{"id":774867,"url":"https://alion.io/job/g-research-applied-ai-engineer","title":"Applied AI Engineer","company":{"id":445185,"name":"G-Research","domain":"gresearch.com","url":"https://alion.io/company/g-research","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":75,"open_postings":21,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-10T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":85000,"max_usd":224000,"period":"year","method":"role_country_seniority_unknown","sample_n":131},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C#","optional":false},{"name":"C++","optional":false},{"name":"Context Engineering","optional":false},{"name":"Fine-tuning","optional":false},{"name":"gRPC","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LoRA","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Pydantic AI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Tool Use","optional":false},{"name":"LangChain","optional":true},{"name":"PEFT","optional":true}],"status":"live","first_seen_at":"2026-06-15T00:00:00Z","employer_posted_date":"2026-06-15","last_verified_at":"2026-10-11T19:44:25Z","board_verified":true,"closed_at":null,"days_open":118,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":118},"description":"We tackle the most complex problems in quantitative finance by bringing scientific clarity to financial complexity.\nFrom our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we’re building a world-class platform to amplify our teams’ most powerful ideas.\nAs part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm.\nTake the next step in your career.\nThe role\nWe are building the AI layer that will transform how teams across the firm work, from quant research to engineering, risk and operations.\nThe Applied AI team sits at the centre of this effort. We are a small, high-autonomy team focused on defining how AI should be used across the entire company and delivering it in practice.\nWe own a number of large high-impact projects end-to-end. We also embed with teams across the firm when needed, partnering with quantitative researchers to build tools that accelerate discovery, taking promising prototypes from engineering teams and scaling them for firm-wide use, or working with corporate functions to automate a workflows.\nKey responsibilities of the role include:\nWorking across areas such as retrieval and knowledge systems, multi-agent orchestration, evaluation and reliability and context engineering\nTaking AI systems from early prototypes to trusted, production-ready solutions\nOwning high-impact projects from initial concept through to production\nPartnering with teams across the firm to identifying problems and delivering scalable solutions\nTurning team-specific use cases into solutions that can be adopted more widely across the organisation\nWho are we looking for?\nYou are a strong software engineer who actively builds with modern AI technologies. You have experience delivering LLM-powered systems in production and understand how to design, evaluate and operate them effectively.\nThe ideal candidate will have the following skills and experience:\nHands-on experience building with LLMs in production, including agents, RAG pipelines, MCPs, tool-use, multi-step workflows. You've used frameworks like LangGraph, Pydantic AI or similar, and you know when to use them and when to throw them away\nStrong Python engineering skills. Clean, testable, production-quality code\nExperience with context engineering, including retrieval strategies, prompt construction, information routing, memory\nExperience with evaluation and observability for AI systems. Measuring accuracy, detecting regressions, understanding failure modes\nThe ability to work across domains. You're comfortable embedding with a quant research team one month and an ops team the next\nClear communication\nFine-tuning or adapting foundation models, such as LoRA and DPO\nComfort integrating with heterogeneous stacks, such as C#, C++, JVM, gRPC, Kubernetes\nContributions to open-source AI projects, technical writing or conference talks.\nWe're looking for people who want to shape how an entire organisation works with AI. If that's you, we'd love to talk.\nWhy join us?\nHighly competitive compensation plus annual discretionary bonus\nLunch provided (via Just Eat for Business) and dedicated barista bar\n35 days annual leave\n9% company pension contributions\nInformal dress code and excellent work/life balance\nComprehensive healthcare and life assurance\nCycle-to-work scheme\nMonthly company events\nG-Research is committed to cultivating and preserving an inclusive work environment. We are an ideas-driven business and we place great value on diversity of experience and opinions.\nWe want to ensure that applicants receive a recruitment experience that enables them to perform at their best. 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