Senior/Staff Software Engineer - AI‑Accelerated Belief: We believe modern AI tools exponentially compound the output of the very best engineers. Our bar is intentionally high: we hire exceptional builders and give them an AI multiplier. The Role Own end‑to‑end delivery of production systems in an AI‑first environment. You’ll turn fuzzy problems into tight specs, orchestrate AI coding tools as collaborators, and ship reliable, secure, observable software that users love. What You’ll Do Frame problems & write crisp specs with clear acceptance criteria, non‑goals, and performance/cost/privacy constraints. Use AI coding tools as force multipliers (generate, refactor, review) while you own architecture, correctness, and maintainability. Engineer verification : property‑based tests, mutation testing, golden tests, and CI gates that prevent regressions. Design robust architectures (modular boundaries, contracts, versioning, idempotency, retries/backoff, feature flags, canaries). Build data & knowledge foundations : schemas, data contracts, quality checks; pragmatic RAG/embeddings where appropriate. Operate AI features : tracing, offline/online evals, drift monitoring, guardrails, human‑in‑the‑loop feedback. Harden security & safety : threat models for AI chains, least‑privilege tool access, I/O validation, SBOM/supply chain hygiene. Optimize performance & cost : profiling, caching/batching/streaming, p95/p99 targets, cost budgets, graceful degradation. Instrument reliability : SLIs/SLOs, structured logging, distributed tracing; circuit breakers and fallbacks. Collaborate crisply : write concise RFCs/ADRs, make reversible decisions, and mentor others in AI‑accelerated workflows. You’ll Thrive Here If You Have Product sense & taste : you choose the simple thing that scales; your naming, APIs, and defaults reduce cognitive load. Rapid domain learning : you become credible in unfamiliar domains in days, not months - through targeted research and fast prototypes. Spec‑first, test‑first instincts : you treat specs, tests, prompts, and datasets as versioned artifacts. Systems thinking : you design for failure, latency, and cost from the start. Clean fundamentals : algorithms/DS, concurrency, networking/OS, DB internals, type systems - so you can audit AI output. Core Skills We Care About Problem Framing & Specification Context Engineering & Workflow Design (long term memory, HITL, tool use) Verification Engineering (property‑based, metamorphic, mutation) Architecture & Integration (contracts, compatibility, migration paths) Data/Knowledge Engineering (schemas, quality, governance; pragmatic RAG) LLMOps & Evaluation (telemetry, eval sets, drift, feedback loops) Security, Privacy & AI‑Specific Threat Modeling (prompt injection, data exfiltration, tool sandboxing) Performance & Cost Engineering (profiling, caching, batching, streaming) Reliability & Observability ( tracing, dashboards, incident response) Uncertainty‑Aware UX (confidence cues, sources, safe fallbacks) Communication & Decision‑Making Nice to Have Entrepreneurial experience (founded a company or led a 0→1 product). Prior ownership of an AI‑infused production system with evals/guardrails/telemetry. How We Work AI‑first, spec‑first, test‑first. Code is cheap; correctness and systems are not. Small, senior teams. High ownership, fast feedback, low ceremony, strong documentation. Measure everything. If we can’t observe it, we don’t ship it. Qualifications Senior/Staff‑level impact demonstrated through shipped, operating software. Evidence of product judgment and taste in API/UX design. Track record of learning new domains fast and making good decisions under ambiguity. Comfortable supervising AI coding tools and holding the line on quality, security, and reliability. Equal Opportunity We value diverse perspectives and are an equal‑opportunity employer. If you’re exceptional but don’t tick every box, please apply. How to Apply - Project Submission Only Complete the take-home project in https://tinyurl.com/yjepr8xc Submit your GitHub repo along with your CV
As a Senior/Staff Software Engineer at AI Accelerated, you will play a crucial role in owning the end-to-end delivery of production systems in an AI-first environment. Your responsibilities will include framing problems, writing clear specifications with acceptance criteria, and utilizing AI coding tools to enhance architecture, correctness, and maintainability. You will also be responsible for engineering verification through various testing methodologies and designing robust architectures to ensure reliability and scalability. Key Responsibilities: - Frame problems and write specifications with clear acceptance criteria, non-goals, and constraints. - Use AI coding tools as force multipliers while owning architecture and maintainability. - Engineer verification through property-based tests, mutation testing, and CI gates. - Design robust architectures including modular boundaries, versioning, retries/backoff, and feature flags. - Build data and knowledge foundations, ensuring quality checks and pragmatic embeddings. - Operate AI features by monitoring drift, implementing guardrails, and incorporating human-in-the-loop feedback. - Harden security and safety by developing threat models, enforcing least privilege access, and ensuring I/O validation. - Optimize performance and cost through profiling, caching, and setting cost budgets. - Instrument reliability by defining SLIs/SLOs, structured logging, and implementing circuit breakers. Qualifications Required: - Senior/Staff-level impact demonstrated through shipped, operating software. - Evidence of product judgment and taste in API/UX design. - Track record of rapid domain learning and making decisions under ambiguity. - Comfortable supervising AI coding tools and ensuring quality, security, and reliability. Additionally, AI Accelerated is an equal opportunity employer that values diverse perspectives. If you are exceptional but do not meet every requirement, we encourage you to apply. Please note that the application process for this role involves completing a take-home project and submitting your GitHub repository along with your CV using the provided Google form.,