Poszukujemy Inżyniera AI do pracy nad autonomicznymi agentami negocjacyjnymi w Warszawie. Wymagana znajomość Pythona oraz doświadczenie w AI/ML. Zdalna praca, premiowy system wynagrodzeń.
Słowa kluczowe
Python
AI/ML
LLM systems
enterprise procurement
software engineering
negotiation strategies
data analysis
Benefity
Konkurencyjne wynagrodzenie
Znaczny udział w akcjach
Premie związane z wynikami
Elastyczne godziny pracy
Minimum 30 dni urlopu rocznego
Dzień wolny w urodziny
Praca zdalna do 120 dni w roku
What you will do
Applied AI Engineer - Monq
We are looking for brilliant engineers to join our team at Monq. We're pushing the boundaries of AI with next-generation agentic systems that can autonomously negotiate high-value enterprise contracts. We're focusing on a $4.2 trillion market of strategic procurement that has been largely untouched by AI innovation.
Our mission is to transform how enterprises negotiate their most critical deals, turning strategic procurement from a manual, gut-driven process into a competitive advantage powered by intelligent AI agents.
About the Role
As an Applied AI Engineer, you'll be working on the most cutting-edge component of our product - autonomous negotiation agents that handle $1M+ enterprise contracts. Here, you'll be working alongside the CTO to develop AI systems that can parse complex multi-dimensional deal terms, develop negotiation strategies in real-time, and optimize outcomes beyond just price. You'll ship production-grade AI solutions to Fortune 500 procurement teams, completely transforming how they approach their highest-stakes negotiations.
What You Will Do
Build Advanced Negotiation AI:
Develop and deploy agentic LLM workflows that automate contract analysis, vendor research, and strategic negotiation planning
Create AI agents specialized in key procurement areas: CapEx Equipment, Professional Services, Software & Technology, and Logistics & Supply Chain
Build multi-dimensional optimization systems that consider price, terms, risk, timeline, and relationship factors
Lead Complex AI Projects:
Architect end-to-end negotiation workflows: contract intelligence, strategic reasoning, human orchestration, and outcome optimization
Develop robust multi-agent collaboration frameworks for high-stakes enterprise negotiations
Build comprehensive LLM evaluation systems focusing on negotiation performance, safety, and behavioral consistency
Enterprise Integration & Deployment:
Create sophisticated tooling to connect AI agents to major procurement systems (SAP, Oracle, Coupa, GEP)
Build real-time negotiation dashboards and control systems for procurement professionals
Develop enterprise-grade security, compliance, and audit capabilities for high-value contract negotiations
Strategic Collaboration:
Work directly with Fortune 500 procurement executives to refine AI negotiation strategies
Demo advanced negotiation prototypes and gather feedback on complex use cases
Collaborate with domain experts to ensure AI agents understand nuanced procurement dynamics
About Monq
Monq is building the first AI platform specifically designed for strategic procurement negotiation. We're creating a blue ocean in a $4.2 trillion market that has been ignored by existing AI solutions. Our team brings together deep technical expertise in AI with proven experience in enterprise software and procurement.
We're backed by forward-thinking investors who understand the massive opportunity in applying advanced AI to high-value B2B negotiations. With several major enterprises joining us, we're positioned to become the category-defining platform for AI-powered procurement. We are founded and backed by Revolut and HSBC executives.
Why This Matters: Every 1% improvement in strategic procurement represents a $42 billion market impact. We're not just building software - we're creating the future of how businesses negotiate their most critical deals.
What we offer
Compensation and Benefits
At Monq, we recognize that we're building category-defining technology in a massive market. We offer:
Competitive Package:
Competitive compensation
Significant equity stake - play a real part in Monq's potential to capture a $4.2T market
Bi-annual performance bonuses tied to successful pilot deployments and customer outcomes
Work Environment:
Remote first with quarterly gatherings
Direct collaboration with Fortune 500 procurement teams
Annual team retreat - fully-funded off-site focused on AI innovation and team building
Career Growth:
Visa sponsorship is available for exceptional candidates who complete our recruitment process
Opportunity to define the future of AI-powered enterprise negotiations
Direct mentorship from experienced AI researchers and enterprise software veterans
Others:
No HR organisation
Minimum 30 days of annual leave and a day off in the month of your birthday
Flexible working hours as long as we get the things done
Temporary work from abroad up to 120 days a year (certain limitations apply depending on your nationality/work authorisation status and tax obligations)
Requirements
Requirements
Essential Qualifications:
2+ years of professional software engineering experience - ideally in a start-up
Strong expertise in Python with focus on AI/ML applications
Proven experience deploying LLM systems to production with robust evaluation, guard-railing, and monitoring
Master's or PhD degree in Machine Learning, Computer Science, or related quantitative field
Deep understanding of transformer architectures and large language model capabilities
Preferred Experience:
Previous research and publications in large language models, multi-agent systems, or AI negotiation
Experience with enterprise B2B software development and integration
Understanding of procurement processes, contract analysis, or business negotiations
Experience building AI systems that require high reliability and explainability
Essential Skills:
Ability to architect and build complex, production-ready AI systems from scratch
Strong communication skills with both technical teams and business stakeholders
Comfort whiteboarding AI system designs with enterprise customers
Thrives in fast-paced, dynamic startup environments with high-stakes deliverables
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Wyświetlenia: 1
Opublikowana
11 dni temu
Wygasa
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