Senior Applied AI Engineer

1001
London
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 6+ yearsEducation: bachelorsSkills: ["Mentorship","Review","Judgment","Tradeoff making","Accountability"]

Build production AI systems that operators can trust in complex enterprise and government deployments. Turn ML prototypes into production AI features by owning end-to-end systems: APIs, services, evaluation harnesses, monitoring, and the architecture, security, and maintainability behind them. Work across multiple live deployments under hybrid/on-prem/sovereign cloud constraints, and raise the engineering bar through mentorship and review while making tradeoffs across speed, quality, security, and maintainability.

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FursaFursa
1001
1001
1 month ago

Senior Applied AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 7 hours agoStatus: Live

Job Summary

Build production AI systems that operators can trust in complex enterprise and government deployments. Turn ML prototypes into production AI features by owning end-to-end systems: APIs, services, evaluation harnesses, monitoring, and the architecture, security, and maintainability behind them. Work across multiple live deployments under hybrid/on-prem/sovereign cloud constraints, and raise the engineering bar through mentorship and review while making tradeoffs across speed, quality, security, and maintainability.
Location: London
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Take ML prototypes to production, including APIs, services, evaluation harnesses, and monitoring operators can rely on.
  • •Turn ambiguous product asks into AI workflows that solve operational problems rather than just exposing endpoints.
  • •Build AI features from product requirements using modern LLM and agent tooling.
  • •Own systems end to end across multiple live enterprise deployments, from model code to product surface.
  • •Ship and design for hybrid, on-prem, and sovereign cloud constraints; set production AI standards through mentorship and review.

Key Requirements

  • •6+ years in software engineering, with 2+ years deploying and maintaining ML models in production.
  • •Engineering-first and ML-literate: comfortable reasoning about models without being a researcher.
  • •Strong fundamentals in distributed systems, APIs, data pipelines, and testing.
  • •Hands-on with modern LLM and agent tooling (e.g., LangChain, LlamaIndex, DSPy), including vector stores plus eval and observability tooling.
  • •Production experience in both TypeScript and Python, with a track record shipping ML-backed features.
  • •A top computer science or engineering degree, or equivalent demonstrated experience.
Experience:6+ yearsEnterprise deploymentsGovernment environmentsMachine learningProduction AIEarly-stage team
Education:Bachelor's in Computer science or engineering
Skills:MentorshipReviewJudgmentTradeoff makingAccountability
Tech Stack:TypeScriptPythonLangChainLlamaIndexDSPyVector stores

Company Brief

1001
1001 AI builds AI-powered operational intelligence for complex, data-heavy industries like aviation, ports, energy, and construction. Its platform unifies operational data to predict delays, manage risk, and optimize performance across critical infrastructure and megaproject environments.
Industry: AI & Machine Learning
Company Size: Micro (1 to 10 employees)
Growth: Growth Stage Startup
Funding: Series A
Headquarters: London, United Kingdom
WebsiteLinkedIn