• Define AI architecture and technical strategy, and lead implementation across the full lifecycle from design through production • Build scalable ML platforms, pipelines, and workflow orchestration that support model development and event-driven, asynchronous operations at scale • Architect and build LLM-powered systems, including prompt engineering, function/tool calling, multi-agent orchestration, RAG patterns, vector databases, embeddings, and streaming responses • Design and develop APIs and backend services that integrate AI capabilities with enterprise systems and third-party platforms • Lead model development, optimization, and the path from research to production, ensuring promising approaches translate into reliable, production-ready systems • Ensure AI reliability, security, and scalability across deployed systems, including logging, monitoring, and debugging in production environments • Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace • Co-define the AI roadmap with leadership, operating as a peer in strategic technical conversations • Communicate complex technical concepts clearly to engineering and non-engineering stakeholders alike, translating depth into decisions others can act on • Engage with product, engineering, and data teams to align AI work with broader business priorities • Define and champion AI engineering standards that shape how the organization builds and operates AI systems • Mentor across the organization, shaping engineering culture and developing the next generation of technical leaders • Own high-stakes architectural decisions that carry significant organizational and cross-engagement weight • Drive technical vision — defining not just what gets built, but how AI engineering evolves at R&P over time

• Design, develop, and deploy AI-driven solutions that solve real-world business challenges. • Work across the full AI lifecycle—from data preparation and model development to deployment, monitoring, and optimization. • Collaborate closely with product managers, software engineers, and domain experts. • Own the end-to-end AI lifecycle, including data exploration, model development, evaluation, deployment, monitoring, and continuous improvement. • Perform model evaluation, error analysis, and performance optimization to ensure reliability and accuracy. • Develop and enhance AI applications powered by Large Language Models (LLMs). • Build Retrieval-Augmented Generation (RAG) systems, semantic search solutions, and AI assistants. • Work with embeddings, vector databases, and modern AI orchestration frameworks. • Evaluate and improve model outputs for quality, relevance, latency, and user experience. • Deploy and maintain AI services in cloud and containerized environments. • Build scalable APIs and inference pipelines for real-time and batch processing workloads. • Monitor AI systems in production and troubleshoot performance or reliability issues. • Collaborate with engineering teams to integrate AI capabilities into customer-facing products. • Partner with Product, Engineering, Data, and Customer Success teams to translate business requirements into AI solutions. • Contribute to technical discussions, design reviews, and AI best practices. • Stay up to date with emerging AI technologies and recommend practical innovations that create business value.

Role Description We are looking for a passionate and skilled AI engineer to lead the AI engineering practice at a team or program level. In this role, you will guide the design and delivery of generative AI solutions, shape the technical roadmap for your team(s), and ensure high standards of engineering excellence. You will provide technical leadership to a small group of engineers, collaborate with product and business partners, and act as a trusted technical consultant for stakeholders. - Lead a cross-functional team of software engineers, data scientists and other specialists delivering GenAI solutions. - Guide the design and delivery of AI-powered systems that are scalable, reliable and production-ready. - Set direction for technical decisions, ensuring AI solutions are optimized for performance, cost and maintainability. - Collaborate closely with product managers, designers and stakeholders to align technical solutions with business goals. - Establish and promote best practices in AI engineering, covering testing, guardrails, responsible AI, monitoring and documentation. - Provide architectural guidance, balancing experimentation with delivery in short, safe cycles. - Review designs and code across the team, ensuring quality and consistency in AI-enabled features. - Set direction for GenAI application optimization to improve accuracy, performance, cost and know when model tuning is required. Qualifications - Strong expertise in Python and modern software engineering practices, including CI/CD, testing, version control and system reliability. - Proven ability to design and integrate end-to-end AI systems, ensuring scalability, maintainability and performance. - Deep experience with GenAI and agentic frameworks, guiding teams in their effective use. - Expertise in building and scaling RAG pipelines and integrating vector databases into production systems. - Experience deploying AI solutions on major cloud platforms, using containers and CI/CD pipelines for reproducibility. - Skilled in LLMOps practices and monitoring production systems with observability tools. - Experience with fine-tuning, model adaptation and advanced use of ML/NLP frameworks. Requirements - Ability to articulate complex technical concepts to non-technical audiences and influence senior decision-makers. - Proven ability to inspire, mentor and develop high-performing engineering teams, fostering a collaborative and inclusive environment. - Demonstrates the ability to anticipate technological trends and proactively shape the technical direction of the team. - Skilled in navigating complex internal and external dynamics, driving consensus and achieving technical and business goals. Benefits - Learning & Development: There is no one-size-fits-all career path at Thoughtworks; your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. - Responsible Use of AI in Recruitment: AI tools are used to support recruitment tasks, but all selection decisions are made by interviewers and hiring managers. - EEO: Thoughtworks is an equal-opportunity employer committed to providing equal employment opportunities without regard to any characteristic protected by law. - US - Work Authorization: Applicants must have work authorization that does not require visa sponsorship. - Accommodations: Thoughtworks provides reasonable accommodations to qualified applicants with disabilities or sincerely held religious beliefs. - Cancellations: Project scope or availability may shift, and candidates will be informed of any significant changes. Company Description Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator.

Role Description We are looking for a passionate and skilled AI engineer who is responsible for designing and delivering complex generative AI solutions. This role requires the ability to work autonomously on challenging technical problems, provide mentorship to junior engineers and champion engineering best practices. - Design, build and deploy GenAI applications using techniques such RAG, Agents, Multi Agent Systems etc., taking ideas from prototype to production. - Work with both AI/ML engineers and software engineers to deliver reliable, scalable systems. - Own key features or components, ensuring they are well-structured, efficient and easy to maintain. - Make technical decisions and contribute to system design with attention to performance, cost and reliability. - Collaborate with product managers, designers and data scientists to turn business needs into practical solutions. - Share knowledge and mentor junior team members, helping them grow their technical skills. - Review code and provide clear, constructive feedback to peers. - Understand deployment options and trade offs across different cloud providers such as AWS, Azure, Google Cloud, etc. - Understand optimization techniques to improve accuracy, performance and cost for GenAI applications. Qualifications - Strong software engineering fundamentals, including Python, CI/CD, testing, version control and clean code practices. - Solid grasp of software design principles and ability to design and implement AI-powered components or workflows. - Experience with at least one GenAI framework (e.g., LangChain, LlamaIndex, Semantic Kernel) and one agentic framework (e.g., PydanticAI, LangGraph, AutoGen2). - Hands-on experience building and optimizing Retrieval-Augmented Generation (RAG) pipelines with vector databases (e.g., FAISS, Pinecone, Weaviate). - Familiarity with deploying AI solutions on major cloud platforms (AWS, Azure or GCP), with basic use of containers (Docker) and CI/CD pipelines. - Experience using LLMOps and observability tools (e.g., Langfuse, PromptLayer, OpenTelemetry) in production. - Exposure to fine-tuning and use of ML/NLP frameworks such as PyTorch or Hugging Face Transformers. Requirements - Ability to independently solve complex, ambiguous technical problems. - Willingness and ability to guide and mentor junior engineers, sharing knowledge and best practices. - Strong collaborative skills, working effectively with diverse, cross-functional teams. - Thrives in a dynamic and fast-paced environment, demonstrating resilience in the face of challenges. Benefits - There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. - Your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. - We see value in helping each other be our best and that extends to empowering our employees in their career journeys.