Senior AI Engineer

We are looking for a Senior AI Engineer with deep expertise in Large Language Model (LLM) design, integration, and production deployment. This role is ideal for a technically strong builder who excels at architecting advanced AI solutions, driving complex initiatives, and providing technical guidance to peers. Formal people management is not required, but the ability to influence architecture, mentor junior engineers, and elevate engineering best practices is highly valued.

This individual will play a central role in shaping and scaling our next generation of AI-powered products, from sophisticated retrieval-augmented generation (RAG) systems to multimodal AI applications, helping turn cutting-edge capabilities into reliable, production-grade solutions.

Key Responsibilities

LLM Architecture & Integration

Design, integrate, and optimize pre-trained LLMs within production environments using APIs, orchestration tools, and modern frameworks to deliver scalable, high-performance, low-latency applications.

Solution Design & Technical Leadership

Lead the design and execution of advanced AI initiatives, including conversational AI, natural language interfaces, semantic search, and multimodal processing workflows. Help define architecture standards and guide technical direction across projects.

RAG & Knowledge Systems

Build and enhance RAG pipelines that combine LLMs with vector databases and enterprise data sources, ensuring outputs are accurate, context-aware, and well-grounded across large-scale document and information systems.

Innovation & Model Optimization

Evaluate and improve AI performance through experimentation with embeddings, tuning strategies, prompt design, and hyperparameter optimization, balancing quality, speed, and cost while identifying high-impact business applications.

Vision + Language Workflows

Develop hybrid AI systems that combine OCR, computer vision, and LLM-driven reasoning to support complex multimodal use cases.

Engineering Quality & Governance

Establish high standards for code quality, testing, evaluation, deployment, and observability. Promote responsible AI practices, including security, fairness, and bias mitigation.

Mentorship & Cross-Functional Collaboration

Support and mentor junior engineers, contribute to technical design discussions, and collaborate closely with product, engineering, and business teams to deliver practical, high-value AI solutions.

Cloud & Infrastructure

Help deploy and scale AI workloads in cloud environments, especially GCP tools such as Vertex AI and Cloud Run, with familiarity across AWS and Azure. Contribute to containerization and Kubernetes-based infrastructure strategies.

Strategic Partnership

Work with leadership to align AI initiatives with company goals, inform product roadmaps, and identify emerging technologies that can create meaningful competitive advantage.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
• 5+ years of professional experience in AI engineering, including hands-on experience deploying and optimizing LLM-powered applications in production
• Strong experience with frameworks and tools such as Hugging Face Transformers, LangChain, LlamaIndex, and APIs including OpenAI, Groq, or Ollama
• Advanced Python development skills, including pipeline design, package and dependency management, and integration with vector and retrieval tools such as FAISS, Pinecone, or Weaviate
• Demonstrated success building and scaling RAG systems, chatbots, and conversational AI platforms
• Experience with multimodal AI workflows, including OCR and computer vision integrations
• Proven ability to troubleshoot, optimize, and scale LLM-based systems in real-world environments
• Working knowledge of GCP and other major cloud platforms, along with containerization and orchestration best practices
• Strong communication skills with the ability to work effectively across both technical and non-technical teams

Preferred Qualifications

• Experience leading technical direction or mentoring engineers, formally or informally
• Contributions to open-source AI projects, research publications, or patents
• Familiarity with multi-agent architectures, evaluation frameworks, and responsible AI guardrails
• Experience in startup or high-growth environments, with the ability to balance rapid experimentation and long-term scalability

What We Offer

• Competitive compensation and comprehensive benefits
• Flexible hybrid work environment
• The opportunity to shape the future of AI-driven products at a fast-growing, established company
• Meaningful career growth through technical leadership, innovation, and professional development opportunities