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Backend Engineer

Backend Engineer

Parsio - Founding Backend/AI Engineer

OSS Ventures

Paris

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Описание вакансии

Build Parsio's core backend and AI systems, and help turn our clients' messy industrial files into typed, auditable, decision-ready data that makes them more competitive.

The role at a glance

  • Location: Paris
  • Contract: CDI
  • On-site・ 3–4 days/week
  • Compensation: €80–90K gross
  • Equity: Founding-level (BSPCE)
  • Reports to: Co-founder & CTO
  • Start date: ASAP

About Us
We started Parsio with one intention: help make European industry competitive for the 21st century. It’s a domain where deep technical skill still turns into real, measurable impact, and that’s the leverage we want.

What we do: help procurement teams buy better and buy smarter. Manufacturers sit on huge piles of unstructured technical data (PDFs, scanned drawings, CAD files, spreadsheets). We turn it into something a human and an AI can both understand, then build a cost modeling layer on top that can simulate anything: a supplier change, a part redesign, a commodity price hike, and more. Weeks of expert work become a cost-saving strategy a team can act on.

We’re a small, synchronous, trust-first team in Paris: side by side most of the week, decisions made out loud, no org chart between you and the two founders.

Why we're hiring for this role
Every new client brings more industrial data and more processes to model. We need serious engineering muscle to scale without slowing down. That takes two things at once: shipping fast today, and building the right foundation for tomorrow. We’re hiring the founding engineer to help us do both: someone who builds in both Python and TypeScript, and who we trust to make the big architecture calls with us, the decisions that set how far and how fast we can grow from here.

This is a builder’s role. If the thing that gets you out of bed is taking a hard, ambiguous problem and shipping the system that solves it, this is the seat.

The role
As our founding engineer, you will own our core backend and AI systems end to end, in Python and TypeScript. You will report to the Co-founder & CTO and work daily with the CEO.

We decide the what and the when together, out loud, then ship fast. On your scope you own the architectural calls, with the ownership, autonomy and initiative that implies.

How we ship.
Every change goes through review and CI before it merges; tests, evals and monitoring are part of “done”, not a follow-up. Because we trust our CI, we deploy to production whenever we need to.

The stack
The product is made of several blocks with distinct roles:

  • App client: An SPA, the user-facing UI.
  • App backend: A REST API with direct DB access; it serves the SPA and the AI backend, and computes the cost models.
  • AI backend: A dedicated API that runs the AI agents; reaches data only through the App backend.
  • ELT: A data pipeline that processes our clients’ input files and loads the results into our DB through the App backend.

Client:
React, React-router, TypeScript, Vite (SPA)

App backend:
TypeScript, Hono, Drizzle, Postgres (Neon).

AI backend:
Python, FastAPI, PydanticAI + Logfire, GCP Vertex (Gemini, Claude).

ELT:
Python, dlt, dbt, cadquery (CAD / STEP), Postgres, LLM and OCR document extraction.

Infra:
GCP Cloud Run, GCS, Cloudflare, CI/CD on GitHub.

We have an opinion on every brick, but none is set in stone: several calls (orchestration, agent architecture, parts of the backend design) are open and we expect you to own some of them.

Your Main Responsibilities

  • Application backend and the should-cost engine. Build the Hono REST API and the Drizzle data model the whole app reads and writes, and own the engine at the heart of the product: turning a part’s specs and variables into a defensible, explainable cost analysts act on.
  • AI systems (Python).
  • Build the agentic harness : structured outputs, model selection, eval suites and Logfire monitoring, and the cost, quality and latency tradeoffs of running it at scale.
  • Build and fine tune our different agents : spec extraction (reading pdf, cleaning data), modelling (code the data model), cost analysis (reason over the cost engine result), sourcing (retrieving reference data online)
  • The data pipeline. A contained ELT pipeline (Python, dlt, dbt) that processes clients’ data and ingests it into our DB.
  • Own the architecture with us. The foundational choices aren’t pre-baked. You’ll make them with the CTO and own them on your scope (see The stack for what’s deliberately left open).

What Success Looks Like

  • At 30 days. You own a meaningful slice of the system (a backend domain, the should-cost engine, or the AI extraction) and have shipped your first improvements to production.
  • At 90 days. The systems you own run reliably in production, with the tests, evals and monitoring you put in place. You’re making architectural calls on your scope, not just implementing them.
  • At 6 months. Your work measurably moves the product: faster and more accurate extraction, a should-cost engine analysts trust, backend that scales with new tenants. You’re one of the people the architecture of Parsio runs through.

Career path
We level engineering on a clear track:
Engineer → Senior Engineer → Lead / Staff Engineer.
You join as our founding engineer, owning core systems end to end. As you grow, you’ll take on broader architectural ownership across the backend and AI stack, set the engineering standards, and mentor the engineers we hire next.

The process

  • Intro call with the CTO (~1h)
  • Case (~1h30)
  • Meet the CEO (~1h)
  • Reference calls (1–2)

Your profile
Must-haves

  • You build in both Python and TypeScript, or you’re clearly strong in one and hungry to be strong in the other. This role lives on both sides.
  • You ship production backends. Real APIs, real data models, real migrations, running for real users. You write code others can read, extend and trust.
  • Solid with relational databases and SQL. You model data well and you’re comfortable in Postgres.
  • You’ve built on LLMs, not just with them. You’ve shipped at least one LLM-powered feature or pipeline to production (structured extraction, agents, RAG) and you know that prompts without evals are guesses.
  • You want to own architecture, not just tickets. You have opinions on how systems should be built, you can defend them, and you can change your mind.
  • Pragmatic with AI tooling. Claude Code (or equivalent) as your primary coding interface, not a curiosity. You know when to trust it and when not to.
  • Operational French and English (international clients).
  • 5+ years building and shipping software, a good chunk of it backend.

Nice-to-haves

  • Experience with a typed DSL, rules engine, or anything that evaluates expressions (interpreters, ASTs, formula languages).
  • dbt and modern ELT (dlt, warehouse modeling).
  • Experience with LLM eval frameworks, or vision models for document understanding.
  • Familiarity with CAD / STEP files (cadquery).
  • You’ve shipped a typed product taxonomy or ontology.
  • Real industrial exposure.

This role is probably not for you if…

  • You want a fully defined scope with no ambiguity.
  • You’d rather go deep in one narrow layer than build across the stack.
  • You’re uncomfortable switching between architectural decisions and hands-on, scrappy execution.
  • You need a large team and established processes to be effective.
  • You see AI tooling as a gimmick rather than a core part of how you ship.
  • You’re not comfortable operating in both French and English.

How To Apply
Are you excited about building an AI-native platform for manufacturing where your decisions matter, you ship impactful code, and you help keep European manufacturing competitive? We'd love to hear from you. Please send us:

  • A short intro: why you're applying, what manufacturing means to you, and how you think AI will reshape the SaaS landscape (especially data-driven SaaS).
  • A link to your GitHub (or another repo).
  • Your CV or LinkedIn.

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Backend Engineer

Senior Machine Learning Engineer

Randstad Hungary

Удалённоsenior

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Описание вакансии

Organisation/Department

Our client is a US-headquartered, market-leading enterprise in their sector with a multi-decade history and an agile, global network. We are seeking a highly skilled Senior
Machine Learning Engineer
to join their expanding Budapest team as a senior technical individual contributor. Situated within the Data Engineering organization, you will operate at the intersection of data engineering, applied ML, and software engineering to design, build, and deploy production-grade ML infrastructure and agentic AI systems that directly impact the business.

Job description

  • End-to-End ML Pipeline Engineering:
    Design, build, and maintain production ML pipelines end-to-end — feature engineering, model training, evaluation, deployment, serving, and monitoring on AWS and Databricks.
  • Agentic AI Architecture:
    Architect and implement agentic AI orchestration systems using frameworks like LangChain, LangGraph, CrewAI, or custom layers, with production-grade reliability, observability, guardrails, planning loops, and memory management.
  • Feature Stores & Data Pipelines:
    Build and optimize feature stores, training data pipelines, and feature engineering workflows serving both batch and real-time inference workloads.
  • MLOps Infrastructure & Governance:
    Own MLOps infrastructure including CI/CD for models, automated retraining pipelines, A/B testing frameworks, model versioning, experiment tracking, and ML asset governance using MLflow, Unity Catalog, and Databricks Model Serving.
  • LLM Integration Patterns:
    Design and implement LLM integration patterns including RAG architectures, prompt management systems, tool-use frameworks, vector databases, and memory/state management.
  • Monitoring, Observability & Evaluation:
    Develop model monitoring for drift detection, performance degradation alerts, cost tracking, and automated remediation. Establish evaluation frameworks for predictive models (standard ML metrics, backtesting) and agentic systems (task completion, hallucination detection, tool-use accuracy, latency budgets).
  • Technical Leadership & Collaboration:
    Drive build-vs-buy and framework selection decisions backed by prototypes and benchmarks. Mentor ML engineers through technical design reviews, code reviews, and architectural guidance.

Required Experience

  • Core Background:
    6+ years in machine learning engineering, applied ML, or closely related software engineering roles with recent, demonstrated production delivery.
  • Production ML at Scale:
    2+ years building and operating production ML systems handling real traffic and business-critical decisions (not just notebooks or proof-of-concepts).
  • Databricks ML & AWS Ecosystem:
    Production experience with Databricks ML ecosystem (MLflow, Model Serving, Feature Store, Unity Catalog) and supporting AWS services (SageMaker, Bedrock, S3, Lambda, Step Functions, ECS/EKS).
  • Agentic AI Production Systems:
    Hands-on experience building agentic AI systems (multi-step orchestration, tool use, planning loops, memory management, human-in-the-loop patterns).
  • Core Tech Stack & Software Engineering:
    Deep proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) with strong software engineering fundamentals (testing, version control, code review, CI/CD).
  • LLM & Inference Experience:
    Production experience with LLM applications (RAG pipelines, vector databases like Pinecone/Weaviate/Chroma/pgvector, embeddings, prompt engineering, fine-tuning) and real-time/batch inference optimization (quantization, distillation, caching).

Preferred Qualifications

  • Experience with multi-agent system architectures (specialization, inter-agent communication, shared state management, failure recovery).
  • Production experience with model fine-tuning and RLHF/DPO alignment techniques.
  • Hands-on GPU infrastructure management, distributed training, and compute optimization on AWS (EC2 GPU, SageMaker training jobs, Bedrock custom models).
  • Familiarity with streaming ML (online learning, real-time feature computation, event-driven inference) and AI guardrail/safety systems (content filtering, output validation, cost controls).
  • Contributions to open-source ML tooling or published applied ML work.
  • MS or PhD in Computer Science, Machine Learning, or a quantitative field (practical production experience weighted equally).

Benefits

  • High Technical Impact:
    A unique professional challenge to shape production predictive AI models and agentic orchestration workflows for a stable, market-leading global enterprise.
  • Competitive Compensation:
    Senior level base salary and annual target bonus.
  • Benefits Package:
    Cafeteria allowance and private health insurance package.
  • Flexibility:
    Hybrid working model requiring 3 days of office presence (Budapest) and offering 2 days of Home Office per week.

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Backend Engineer

Architecte Solutions logiciel Aéronautique/Défense

Capgemini Engineering

Удалённоlead

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Описание вакансии

Capgemini Engineering, leader mondial des services d'ingénierie , rassemble des équipes d'ingénieurs , de scientifiques et d'architectes pour aider les entreprises les plus innovantes dans le monde à libérer leur potentiel . Des voitures autonomes aux robots qui sauvent des vies, nos experts en technologies digitales et logicielles sortent des sentiers battus en fournissant des services uniques de R&D et d'ingénierie dans tous les secteurs d'activité . Rejoignez nous pour une carrière pleine d'opportunités , où vous pouvez faire la différence et où aucun jour ne se ressemble

Description du poste

Rejoignez Notre Centre D’Excellence Software Et Contribuez Au Développement De Solutions Innovantes Dans Les Secteurs De L’Aéronautique, Du Spatial, De La Défense Et Du Naval. Vous Interviendrez Sur Des Projets Stratégiques à Forte Dimension Technologique Autour Des Applications Web, Mobiles Et Cloud, Au Cœur Des Enjeux De Transformation De Nos Clients. Dans Ce Cadre, Vos Missions Seront De

  • Comprendre les besoins fonctionnels et applicatifs des clients et contribuer aux démarches d’avant-vente.
  • Concevoir des architectures logicielles robustes, évolutives et sécurisées pour des environnements critiques.
  • Développer et promouvoir des offres innovantes autour des technologies applicatives et cloud.
  • Piloter la cohérence entre les besoins du marché, la stratégie des solutions et les capacités internes.
  • Développer un réseau de partenaires et assurer une veille continue sur les évolutions technologiques du marché.

Description du profil

  • Diplômé(e) d’une école d’ingénieurs ou Bac+5, vous justifiez d’au moins 15 ans d’expérience en architecture logicielle dans un contexte industriel complexe ou critique
  • Vous disposez d’une expertise dans les secteurs Aéronautique, Spatial, Défense ou Naval et connaissez les standards associés
  • Vous maîtrisez les architectures distribuées, les API, les microservices, le cloud hybride et les enjeux de cybersécurité logicielle
  • Vous évoluez avec aisance dans plusieurs environnements techniques tels que C/C++, Java, Python, C#/.NET ou Go et possédez un niveau d’anglais avancé
  • Vous êtes reconnu(e) pour votre leadership technique, votre capacité à fédérer les équipes et votre esprit d’analyse.

3 raisons de nous rejoindre

Qualité de vie au travail
: accord de télétravail en France et à l’international, accord sur l’égalité professionnelle, la parentalité, l’équilibre des temps et la mobilité durable.

Apprentissage en continu
: certifications et formations en libre accès, accompagnement sur mesure avec votre career manager, parcours d’intégration sur 9 mois.

Avantages groupe & CSE
: plan actionnariat, activités à tarifs préférentiels, remboursement partiel vacances, remboursement de votre abonnement sportif ou culturel.

Nos engagements et priorités

Le groupe Capgemini encourage une culture inclusive dans un cadre multiculturel et handi-accueillant. En nous rejoignant, vous intégrez un collectif qui valorise la diversité, développe le potentiel de ses talents, s’engage dans des initiatives solidaires avec ses partenaires, et se mobilise pour réduire son impact environnemental sur tous ses sites et auprès de ses clients.

Leader mondial des services d’ingénierie et de R&D, Capgemini Engineering met en oeuvre une connaissance sectorielle approfondie avec la maîtrise des dernières technologies digitales et logicielles pour accompagner la convergence des mondes physique et numérique. Avec plus de 55 000 ingénieurs et scientifiques dans plus de 30 pays, nous aidons nos clients à accélérer leur transformation vers l'Intelligent Industry.

Get The Future You Want* |www.capgemini.com/fr fr

  • Capgemini, le futur que vous voulez

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Backend Engineer

Asset Management & Systems Analyst

Accenture Argentina

Удалённо

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Описание вакансии

We are looking for an Asset Management & Systems Analyst to join our Supply Chain & Engineering team. In this role, you will collaborate on a project for a leading transportation company based in Canada, focused on improving control systems and inventory management.

As an Asset Management & Systems Analyst, you will support and optimize asset management systems and processes to improve asset performance, reliability, and lifecycle management. You will work closely with cross-functional teams, leveraging Enterprise Asset Management (EAM) platforms and digital tools to drive operational efficiency and data-driven decision-making.

👨‍💻 Key Responsibilities:

  • Support and optimize asset management systems and processes.

  • Collaborate with Operations, Maintenance, and Reliability teams to identify opportunities for improving asset performance.

  • Leverage data analytics and digital tools to enhance asset management practices.

  • Support the implementation of solutions for predictive maintenance and asset monitoring.

  • Contribute to the optimization of maintenance strategies.

  • Participate actively in team discussions and help resolve work-related challenges.

🎯
Must-have Skills:

  • Experience with Enterprise Asset Management (EAM) platforms such as SAP EAM, IBM Maximo, Hexagon EAM, or similar solutions.

  • Advanced English (the client is based in Canada, and the role requires regular interaction with international stakeholders).

  • Advanced SQL skills, including writing complex queries for asset and operational data analysis.

🚀 Nice-to-have Skills:

  • Experience with Hexagon EAM.

  • Knowledge of Asset Performance Management (APM) platforms.

  • Knowledge of Systems Engineering concepts.

  • Experience with predictive maintenance and asset monitoring.

  • Experience working with SCADA (Supervisory Control and Data Acquisition) systems.

  • Intermediate knowledge of Python.

  • Experience in transportation, manufacturing, utilities, or other asset-intensive industries.

🤳
Benefits We Offer You:

  • 🍔 Pedidos Ya delivery credits

  • 🏥 Swiss Medical premium healthcare plan at no cost for you and your immediate family

  • 🌐 Connectivity reimbursement

  • 🏋️ 100% covered gym membership

  • 🌴 Flexible vacation policy

  • ⏰ Flexible working hours

  • 📜 Sponsored certifications

  • 🎉 Day off on your birthday

  • 💰 Performance bonuses

  • 🗓 Accenture Days

  • 🎯 Flexible benefits package

  • 👶 Extended maternity & paternity leave

  • 🧸 Financial support for childcare

  • ➕ And many more!

  • We want you to have the tools you need to keep learning, growing, and making a difference in the world.

🌍
Location:
We have offices in
Buenos Aires, Córdoba, Mar del Plata, Rosario, Salta, and Mendoza
.

If you are based in other provinces, many of our positions are remote, so you can work from home.

🌈
Equality and Inclusion
At Accenture, equality drives innovation. We believe in building an inclusive and diverse workplace where everyone has equal opportunities.

All decisions related to recruitment and selection are made without distinction, exclusion, or preference based on race, color, gender, sexual orientation, disability, age, religion, political or union opinion, nationality, socioeconomic background, or any other characteristic protected by applicable law.

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Backend Engineer

Développeuse / Développeur CRM - Stage

Capgemini

Удалённоparttimelead

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Описание вакансии

Choisir Capgemini, c'est choisir une entreprise où vous serez en mesure de façonner votre carrière selon vos aspirations. Avec le soutien et l'inspiration d'une communauté d’experts dans le monde entier , vous pourrez réécrire votre futur . Rejoignez nous pour redéfinir les limites de ce qui est possible, contribuer à libérer la valeur de la technologie pour les plus grandes organisations et participer à la construction d’un monde plus durable et inclusif

Vos missions

Vous rejoindrez une équipe intervenant sur des projets variés grâce à la diversité des secteurs d'activité (Banque, Media, Energie, Retail…).

Vous participerez aux missions suivantes :

Paramétrer et développer des applications digitales (CRM / e commerce)

Participer à l'intégration technique de solutions CRM et e-commerce sur mesure dans un contexte Agile.

Concevoir des applications sur les plans technique et fonctionnel.

Paramétrer des solutions Salesforce (SFDC), réaliser les tests et les recettes fonctionnelles, puis participer à leur déploiement.

Cette description n’est pas limitative. Elle peut tout à fait évoluer en fonction de votre expérience, des projets en cours et de vos attentes.

Votre profil

En M1/M2 dans le domaine du développement logiciel

Compétences en développement (Java, APEX).

Curiosité technologique et volonté d’apprendre

Aisance en anglais (niveau B2 minimum)

3 Raisons de nous rejoindre

Avantages groupe :
bénéficiez d’un ensemble d’avantages tels que les primes de cooptation, tickets restaurant, ainsi que des activités sociales et culturelles variées proposées par le CSE. Des dispositifs d’accompagnement à la parentalité, comme le temps partiel à 90% pendant les vacances scolaires, sont également disponibles, ainsi que de nombreux autres avantages issus de nos accords collectifs.

Qualité de vie au travail :
profitez d’un équilibre entre vie professionnelle et personnelle, d’une possibilité de télétravailler (en France et à l’international), ainsi que des dispositifs de santé et bien-être (ligne d'écoute, plateforme dédiée...).

Environnement inclusif :
rejoignez des réseaux engagés comme Women@Capgemini, Parents@Capgemini, OUTfront ou CapAbility, et évoluez dans un cadre certifié EDGE+ et reconnu par le Bloomberg Gender Equality Index.

Happy Trainees :
notre engagement envers les jeunes talents est reconnu dans le classement HappyTrainees, preuve que chez nous, les stagiaires et alternants ne viennent pas juste apprendre… ils viennent s’épanouir !

Notre engagement et priorités

Le groupe Capgemini encourage une culture inclusive dans un cadre multiculturel et handi-accueillant. En nous rejoignant, vous intégrez un collectif qui valorise la diversité, développe le potentiel de ses talents, s’engage dans des initiatives solidaires avec ses partenaires, et se mobilise pour réduire son impact environnemental sur tous ses sites et auprès de ses clients.

A propos de Capgemini

Capgemini est un leader mondial, responsable et multiculturel, regroupant près de 350 000 personnes dans plus de 50 pays. Fort de 55 ans d’expérience, nous sommes un partenaire stratégique des entreprises pour la transformation de leurs activités en tirant profit de toute la puissance de la technologie et des innovations dans les domaines en perpétuelle évolution tels que le cloud, la data, l’Intelligence Artificielle, la connectivité, les logiciels, l’ingénierie digitale ou les plateformes.

Capgemini, partenaire de la transformation business et technologique de ses clients, les accompagne dans leur transition vers un monde plus digital et durable, tout en créant un impact positif pour la société. Le Groupe, responsable et multiculturel, rassemble 340 000 collaborateurs dans plus de 50 pays. Depuis plus de 55 ans, ses clients lui font confiance pour répondre à l'ensemble de leurs besoins grâce à la technologie. Capgemini propose des services et solutions de bout en bout, allant de la stratégie et du design jusqu'à l'ingénierie, en tirant parti de ses compétences de pointe en intelligence artificielle et IA générative, en cloud, et en data, ainsi que de son expertise sectorielle et de son écosystème de partenaires.

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Parsio - Founding Backend/AI EngineerOSS Ventures

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