Senior AI Engineer

xperience

10+ years overall engineering experience, including 3+ years of hands-on experience building Generative AI/LLM-based solutions.

Job Summary

We are looking for an experienced Principal AI Architect / Staff Engineer to lead the design and development of our Generative AI and agentic AI capabilities. You will architect and build scalable, production-ready AI solutions using LLMs, AI agents, RAG pipelines, and cloud-native AI platforms. This is a highly hands-on technical leadership role where you'll own end-to-end AI architecture and mentor engineers while working closely with product, backend, and cloud teams.

Key Responsibilities

• Design and architect end-to-end Generative AI and agentic AI solutions for production environments.
• Build AI agent workflows using LangChain, LangGraph, MCP, and integrate external tools and data sources.
• Design, implement, and optimize RAG (Retrieval-Augmented Generation) pipelines, embeddings, and vector databases.
• Define model selection strategies across multiple LLMs and SLMs, balancing quality, latency, cost, and security.
• Develop scalable AI services on AWS Bedrock, Google Vertex AI, or similar cloud AI platforms.
• Ensure production readiness through observability, monitoring, security, and reliability best practices.
• Collaborate with Product, Engineering, and Security teams to translate business problems into AI-powered solutions.
• Mentor engineers and drive technical excellence across the AI engineering team.

Required Skills

• 10+ years of software engineering experience.
• 3+ years of hands-on experience building production-grade Generative AI applications.
• Strong experience designing AI architectures, not just integrating LLM APIs.
• Hands-on expertise with:
• Generative AI / LLMs
• LangChain / LangGraph
• MCP (Model Context Protocol)
• RAG architectures
• Vector databases (Pinecone, Weaviate, Milvus, Qdrant, pgvector, etc.)
• Embeddings and prompt engineering
• Experience with cloud platforms such as AWS (Bedrock) or Google Vertex AI.
• Strong knowledge of distributed systems, scalable backend architecture, and cloud security.
• Excellent problem-solving, communication, and technical leadership skills.

Preferred Qualifications

• Experience contributing to or leveraging open-source AI frameworks.
• Experience building AI solutions for security, identity, or compliance-focused products.
• Familiarity with AI evaluation frameworks such as Ragas or similar tools.
• Prior experience in a product-based company or startup, owning systems end-to-end.

What You'll Gain

• Opportunity to define the AI strategy for a cutting-edge product.
• Work alongside a senior engineering team on next-generation AI technologies.
• High ownership with end-to-end architectural decision-making.
• Exposure to the latest advancements in LLMs, AI agents, cloud AI platforms, and production-scale Generative AI systems.