Forward Deployed AI Engineer

OVERVIEW Most senior client-facing technical role at Toloka. Partner directly with CTOs, VPs of Engineering and ML, and research leaders to solve complex AI data challenges, designing and building the data-generation, labeling and evaluation pipelines that power next generation AI models, and owning each solution from problem discovery to delivery. The role sits at the intersection of consulting, engineering and AI. WHAT THEY’LL DO • Act as the primary technical counterpart to CTOs, VPs of Engineering and research/engineering leadership; lead executive conversations with a structured, answer-first (BLUF) approach • Manage escalations with composure; build long-term trusted relationships through evidence-based recommendations • Uncover the client’s real need (their model, target metrics, how they train or evaluate) and propose the data that will solve it, with options and rationale • Design and build data solutions hands-on: configure data-labeling components and quality controls • Develop user interfaces and AI-driven solutions (agentic systems, RAG, synthetic data generation) • Integrate solutions into automated, multi-stage pipelines that produce data for AI training and evaluation • Run experiments to prove the pipeline delivers data of the required quality and speed; iterate from MVP toward production • Provide technical leadership across client engagements, establish reusable engineering standards and mentor Solution Engineers and Technical Consultants • Own delivery end to end (timelines, quality, scalability) and the commercial outcome, including Gross Margin and Contribution Margin; identify and drive expansion opportunities REQUIRED SKILLS • Executive communication with CTOs, VPs and senior technical stakeholders; professional English (C1+) • Strong understanding of modern LLM development: how LLMs are trained, fine-tuned and evaluated (SFT, RLHF/RLAIF, DPO/PPO, reward modeling, LoRA/PEFT) • Post-training experience: SFT and Reinforcement Learning • Hands-on solution engineering: complex AI solutions, multi-stage pipelines, agentic workflows, RAG, synthetic data generation • Python (NumPy, Pandas), API integration, and independently prototyping LLM-powered solutions • Solid software engineering foundations: version control, testing, MVP thinking, iterative development • Strong discovery and problem framing: translating business or research goals into AI data and evaluation strategies • 8+ years delivering complex AI, ML or data projects end to end; experience influencing technical direction beyond individual projects • Ownership mindset: thoughtful trade-offs between time, cost and quality GOOD TO HAVE • Experience building production software • Establishing engineering standards, mentoring engineers or leading cross-functional technical initiatives • Top-tier strategy consulting (McKinsey, Bain, BCG) and/or applied ML / LLM engineer experience • Hands-on training or fine-tuning of LLMs and/or building agentic systems • Advanced degree (MSc/PhD) in AI, CS or a related field • Crowdsourcing / data-centric AI; fast-paced multi-project delivery for frontier AI clients