Lead AI Engineer
Summary
Lead the design and delivery of generative AI systems, including document intelligence and RAG pipelines, using Python, LangChain, and Google Cloud tools.
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.
What You Will Do:
- Architect & Build: Design and implement end-to-end GenAI applications using Python, LangChain, and LlamaIndex on Google Cloud
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Engineer for Precision: Develop advanced RAG (Retrieval-Augmented Generation) pipelines and Semantic Search systems using Google Cloud Vector Search or Pinecone
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Optimize Models: Lead efforts in LLM and Embedding fine-tuning to improve domain-specific performance
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Agentic Ops: Build and manage agentic workflows that automate complex multi-step reasoning tasks
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Collaborate & Innovate: Work directly with customers to understand requirements, suggest novel features, and implement state-of-the-art AI techniques
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Productionize: Apply MLOps best practices to ensure models are served efficiently, monitored, and continuously improved
Your Technical Toolkit:
- Core Languages: Mastery of Python and shell scripting
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AI/LLM Ecosystem: Extensive experience with Google Gemini, GPT-4, or LLaMA; deep knowledge of Prompt Engineering and Fine-tuning
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Data & Search: Expertise in Vector Databases (Vertex AI Vector Search, pgvector, etc.) and implementing Semantic Search
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Infrastructure: Hands-on experience with Google Cloud (Vertex AI) and building scalable software architectures
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Frameworks: Proficiency in LangChain, LlamaIndex, or similar orchestration layers
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Mindset: A strong software engineering foundation—you write clean, maintainable code and understand the full SDLC
Basic Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
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8+ years of experience in AI/ML
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Proven track record of deploying GenAI products to a production environment
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Experience with Classic Machine Learning (neural nets, training, tuning) is a strong plus
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Knowledge of Data Engineering and SQL
Personal Attributes:
- Ownership: You take pride in your code and see projects through from concept to deployment
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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
Skills
As published by lever · 5 questions · 3 written answers
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, Twitter URL, GitHub URL, Portfolio URL, Other website
Pick from a list (2)
- Do you currently reside in the USA? optional
- Are you a US citizen, permanent resident, on OPT, or do you require sponsorship to work in the US?
Written answers (3)
- Please review the links you provided above - LinkedIn or GitHub. *NOTE: Incomplete or inaccurate profiles may disqualify you from consideration. If you don't have a LinkedIn or GitHub profile, please provide a link to your online portfolio or another relevant platform to showcase your skills.
- What is one project you've worked on that is most similar to this role?
- Why are you interested in working at Egen?