus solid understanding of AI governance, responsible AI, and emerging regulatory frameworks (e.g. EU AI Act, UK AI regulatory principles, NIST AI RMF)
• Demonstrated technical leadership — leading architecture teams, chairing design/technical governance authorities, and mentoring senior engineers — combined with client-facing consulting experience: solutioning, pre-sales support, and stakeholder management at senior client level
• Strong software engineering fundamentals (API design, cloud-native architecture, microservices, and data pipeline/data engineering experience) and a Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent professional experience

These will help you succeed

• Experience with agent orchestration frameworks (e.g. LangGraph, AutoGen, CrewAI) and emerging tool-integration protocols (e.g. Model Context Protocol)
• Public sector or other regulated-industry delivery experience (financial services, healthcare, government)
• Relevant certifications (e.g. Azure AI Engineer Associate, AWS Certified Machine Learning, Google Professional ML Engineer)
• Experience building or scaling an AI Centre of Excellence or comparable practice capability within a consulting organisation
• Published thought leadership, patents, or conference speaking in AI/ML; advanced degree is a plus

Security Clearance

SC Clearance required or eligibility to obtain clearance.

Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.