Overview

Partnering with an ex-Googler-led startup to hire AI Lead Engineer to own the technical execution of our most important products — and to build the engineering culture that will define the organization for years to come.

Responsibilities

• Lead and build a team: Manage, mentor, and grow a team of 6–8 engineers and interns across full-stack and AI workstreams. Set the bar for quality, velocity, and craft. Create an environment where junior engineers learn fast and senior engineers do their best work.
• Architect and ship AI-native products: Design and build production systems using LLMs, autonomous agents, agentic orchestration frameworks, and modern cloud-native infrastructure. Own the full lifecycle — from prototype to production deployment to iteration.
• Go deep on the hard problems: This is not a management-only role. You'll be in the code daily — debugging agent behavior, tuning prompts, optimizing inference pipelines, and making architectural decisions that determine whether a product scales or breaks.
• Move at startup speed: Bootstrap fast, iterate faster, and ship prototypes that can scale. We value working software over perfect plans. You'll be expected to make smart tradeoffs between speed and durability — and to know when each one matters.
• Drive engineering excellence: Establish and evolve best practices across engineering, design, and operations. Build the CI/CD pipelines, testing frameworks, and development workflows that let a small team punch above its weight.
• Shape the product and technical roadmap: Collaborate directly with Engineering Leadership and customers to define what we build next. Translate customer problems into technical strategies. Bring a point of view on where AI tooling is headed and how we should position our platform.
• You're a builder at your core: You've shipped real products — not just features inside large organizations, but systems you owned end-to-end. You've made architecture decisions, lived with the consequences and learned from them.
• You're deeply technical across the full stack: You're fluent in modern frontend and backend development, cloud-native infrastructure (AWS, GCP, or Azure), containerization, and CI/CD. You don't need a separate team to deploy what you build.
• You understand AI from the inside out: You know how LLMs, agents, and agentic frameworks work under the hood — tokenization, context windows, retrieval-augmented generation, tool use, chain-of-thought, agent orchestration. You can evaluate tradeoffs between different model architectures, hosting strategies, and orchestration patterns.
• You can context-switch without losing depth: One hour you're pair-programming with a junior engineer; the next you're redesigning an agent's planning loop. You bring clarity to both conversations.
• You thrive in ambiguity: Early-stage means the spec is often a conversation, the requirements shift weekly, and the right answer is the one that ships and learns. You find that energizing, not frustrating.
• You have 6–9 years of software engineering experience, including meaningful time in hands-on full-stack development and technical leadership. That said — we care more about your depth, clarity of thought, and ability to build than the number of years on your resume.
• Hands-on experience with open-source LLMs (Llama, Mistral, etc.), vector databases (Pinecone, Weaviate, Qdrant, ChromaDB), or agentic SDKs (Claude, OpenAI, Google or similar). ● Experience building or fine-tuning domain-specific AI models for industrial, financial, or healthcare applications.
• Previous startup or early-stage build experience — you've operated in environments where speed, ownership, and resourcefulness matter more than process. ● Familiarity with digital twin architectures, real-time data pipelines, or IoT integration.

Qualifications

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• Position: Engineering Lead
• Job Location: Coimbatore, Tamil Nadu (On-site, Work from Office)
• Job Type: Full-Time, Permanent
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