Thoughtworks

Technology

LeadAIEngineer(Hybrid)

$198–261k San Francisco, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Lead AI Engineer (Hybrid) at Thoughtworks. Skills: AI Engineering, Generative AI, LLMOps, RAG pipelines. Lead AI engineering practice. Guide design of GenAI solutions”

Industry & Context.

Technology
Problems you'll solve

Root cause analysis; Troubleshooting

What They're Looking For.

Must Have

Expertise in Python, Modern software engineering practices, CI/CD, Testing, Version control, System reliability, Design end-to-end AI systems, Scalability, Maintainability, Performance, Deep experience GenAI, Agentic frameworks, Build RAG pipelines, Integrate vector databases, Deploy AI solutions, Major cloud platforms, Containers, CI/CD pipelines, LLMOps practices, Monitoring production systems, Observability tools, Fine-tuning, Model adaptation, ML/NLP frameworks

Nice to Have

Articulate complex technical concepts, Influence senior decision-makers, Inspire engineering teams, Mentor engineering teams, Develop engineering teams, Anticipate technological trends, Proactively shape technical direction, Navigate complex dynamics, Drive consensus

What You'll Do.

Lead AI engineering practice

Guide design of GenAI solutions

Shape technical roadmap

Ensure engineering excellence

Provide technical leadership

Collaborate with partners

Act as technical consultant

Lead cross-functional team

Deliver GenAI solutions

Guide design of AI systems

Ensure production-readiness

Set direction for technical decisions

Optimize AI solutions

Collaborate with product managers

Align technical solutions

Establish best practices

Promote best practices

Provide architectural guidance

Balance experimentation

Set direction for GenAI optimization

Determine model tuning needs

How You'll Work.

Team & Collaboration

Cross-functional team; Product and business partners; Stakeholders

Communication Scope

Articulate complex concepts; Influence decision-makers

Process & Methodology

Technical roadmap, Short cycles

Full Job 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. Job responsibilities 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, while uplifting the team by sharing knowledge, tools and practices that enable both SMEs and generalists to contribute effectively. 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. Job qualifications Technical Skills 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

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