• Designing, building, testing, and delivering production AI capabilities, including intelligent agents, workflows, MCP servers, integrations, machine learning models, and shared services • Developing AI-powered products that automate clinical, operational, financial, and patient-facing workflows across the Curve platform • Building, training, evaluating, deploying, monitoring, and continuously improving machine learning models and intelligent services running in production • Developing reusable MCP tools, APIs, and platform components that accelerate AI development across multiple platform teams • Writing high-quality production code while leveraging modern AI-assisted development tools, including Claude Code, to improve software quality and development productivity • Participating in technical design discussions, code reviews, testing, production deployments, and production support throughout the software development lifecycle • Working closely with Product, UX, Architecture, and development teams to transform business requirements into secure, scalable, maintainable software • Continuously improving AI capabilities through experimentation, prompt engineering, model tuning, evaluation, monitoring, and operational feedback • Taking ownership of production software by troubleshooting complex issues, improving reliability, and helping deliver exceptional customer experiences

• Develop and integrate LLM-based AI solutions via Copilot Studio & Prompt Flow; deploy AI agents into Teams, SharePoint, and Power Platform workflows. • Architect and deploy Microsoft 365 services (Exchange Online, OneDrive, Teams, SharePoint Online, Intune, M365 Apps) with scalable, secure designs. • Implement security & compliance features (Purview, Responsible AI) across M365 environments. • Automate tasks using PowerShell and build custom solutions with Power Automate & Power Apps. • Act as a trusted advisor for clients by leading technical workshops, delivering proofs of concept (POCs), and presenting AI and automation solutions with a clear, structured, and high‑impact communication style tailored to both technical and executive audiences. • Strong knowledge of Azure AI Foundry and Copilot Studio, with the ability to scale, operationalize, and govern AI solutions across enterprise environments, ensuring performance, security, and reliability as adoption grows.

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 support our recruitment team with administrative tasks, but do not screen, assess, rank or make hiring decisions. - EEO: Thoughtworks is an equal-opportunity employer committed to providing equal employment opportunities to all qualified applicants. - US - Work Authorization: Applicants must have work authorization that does not require sponsorship of a visa for employment in the United States. - Accommodations: Thoughtworks is committed to providing reasonable accommodations to qualified applicants with disabilities or sincerely held religious beliefs. - Cancellations: Project scope or availability may shift, or projects may be cancelled during the recruitment and selection process. 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.

• Design, build, and validate machine learning models for RF emitter identification — including feature engineering from sensor data, training pipeline development, model evaluation, and iterative refinement based on results • Conduct hands-on exploratory data analysis on RF sensor datasets using Python and Jupyter notebooks — writing and running analytical code, characterizing feature distributions, identifying data quality issues, and producing documented findings • Implement and maintain ML data pipelines — ingesting NDF sensor streams, applying rollup and preprocessing logic, constructing training datasets, and ensuring pipeline correctness on constrained edge hardware with no cloud dependency • Collaborate with the technical lead and Principal AI/ML Engineer to investigate RF sensor data quality, attribution reliability, and feature behavior under contention — writing code to characterize error sources, validate assumptions, and reproduce findings • Produce clear technical documentation of experiments, model configurations, and results — maintaining reproducibility through disciplined versioning, and contributing to monthly status reports and team knowledge sharing