Principal AI Architect

As an AI Architect within Thoughtworks' Data AI Service Line, you will be at the forefront of helping our clients design, build, and scale enterprise-grade AI systems. You will operate as a trusted technical leader and advisor — shaping AI strategy, establishing architectural patterns, and delivering impactful solutions that create measurable business value.

This is a hands-on, consulting-first role. You'll partner with client stakeholders across industries, lead multidisciplinary teams, and bring Thoughtworks' hallmark of technical excellence to every engagement — from early discovery through to production.

About Thoughtworks the Data AI Service Line

Thoughtworks is a global technology consultancy that integrates strategy, design and engineering to drive digital innovation. Our Data AI Service Line partners with forward-thinking organizations to harness the power of data and artificial intelligence — building the foundations, capabilities, and solutions needed to compete in an AI-native world.

Our practice spans the full AI lifecycle: from data strategy and modern data platforms to machine learning engineering, generative AI, responsible AI, and MLOps. We work with enterprises across financial services, healthcare, retail, media, and the public sector, delivering outcomes that matter.

What You'll Do

AI Architecture Solution Design

Architect scalable, production-ready AI and ML systems, including LLM-powered applications, agentic frameworks, and real-time inference platforms

Define and deliver end-to-end technical blueprints covering model development, data pipelines, serving infrastructure, monitoring, and governance

Lead the design of Retrieval-Augmented Generation (RAG) systems, fine-tuning pipelines, and model evaluation frameworks

Evaluate and recommend AI/ML platforms, cloud-native services (AWS, GCP, Azure), vector databases, and open-source tooling

Client Advisory Consulting

Act as a strategic AI advisor to C-suite and senior technical stakeholders, translating business challenges into AI-driven solutions

Lead architecture discovery workshops, technical due diligence, and capability assessments

Shape and present compelling technical proposals, RFP responses, and point-of-view documents

Navigate complex client organisations, managing stakeholder expectations and building lasting trust

Engineering Leadership

Lead and mentor cross-functional teams of engineers, data scientists, and ML practitioners on client engagements

Define engineering standards, architectural principles, and best practices for AI systems

Champion responsible AI practices including fairness, explainability, privacy, and security by design

Drive hands-on delivery — this is not a purely advisory role; you will write code, review designs, and unblock teams

Practice Community

Contribute to Thoughtworks' AI practice development: thought leadership, internal accelerators, reusable frameworks, and IP

Represent Thoughtworks at conferences, publish articles, and engage with the broader AI community

Mentor and grow the next generation of AI practitioners within the firm

What You'll Bring

Technical Expertise

8+ years of experience in software engineering, data engineering, or ML engineering, with at least 3 years in a senior architecture or technical leadership role

Deep expertise in designing and deploying ML and AI systems at scale — spanning classical ML, deep learning, and generative AI

Strong command of LLM ecosystems: prompt engineering, fine-tuning, RLHF, RAG architectures, LangChain, LlamaIndex, or equivalent frameworks

Proficiency in Python and familiarity with ML frameworks (PyTorch, TensorFlow, Hugging Face, scikit-learn)

Solid grounding in data architecture: streaming (Kafka, Spark), lakehouses, feature stores, and vector databases (Pinecone, Weaviate, pgvector)

Hands-on experience with cloud AI services across AWS (SageMaker, Bedrock), GCP (Vertex AI), or Azure (Azure ML, OpenAI Service)

Familiarity with MLOps and LLMOps practices: CI/CD for ML, model registries, A/B testing, drift detection, and observability

Consulting Leadership Skills

Demonstrated experience operating in a consulting or professional services environment, managing client relationships and delivering on commercial commitments

Ability to communicate complex AI concepts clearly to both technical and non-technical audiences

Proven track record of leading delivery teams in agile environments, with experience across the full software development lifecycle

Comfortable operating with ambiguity — adept at framing problems, structuring workstreams, and driving clarity

Nice to Have

Experience with autonomous AI agents, multi-agent systems, or AI orchestration frameworks

Contributions to open-source AI/ML projects or published research

Domain expertise in one or more verticals: financial services, healthcare, retail, or the public sector

Familiarity with AI governance frameworks, EU AI Act, or responsible AI toolkits (e.g. IBM AI…