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We are hiring an AI Engineer with strong backend and systems engineering depth to design, build and own production-grade AI systems. You will work across AI architecture, backend systems, agent execution, data infrastructure, reliability and production operations . What You’ll Do Design and build scalable AI/backend systems and autonomous multi-step workflows. Engineer agent orchestration, tool execution, context engineering, memory, retrieval, state and long-horizon execution . Design APIs, asynchronous workers, distributed workflows, database and caching layers. Build evaluation, observability, validation and recovery systems for non-deterministic AI behavior. Own reliability, performance, security, latency, scalability and cost across production workloads. Make system-level architecture decisions and debug failures across AI, backend, database and infrastructure layers. Requirements 2+ years of professional AI, backend, platform or systems engineering experience. Proven experience owning production or enterprise-grade systems . Strong Python , backend architecture, API design, async/concurrent programming and system design. Strong knowledge of PostgreSQL/SQL, Redis, queues/event-driven systems and distributed systems fundamentals . Deep practical understanding of LLMs, agentic systems, RAG, context engineering, memory architecture, tool calling and structured generation . Experience with Docker, Kubernetes/cloud infrastructure, CI/CD, Linux and observability/tracing . Understanding of AI evaluation, model routing/fallbacks, caching, token/cost optimization and production failure handling. Ability to design deterministic safeguards around probabilistic AI systems and make sound architectural trade-offs. We want engineers who can own the complete AI system—from model interaction and backend architecture to infrastructure and production reliability.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.