Member of Technical Staff
* **Job Title:** Member of Technical Staff (MTS) - Engineering
* **Location:** Bengaluru, India (On-site)
* **Employment Type:** Full-time
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### **About the Company**
Our client builds realistic reinforcement-learning environments, verifiers, and training data designed to help frontier AI labs and enterprise teams (including ServiceNow, IBM, HUMAIN, and Zoho) improve and evaluate their next-generation models. Researcher-founded and researcher-led, we are a high-velocity team of ~30 people globally where everyone ships, innovates, and contributes directly to core products like Simulation Labs, agent-training data, and AI evaluation benchmarks.
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### **Job Summary**
We are looking for a talented Member of Technical Staff (MTS - Engineering) to join our engineering team in Bengaluru. This is an engineering-first, full-stack product development role designed for builders who combine deep full-stack expertise (React/Next.js and Python/FastAPI) with proven hands-on experience shipping production-grade LLM and agentic systems. You will play a critical role in taking complex, AI-powered features from blank page to reliable, scalable production systems.
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### **Company Culture**
* **Engineering & Research Excellence:** We are a small, tight-knit global team where every engineer takes deep ownership, ships production code, and directly impacts AI infrastructure.
* **Production Over Demos:** We prioritize reliability, robust system architecture, and first-principles failure analysis over superficial AI demos.
* **Speed & Autonomy:** We thrive in fast-paced, high-ownership environments where engineers navigate ambiguity with sound technical and product judgment.
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### **Responsibilities**
* Develop scalable, highly responsive user interfaces and web applications using modern frontend frameworks (React, Next.js).
* Architect, build, and maintain high-performance, reliable backend services and APIs using Python and FastAPI.
* Own meaningful AI-powered features end-to-end—from initial technical scoping and architecture to production deployment and continuous iteration.
* Collaborate closely with cross-functional and AI/ML teams to integrate and deploy applications leveraging LLMs, RAG, and agent frameworks.
* Implement and manage DevOps best practices, CI/CD pipelines, and cloud infrastructure using Docker, Kubernetes, AWS, and Jenkins.
* Write comprehensive unit, integration, and end-to-end tests following Test-Driven Development (TDD) principles to ensure system stability.
* Design, manage, and optimize data schemas and queries across both SQL and NoSQL databases.
* Perform root-cause debugging and engineering failure analysis to optimize system latency, reliability, and cost.
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### **Required Qualifications (Must-Haves)**
* **Experience:** 4–8 years of professional software engineering experience, with a demonstrated track record of shipping production features end-to-end.
* **Education:** Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline.
* **Frontend Engineering:** Strong proficiency in modern JavaScript/TypeScript and frameworks (React, Next.js).
* **Backend Engineering:** Deep expertise in Python and modern backend frameworks (FastAPI or equivalent).
* **Production AI Experience:** Hands-on experience building and shipping production applications powered by LLMs, RAG, or autonomous agents (with a focus on reliability, model behaviors, trade-offs, and failure modes beyond basic API calls).
* **DevOps & Cloud:** Hands-on experience with containerization and infrastructure tools, including Docker, Kubernetes, AWS, and CI/CD pipelines (Jenkins).
* **Database Management:** Solid understanding of database architecture, query optimization, and management across both SQL and NoSQL systems.
* **Testing & Quality:** Proven experience with automated testing frameworks and Test-Driven Development (TDD).
* **Availability:** Candidates who are Immediately available or serving an active notice period are preferred.
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### **Preferred Qualifications (Nice-to-Haves)**
* Experience designing and running rigorous AI evaluation frameworks (metric definitions, error analysis loops, and systematic experimentation).
* Strong ML fundamentals (embeddings, optimization, generalization, and identifying data leakage).
* Familiarity with MLOps infrastructure (model serving, observability, GPU and inference cost optimization).
* Prior experience working in high-growth startups or top-tier technology companies.
* Experience with reinforcement learning (RL) environments, synthetic data generation, or benchmark tooling.
* Active contributions to open-source software or a strong GitHub portfolio demonstrating engineering projects.
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### **Success Metrics for the Role**
* **First-Principles Problem Solver:** You dig deep into technical failure modes and diagnose quality regressions with sound engineering logic.
* **Biased Toward Action:** You take autonomous ownership of ambiguous problems and turn them into resilient, production-ready software.
* **Product-Minded Engineer:** You tie engineering decisions directly to user value and system reliability.
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