Jobs at MLabs

Lead QA architecture and testing strategy for EDR/XDR cybersecurity products. Design automation frameworks and oversee functional, non-functional, security, performance, scalability, endpoint, and cloud testing. Collaborate with engineering and architecture teams to identify risks, diagnose defects, validate fixes, and establish quality metrics. This is a five-month, full-time, on-site contract in Bangalore requiring immediate availability and at least five years of QA leadership or architecture experience.

Develop backend and data solutions while supporting daily operations, collaborating with cross-functional stakeholders, improving workflows, monitoring performance metrics, tracking milestones, solving complex challenges, maintaining documentation, and ensuring compliance. The role requires strong communication, prioritization, independent troubleshooting, and the ability to deliver high-quality outcomes in a fast-paced environment.

Lead design and implementation of high-performance agent runtimes, backend services, and self-hosted model/agent infrastructure. Build low-latency execution systems, real-time data pipelines, telemetry loops, CI/CD for zero-downtime deployments, and ensure fleet reliability on AWS/EKS.

Drive liquidity growth by sourcing and managing high-value liquidity providers (institutional and on-chain), using on-chain data to target allocators, design tailored value propositions, onboard and optimize capital deployment, track TVL attribution, and build the liquidity provider growth function cross-functionally.

Design, deploy, and maintain physical and cloud network infrastructure for a large-scale AI data platform. Implement IaC, virtualization, container orchestration, monitoring, and security to ensure scalable, reliable operations and integrate DevOps automation with engineering teams.

Lead design and build of high-performance trading infrastructure: optimize transaction landing, prevent MEV, implement proprietary routing and cross-chain solvers, deploy advanced trading features, and provide technical leadership to a small engineering team.

Build and scale a developer community (digital and in-person), plan and run Bay Area meetups and hackathons, recruit speakers and partners, manage Slack engagement, and convert community activity into sales pipeline.

Design, build, deploy, and maintain AI agents to automate investment research workflows. Integrate financial tools, APIs, and data sources; implement safety guardrails; create evals and monitoring for production performance; and collaborate with product and quantitative teams to align agent capabilities with platform goals.

Design, build, and optimize a production-grade, low-latency execution engine for event-driven backtesting, paper trading, and live order routing. Implement broker/exchange integrations (REST/WebSockets), ensure state consistency, idempotency, and fault tolerance across simulated and live environments, and reduce latency/slippage while collaborating with a small, high-caliber engineering team.

Lead end-to-end product for an AI-driven quantamental investing platform. Own roadmap, agent orchestration, trading execution, playbook composition, and content distribution. Collaborate with engineering/design, run user research and data analysis, author specs, prototype, test, and ship features to position the platform as a premier AI financial product.

Serve as the company's first full-time recruiter, building end-to-end hiring processes, sourcing passive and active talent, partnering with leadership across functions, creating scalable ATS/workflow systems, designing referral and onboarding programs, and closing high-caliber candidates for technical and non-technical roles.

Senior individual contributor responsible for designing and shipping core systems for LLM-powered agents, high-throughput data pipelines, provider waterfalls, and scalable distributed architectures. Own end-to-end execution, set technical standards, mentor engineers, and collaborate with leadership to drive product and technical strategy.

Build and own end-to-end systems powering autonomous AI sales workflows: high-throughput AI inbound SDR systems, dialer infrastructure, prospecting engines, post-interaction intelligence, and large-scale data pipelines using a modern TypeScript/React/Next.js and AWS-based stack.