Turing - AI Engineering Lead
Requirements
• Develop LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like retrieval-augmented generation (RAG) and multi-agent based architectures. • Build and maintain agent evaluation pipelines, including offline eval datasets, LLM-as-judge, and CI-integrated eval runs. • Codebase ownership: Build & maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices. • Cloud integration: Deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes. • Communication • Actively follows the frontier and has differentiated, up-to-date views on model releases, agentic architectures, evaluation methods, tool-use and computer-use patterns, multimodal capability, reasoning/test-time compute trends, and the serious open questions in the field. • Produce a structured, high-signal answer to an open-ended technical or strategic question — while modulating depth for a non-engineering executive audience. • Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products. • 12+ years of professional experience in software engineering and building applications/systems. • 2+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques, particularly multi-agent systems. • Expert proficiency in programming skills in Python, Langgraph, and SQL is a must. • Expert in architecting GenAI applications/systems using various frameworks & cloud services. • Expert proficiency in using AI tools like Claude Code, Codex, Cursor, Windsurf, and the likes. • Expert proficiency in AI observability & evaluation tools like Langsmith, Langfuse, or similar. • Good proficiency in using various cloud services from Azure, GCP, or AWS for building GenAI applications. • Experience in driving the engineering team toward a technical roadmap. • Excellent communication skills to effectively collaborate with business SMEs. • Values • Values • We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. • We are client first • We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection • We work at Start-Up Speed: • We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. • We are AI forward: • Advantages of joining Turing • Amazing work culture (Super collaborative & supportive work environment; 5 days a week) • Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
Responsibilities
• Solutioning & Lead • Build the technical roadmap given a business requirement and own the delivery of the same. • Lead the engineering team toward a technical roadmap and ensure timely execution of the roadmap to achieve customer satisfaction. • Design robust multi-agent architectures including supervisor-router patterns with dynamic sub-agent routing and stopping conditions • Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development. • Hands-on skills • Develop LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like retrieval-augmented generation (RAG) and multi-agent based architectures. • Build and maintain agent evaluation pipelines, including offline eval datasets, LLM-as-judge, and CI-integrated eval runs • Codebase ownership: Build & maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices. • Cloud integration: Deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes. • Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products. • Values: • Values: • We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. • We are client first • We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection • We work at Start-Up Speed: • We are Al forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. • We are Al forward: • Advantages of joining Turing: • Amazing work culture (Super collaborative & supportive work environment; 5 days a week) • Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience) • Competitive compensation • Flexible working hours
Benefits
• Flexible working hours
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