Role Description The Principal AI Solutions Engineer is Toloka's most senior client-facing technical role - the trusted advisor who sits with our clients' most senior technical stakeholders (CTOs and the CTO office, VPs and Directors of ML/Engineering, research and applied-science leads) and turns their model ambitions into rigorous, defensible AI-data strategies. This is a hands-on role: you design and build the solutions that produce the data used to train and evaluate our clients' LLMs - data-generation, labeling, and evaluation pipelines. You are not training the models yourself; you build the data engine that makes them better. You pair executive-grade communication - the clarity and structure you'd expect from a top-tier strategy consultant - with a strong working understanding of how modern LLMs are trained and improved, and the engineering ability to architect and ship the solution yourself. You are not an order-taker: you diagnose the real problem, tell the client what data will actually move their model, and then build the pipeline that produces it - owning the solution end to end, including its commercial outcome. Every engagement is different. One week you might be designing evaluation pipelines for frontier foundation models, the next helping an enterprise build domain-specific reasoning datasets or synthetic data workflows. This role sits at the intersection of consulting, engineering, and AI. You'll work directly with some of the world's leading AI companies, helping shape how next-generation models are trained and evaluated. What you'll do - Executive partnership - Act as the primary technical counterpart to CTOs, VPs of Engineering, and research/engineering leadership. - Lead executive conversations using a structured, answer-first (BLUF) approach. - Manage escalations and expectations with composure and integrity. - Build long-term trusted relationships by recommending evidence-based solutions. - Data strategy & needs diagnosis - Ask excellent questions to uncover the client's real need - the "question behind the question." - Understand their model, which metrics they want to move, and how they intend to train or evaluate it. - Draw on a solid understanding of how LLMs are trained and fine-tuned to have credible conversations with their technical leaders. - Proactively propose the data that will solve their problem - with options and rationale. - Solution engineering & delivery (hands-on) - Design and build the data solutions yourself: configure data-labeling components and quality controls, develop user interfaces and AI-driven solutions, and integrate them into automated, multi-stage pipelines. - Architect and reason about complex, multi-stage solutions end to end; run experiments to prove the pipeline delivers data of the required quality and speed; iterate from MVP toward production. - Provide technical leadership during implementation, uphold reusable standards, and mentor Solution Engineers / Technical Consultants. - Commercial ownership - Own delivery end to end — timelines, quality, and scalability - and the commercial outcome: Gross Margin and Contribution Margin. - Identify and drive expansion opportunities. Qualifications - Executive communication is your superpower. - Strong understanding of modern LLM development, including pre-/post-training, fine-tuning, and evaluation methodologies. - Hands-on solution engineering experience designing complex AI solutions. - Strong Python (NumPy, Pandas), API integration, and the ability to prototype LLM-based solutions independently. - Solid software-development foundations. - Exceptional discovery and problem-framing skills. - 6+ years delivering complex AI, ML, or data projects end to end. - Ownership mindset. Nice to have - Hands-on experience training or fine-tuning LLMs and/or building agentic systems. - Advanced degree (MSc/PhD) in AI, CS, or a related field. - Experience in crowdsourcing and/or data-centric AI. Important Notice Scam Alert Regarding Fake Job Postings: It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants. Please be aware of the following: - Official Communication: Our recruiting team will only contact you from an official "toloka.ai" email address. - Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process. - Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list . - What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai .

• Partner closely with our most strategic customers to solve complex business and technical challenges. • Serve as the bridge between real-world customer needs and the evolution of our SaaS platform. • Design, architect, and develop scalable features that strengthen and expand our core SaaS platform. • Build full-stack solutions across the application stack, including frontend, backend, APIs, databases, integrations, and cloud services. • Lead technical discovery sessions and architecture workshops with customers and internal stakeholders to define future-state solutions and implementation strategies. • Develop clean, maintainable, and type-safe code using modern technologies such as TypeScript, React, Next.js, and related frameworks. • Translate customer-specific requirements into reusable platform capabilities, ensuring solutions are designed for scale rather than one-time implementations. • Partner closely with Product Management and Engineering leadership to influence product strategy, roadmap priorities, and technical direction based on customer insights. • Design and implement secure, production-ready integrations and automated workflows that improve customer adoption and operational efficiency. • Champion engineering excellence by contributing to CI/CD pipelines, automated testing, observability, performance optimization, and platform reliability. • Mentor engineers, establish technical standards, and promote best practices that elevate the quality, consistency, and scalability of engineering across the organization. • Continuously evaluate emerging technologies, architectural patterns, and development practices to improve platform performance, maintainability, and customer experience.

• Accelerate the sales motion. You lead the technical charge to win new business. This means running discovery with CTOs, mapping complex application ecosystems and hosting needs to our platform, and delivering high-fidelity solution designs and estimates. • Serve as a technical authority. Through demos and architecture deep-dives, you show how Laravel Cloud handles performance and security at scale. You win the respect of engineering teams by solving for their hardest requirements. • Lead evaluations and production pilots. You own the hands-on technical journey, from provisioning trial environments and benchmarking data to coaching customer teams for a seamless production rollout. • Guide the buying journey. You translate technical success into business ROI for leadership. You manage security reviews and procurement hurdles, partnering with your AE to keep the commercial and technical threads aligned. • Influence the platform. You turn field insights into actionable product feedback. Beyond the deal, you represent Laravel in the community by speaking at events, writing technical content, and engaging on livestreams. • Iterate and build. You create the tools and processes that will scale our sales operations. You thrive on turning the unknown into a repeatable, high-performing function.

• Lead a team of Product Managers working on complex, high-impact AI solutions for enterprise customers • Work closely with customers to find the right problem to solve (the use case with the clearest ROI) and define the success metrics before building • Operate in high ambiguity, shaping opportunities where requirements are not clearly defined • Drive the delivery of new solutions from early stages to production, making key product and trade-off decisions across speed, stability, and scope • Own a portfolio of solutions across one or more enterprise customers, setting priorities across multiple parallel engagements • Support your PMs in the day-to-day of running their solutions across different customers: help them prioritize, make trade-offs, and unblock them so product implementations and solutions push forward • Balance speed of execution with long-term quality, reuse, and product thinking • Identify patterns across solutions and push for reuse and productization, working closely with the Platform team • Mentor and develop your PMs, growing their product judgment and helping them operate effectively in a fast-paced, ambiguous environment