Were seeking a Team Lead – Generative AI Engineer to lead a team of engineers in designing, developing, and deploying production-grade AI systems. This role is ideal for someone who is both a strong technical contributor and an experienced people leader-capable of driving architecture decisions, mentoring team members, and delivering innovative AI solutions at scale.
You will be responsible for guiding the end-to-end lifecycle of Generative AI applications, ensuring technical excellence, scalability, and alignment with business needs. This includes working across backend systems, RAG pipelines, prompt engineering, and cloud-native deployments.
Key Responsibilities
Leadership & Team Management Lead and mentor a team of AI/ML engineers, fostering growth and technical excellence.
Define and enforce coding standards, architectural patterns, and best practices.
Collaborate with stakeholders to translate business needs into AI-driven solutions.
Manage project timelines, technical risks, and team deliverables.
Generative AI & Prompt Engineering Integrate and optimize applications using LLM provider APIs (OpenAI, Anthropic, etc.).
Design prompts with advanced techniques (few-shot, chain-of-thought, chaining, context crafting).
Implement safeguards (guardrails, structured output validation, injection protection).
Architecture & Backend Development Build scalable backend services in .NET (C#) and Python, working with SQL and APIs.
Develop and manage RAG pipelines, conversational AI systems, and summarization tools.
Drive observability: tracing, logging, monitoring for LLM-powered systems.
Evaluation & Optimization Benchmark and evaluate LLMs using custom datasets and automated testing.
Oversee system reliability, performance tuning, caching, and optimization.
Ensure solutions meet enterprise-grade standards for security and scalability.
You will be responsible for guiding the end-to-end lifecycle of Generative AI applications, ensuring technical excellence, scalability, and alignment with business needs. This includes working across backend systems, RAG pipelines, prompt engineering, and cloud-native deployments.
Key Responsibilities
Leadership & Team Management Lead and mentor a team of AI/ML engineers, fostering growth and technical excellence.
Define and enforce coding standards, architectural patterns, and best practices.
Collaborate with stakeholders to translate business needs into AI-driven solutions.
Manage project timelines, technical risks, and team deliverables.
Generative AI & Prompt Engineering Integrate and optimize applications using LLM provider APIs (OpenAI, Anthropic, etc.).
Design prompts with advanced techniques (few-shot, chain-of-thought, chaining, context crafting).
Implement safeguards (guardrails, structured output validation, injection protection).
Architecture & Backend Development Build scalable backend services in .NET (C#) and Python, working with SQL and APIs.
Develop and manage RAG pipelines, conversational AI systems, and summarization tools.
Drive observability: tracing, logging, monitoring for LLM-powered systems.
Evaluation & Optimization Benchmark and evaluate LLMs using custom datasets and automated testing.
Oversee system reliability, performance tuning, caching, and optimization.
Ensure solutions meet enterprise-grade standards for security and scalability.
Requirements:
Proven leadership or team lead experience (mentoring, managing, or leading AI/ML engineers).
5+ years of professional experience in Machine Learning / AI engineering.
1-2+ years hands-on experience in Generative AI application development.
Strong backend engineering skills in .NET (C#), SQL, and Python.
Solid knowledge of LLM providers (OpenAI, Anthropic, etc.) and prompt engineering techniques.
Experience with RAG pipelines, AI workflows, and productionizing LLM systems.
Hands-on with Docker, Kubernetes, REST APIs, and Azure (AKS, ACR, containerized deployments).
Excellent communication skills (English, written and spoken).
Preferred / Nice-to-Have:
Azure AI ecosystem: OpenAI, PromptFlow, Azure ML, AI Services.
Familiarity with CosmosDB, KQL, Azure Log Analytics, App Insights.
Experience with multiple LLM providers (Anthropic, Mistral, Cohere, etc.).
Prompt caching, compression, and output validation strategies.
Redis caching for performance optimization.
Frontend experience with React and Next.js.
Proven leadership or team lead experience (mentoring, managing, or leading AI/ML engineers).
5+ years of professional experience in Machine Learning / AI engineering.
1-2+ years hands-on experience in Generative AI application development.
Strong backend engineering skills in .NET (C#), SQL, and Python.
Solid knowledge of LLM providers (OpenAI, Anthropic, etc.) and prompt engineering techniques.
Experience with RAG pipelines, AI workflows, and productionizing LLM systems.
Hands-on with Docker, Kubernetes, REST APIs, and Azure (AKS, ACR, containerized deployments).
Excellent communication skills (English, written and spoken).
Preferred / Nice-to-Have:
Azure AI ecosystem: OpenAI, PromptFlow, Azure ML, AI Services.
Familiarity with CosmosDB, KQL, Azure Log Analytics, App Insights.
Experience with multiple LLM providers (Anthropic, Mistral, Cohere, etc.).
Prompt caching, compression, and output validation strategies.
Redis caching for performance optimization.
Frontend experience with React and Next.js.
This position is open to all candidates.
