Tech Lead

Tech Lead at FrontPage | Y Combinator's Work at a Startup Work at a StartupStartup JobsInternshipsUpcoming EventsHow it WorksLog InTech Lead at FrontPage (S21)₹2.5M - ₹4M INR • 0.50% - 2.00%Community for 100M Indian Financial Market Traders & InvestorsBengaluru, KA, IN / Bengaluru, Karnataka, INFull-timeUS citizenship/visa not required3+ yearsApply nowAbout FrontPage At Frontpage, we're building an exciting product at the cross section of social communication and financial markets. Millions of new traders and investors are looking to participate in financial markets. Frontpage harnesses power of community where traders and investors can connect with each other, share their ideas, and learn from each other. If you, like us, adore social products / social psychology / financial markets /crypto, talk to us! More reasons below: • Huge Opportunity: The future of financial markets is social. The number of investors and traders are growing rapidly and are expected to be >100M in India. • USP: Financial community gives us better CAC, retention, network effects. • Resources: Y Combinator (YC S21) company. Backed by top fintech founder angels - Ashneer Grover, Lalit Kesre, Kunal Shah, Nitin Gupta, Jitendra Gupta. Well capitalized. • Founding Team: Experienced product and tech entrepreneurs from IITs. Built social products before. Active participants in financial markets for a decade. • Culture: Honest. Passionate. Radically Transparent. Love our own work and expect everyone to love theirs. Beer and ideas are a commonplace. About the roleSkills: Kubernetes, Node.js, Google Cloud, PostgreSQL, Microsoft Azure • Experience: 3+ years • Location: Bangalore (On-site, HSR Layout) • Works with: Backend, Data, AI/LLM, Product • Reports to: Founder • Compensation: Competitive market salary + meaningful equity This Role Is Ideal For Someone Who... • Enjoys building serious platforms, not CRUD dashboards • Thinks in data flow, latency, failure modes, and correctness • Has strong architectural opinions and can justify them from first principles • Likes being close to production systems, incidents, and real users • Wants to shape the technical DNA of an Finance AI platform from early stages What You'll Actually Be Responsible For 1. Build and own the core platform You will design, build, and operate the systems that power an AI-driven platform end-to-end: • Data Platform: Architect pipelines ingesting real-time news and datasets from multiple vendors • Scalable Infrastructure: Design and run Kubernetes systems handling events, documents, and concurrent AI workflows • AI-Powered Intelligence: Build and integrate LLM-backed services for: • Document insights and understanding (filings, reports, transcripts) • Retrieval-augmented generation (RAG) using embeddings • Intelligent research and analysis workflows • Product APIs: Support web and mobile teams with reliable, well-designed backend APIs powering equity discovery, analytics, and AI features This role is about owning the platform, not contributing isolated services. 2. Keep production boring (Reliability is the feature) You are directly responsible for: • Platform stability under real market and user load • Incident response, root-cause analysis, and postmortems • Observability: metrics, logs, and traces that actually help debug AI and data issues If something breaks, you are expected to: • Understand what failed (data, infra, model, or orchestration) • Fix it decisively • Put safeguards in place so it doesn't recur Core Technical Expectations (Non-Negotiable) Backend & Systems • Strong production experience with Node.js / Express • Comfort building services in Python (FastAPI) for data and AI workloads Data, AI & Infrastructure • Solid hands-on experience with: • PostgreSQL — transactional correctness, schema design, and performance • pgvector / vector databases — embeddings, similarity search, and retrieval trade-offs • Redis — caching, pub/sub, real-time state • Strong Kubernetes fundamentals (deployment, scaling, troubleshooting) AI / LLM Integration • Production experience integrating OpenAI or equivalent LLM APIs • Hands-on experience with: • RAG architectures • Prompting, chunking, embedding strategies • Managing cost, latency, and correctness trade-offs in LLM systems Cloud & DevOps • Production experience running systems on Cloud (Azure, GCP etc) • Ownership of CI/CD pipelines (GitHub Actions, Cloud Build, etc.) Signals That Strongly Help • Built or operated AI-driven, data-intensive platforms • Equity research, capital markets, or financial data exposure • Experience debugging performance, latency, and reliability issues under load • Clear opinions on: • LLM and RAG architecture choices • Data and embedding schemas • Scaling and failure strategies • Experience with workflow orchestration (e.g. Prefect, Airflow,) for: • Data ingestion • Model pipelines • Long-running AI wor