> Markdown version of [/jobs/ext/4629355-senior-software-engineer](https://www.wearedevelopers.com/jobs/ext/4629355-senior-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer - **Company:** Metanet, Inc - **Location:** Palo Alto, CA, United States - **Experience:** Expert - **Salary:** $200,000.0 - $300,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Cloud Engineering, Code Review, Continuous Integration, Data Infrastructure, Distributed Systems, Fault Tolerance, Hypertext Transfer Protocols (HTTP), PostgreSQL, Role-Based Access Control, Software Engineering, TypeScript, Management of Software Versions, Graphics Processing Unit (GPU), Retrieval-Augmented Generation, Large Language Models, HNSW (Hierarchical Navigable Small World), Backend, Pgvector, Integration Tests, Milvus, Graphql, FAISS, Front End Software Development, Claude, Pagination, Serverless Computing - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25304_1ab3bd4d9976302cd29d362fd120f3c9 ## About the Role * 10-15 years of professional software engineering experience. * Startup experience strongly preferred over candidates with only big-company backgrounds. * Must be hands-on - this is not a fit for managers who are out of touch with the code. * Must currently reside in the SF Bay Area; relocation is not an option for this role. * Must be willing to work from the Palo Alto office 5 days per week - this is an early-stage, in-person, collaborative environment. * Reasonably long tenure at prior companies preferred (not a pattern of 1-2 year stints), unless there is a legitimate explanation. * Strong cultural fit - including willingness to meet in person for initial interviews. * Genuinely ready for a 0-to-1 opportunity, with the experience to back it up. * Visa sponsorship not preferred, though exceptions may be made for an exceptional (\"rockstar\") candidate. * Exceptional work ethic and a mindset of finding ways to make the impossible possible. ## Description We're looking for people who thrive in ambiguity, move quickly, and love building zero-to-one products. We ship fast, cut clean corners, and obsess over reliability, security, and craft. You'll work end-to-end - from whiteboard to production - owning services, shaping architecture, and raising the bar for engineering excellence. You'll fit right in if you've worked at an early-stage company before, or if you've always wanted to experience the intensity and freedom of a startup. Things change daily, and that's part of the fun - you'll wear multiple hats, experiment, and help shape both the product and the culture from the very beginning., * Build production-quality products and APIs - design and implement frontends, backend services, and cloud-native distributed systems with simplicity, performance, scalability, and maintainability; ship pragmatic REST, GraphQL, or gRPC interfaces with versioning, pagination, authnz, schema evolution, and backward compatibility. * Rapid iteration with ownership and bias for action - iterate quickly with a bias for delivery, take autonomy in decision-making from day one, and adapt comfortably to a fast-paced, evolving codebase; own design, implementation, and production outcomes. * Operate with extreme leverage and build guardrails - aggressively use modern AI tools (e.g., Claude) to accelerate development while maintaining correctness, reproducibility, and maintainability; write rigorous unit and integration tests, maintain meaningful coverage, and produce clear documentation - especially for AI-assisted code. * Evolve the AI stack and make principled tradeoffs - prototype and productionize LLM-dependent features (prompt pipelines, retrievals, structured outputs, evals, guardrails, memory); understand when AI is the right tool versus simpler deterministic solutions, balancing latency, cost, and reliability. * Distributed systems & cloud architecture - design and operate cloud-native systems with a solid understanding of scaling, failure modes, state management, consistency models, and graceful degradation. * Collaborate with product and design - work closely to define roadmap and architecture, turn ambiguous problems into secure, compliant, and high-quality user experiences, and ensure alignment across teams. * Mentor and influence teammates - guide through code reviews, design discussions, tech talks, and crisp documentation; promote high engineering standards and team growth., * Curiosity as a habit - you read release notes, try new runtimes and models, and build weekend prototypes for fun - a lot of your YouTube consumption is hacking and learning new technologies, and you enjoy figuring out what you don't know on your own. * Self-driven - you find the problem behind the problem, align stakeholders, and land outcomes without hand-holding. * Systems mindset - you think in SLOs, budgets (latency, cost, error), blast radius, and graceful degradation. * API ergonomics - you care about naming, error design, rate limits, observability, generated SDKs, and docs that don't lie. * Data foundations - you know when to pick Postgres vs. columnar vs. KV vs. vector; you've shipped schema migrations and zero-downtime deploys. * LLM-practical - you've built RAG or agents in anger; you understand context windows, tokenization, evals, and prompt, tooling hygiene. * Security instincts - you default to least privilege, tame secrets, and design auth flows that survive real traffic., * Hands-on with vector DBs (e.g., FAISS, HNSW, Milvus, PGVector), embeddings pipelines, and hybrid ranking. * Can design retrieval layers - embeddings pipelines, vector indexes, hybrid search (BM25 + ANN), chunking, merging strategies, and memory graphs. * Protocol-fluent - you actually enjoy HTTP/1.1 vs. HTTP/2/3 quirks, caching semantics, content negotiation, and idempotency. * Experience with model hosting (self-hosted inference servers, serverless GPUs, or managed endpoints) and caching, streaming strategies. * Infra chops - containers, IaC, CI/CD, service meshes, feature flags, canary/blue-green deploys, cost observability. * Frontend experience with modern TypeScript frameworks and component systems; accessibility and performance budgets. * Prior startup experience or meaningful open-source contributions., * You've hardened an API (or three) - clear contracts, observability, and error budgets in place. * You've improved the AI retrieval/memory layer with measurable gains in quality or cost. * You've leveled up teammates via patterns, docs, or tooling that sticks.