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Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning. Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge. Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success. Your responsibilities will include: Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning. Creating the datasets, metrics, and pipelines that drive measurable improvements across the system. Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization. Establishing MLOps practices, including orchestration, observability, and experiment tracking. Collaborating with the engineering team on system design and with JetBrains Research on the research agenda. Defining hiring criteria, growing the ML team, and shaping the ML team culture. We expect you to have: A proven track record as an ML/AI Lead. At least five years of experience in ML/AI systems, with at least two years focused on LLMs and generative AI. A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches. Hands-on experience with: Prompt engineering and LLM pipeline design, including evaluation. Agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent. Vector databases and retrieval-augmented generation (RAG) patterns. Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models. Strong Python skills – Kotlin knowledge would be a plus. Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences. Proficiency in English, both written and verbal. Our ideal candidate would have: Experience with ontologies, knowledge graphs, or graph-based reasoning. Experience in early-stage startups – you enjoy the zero-to-one phase. The ability to think strategically about product-led AI, beyond just training models in isolation. A background in code analysis, developer tools, or software engineering research. Experience with multi-agent systems or complex agentic workflows. Actively contributed to relevant open-source projects or publications. What we offer A competitive salary and JetBrains benefits. A generous runway and corporate resources with startup autonomy. #LI-KP1 We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
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.