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About Egen:

Egen is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results. If this describes you, we want you on our team.

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About the opportunity:
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.

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