About this role
AlphaSense needs a seasoned engineering leader to ensure that high-throughput AI systems run reliably for enterprise users without breaking down under heavy traffic. The chosen candidate will solve the core challenge of transforming how distributed architectures operate at scale, bridging the gap between experimental research and production-grade stability.
Working alongside a group of talented engineers in Bengaluru, this person will design robust platforms for AI agents, establish rigorous testing and observability frameworks, and steer the long-term technical roadmap. Ideal candidates possess a strong background in distributed systems, a track record of driving high availability, and a pragmatic approach to balancing velocity with architectural integrity.
What you will do
- Design and implement distributed systems that power AI agents processing thousands of requests per hour while balancing performance, reliability, and cost-efficiency.
- Establish comprehensive testing strategies, CI/CD pipelines, and observability systems to detect and resolve issues proactively.
- Mentor and guide a team of motivated engineers by sharing practical experience in operating resilient production systems.
- Own the technical roadmap for the AI platform and make key architectural decisions to shape future scalability.
- Collaborate directly with machine learning engineers and researchers to transition AI capabilities into stable production environments.
What you need
- Bring over eight years of experience building and operating distributed systems in production environments.
- Demonstrate a proven track record of improving system reliability and achieving high uptime metrics.
- Possess deep expertise in modern engineering practices including microservices, containerization with Kubernetes, and infrastructure as code.
- Show documented experience leading technical initiatives and mentoring engineering teams.
- Exhibit strong programming skills with the ability to contribute across the technology stack.
- Apply disciplined troubleshooting methods to debug production issues and implement thorough observability frameworks.
Nice to have
- Experience with LLM applications, agent frameworks, or AI/ML infrastructure
- Familiarity with prompt engineering, RAG patterns, and vector databases
- Background at high-growth companies or modern engineering cultures
- Experience working with multi-model AI systems such as OpenAI, Anthropic, and Google
Skills and tech stack
Questions candidates ask
What kind of systems will I be building?
You will design and implement distributed systems that power AI agents processing thousands of requests per hour, ensuring reliability, performance, and cost-efficiency. You will also own the technical roadmap for the AI platform and collaborate with ML engineers to productionize capabilities.
What are the core technical requirements?
The role requires 8+ years of experience building and operating distributed systems in production, deep expertise in microservices, containerization using Kubernetes, and infrastructure as code. Candidates must also have a track record of improving system reliability and strong coding skills across the stack.
Will I be expected to mentor others?
Yes, you will lead through expertise by mentoring a team of smart, motivated engineers and sharing your experience in building production systems that maintain high availability. You will also help establish engineering excellence and testing standards.
The application is on the official AlphaSense India careers page.
Apply on company site