Lead AI Engineer

As a Lead AI Engineer, you will be at the forefront of our Generative AI initiatives.

We treat AI as a software engineering discipline.

You will be responsible for the full lifecycle of our AI features—specifically document intelligence and RAG pipelines—taking them from initial prototype to robust, scalable production services.

You will solve for real-world constraints like latency, error handling, and cost optimization.

You’ll collaborate with a diverse range of clients to translate business needs into high-performance AI architectures.

This role requires a blend of deep technical expertise in LLMs and a disciplined Software Engineering approach to ensure our solutions are robust, ethical, and scalable.

As a Lead AI Engineer, you will be at the forefront of our Generative AI initiatives.

We treat AI as a software engineering discipline.

You will be responsible for the full lifecycle of our AI features—specifically document intelligence and RAG pipelines—taking them from initial prototype to robust, scalable production services.

You will solve for real-world constraints like latency, error handling, and cost optimization.

You’ll collaborate with a diverse range of clients to translate business needs into high-performance AI architectures.

This role requires a blend of deep technical expertise in LLMs and a disciplined Software Engineering approach to ensure our solutions are robust, ethical, and scalable.

This position may be hired at multiple levels.

Final leveling is determined during the interview process based on a candidate's experience, skills, and interview outcomes, and the applicable salary range will align with the final level assigned.

is determined based on factors including experience, expertise, interview performance, and geographic location, where applicable.

• Architect & Build: Design and implement end-to-end GenAI applications using Python, LangChain, and LlamaIndex on Google Cloud
• Engineer for Precision: Develop advanced RAG (Retrieval-Augmented Generation) pipelines and Semantic Search systems using Google Cloud Vector Search or Pinecone
• Optimize Models: Lead efforts in LLM and Embedding fine-tuning to improve domain-specific performance
• Agentic Ops: Build and manage agentic workflows that automate complex multi-step reasoning tasks
• Collaborate & Innovate: Work directly with customers to understand requirements, suggest novel features, and implement state-of-the-art AI techniques
• Productionize: Apply MLOps best practices to ensure models are served efficiently, monitored, and continuously improved
• Core Languages : Mastery of Python and shell scripting
• AI/LLM Ecosystem : Extensive experience with Google Gemini, GPT-4, or LLaMA; deep knowledge of Prompt Engineering and Fine-tuning
• Data & Search : Expertise in Vector Databases (Vertex AI Vector Search, pgvector, etc.) and implementing Semantic Search
• Infrastructure : Hands-on experience with Google Cloud (Vertex AI) and building scalable software architectures
• Frameworks : Proficiency in LangChain, LlamaIndex, or similar orchestration layers
• Mindset: A strong software engineering foundation—you write clean, maintainable code and understand the full SDLC
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• 8+ years of experience in AI/ML
• Proven track record of deploying GenAI products to a production environment
• Experience with Classic Machine Learning (neural nets, training, tuning) is a strong plus
• Knowledge of Data Engineering and SQL
• Ownership: You take pride in your code and see projects through from concept to deployment
• Curiosity: The AI landscape changes weekly; you are a lifelong learner who stays ahead of the curve Consultative Spirit: You enjoy interacting with clients and can translate technical complexity into business value Ethics: You prioritize responsible AI development and data privacy