Jobs at Calliere

Build and support complex features across C#/.NET back-end services and React front ends. Responsibilities include technical design, API and data modeling, secure and tested coding, production troubleshooting, code reviews, mentoring, documentation, and improving engineering practices. Collaborate with Product, QA, DevOps, Technical Leads, and architecture teams while balancing delivery, maintainability, performance, accessibility, observability, and security.

Design and deploy production AI/ML systems, including data pipelines, RAG systems, agentic workflows, model integrations, APIs, observability, evaluations, guardrails, and cost optimization. Collaborate with product, design, and client stakeholders while contributing to architecture, code reviews, testing, deployment, and technical strategy. Build reliable, secure, scalable systems using modern LLM and cloud technologies.

Implements a scientific software platform for enterprise R&D customers by migrating data, modeling experimental workflows, and supporting customer meetings. The role interprets scientific datasets, collaborates with chemists and researchers, supports enterprise rollouts, manages smaller accounts, and shares customer feedback with product and engineering teams. Candidates need STEM training, laboratory research experience, fluent French, technical curiosity, customer confidence, and strong data skills.

Leads the partnerships function end to end, including partner revenue growth, new customer acquisition channels, partner integration into AI products, delivery health, and team building. Works closely with the CEO and product, engineering, growth, brand, and service delivery teams to align commercial opportunities with customer needs, manage partner relationships, meet contractual commitments, and shape commercial priorities.

Lead the architecture and hands-on development of an AI-enabled data migration platform for legal software. Own extraction, transformation, orchestration, data quality, observability, and scalable go-live workflows. Partner with product management to define roadmap priorities, lead a focused engineering team, make architectural decisions, contribute code, and apply AI to migration assessment, mapping, validation, and automation.

Lead the transformation of a profitable legal services company into an AI-native consumer law platform. Own the product and technology roadmap, build AI workflows across practice areas, improve the client portal, support law firm acquisitions, and hire and develop engineering, product, design, and data teams. The CTO will remain hands-on with coding while setting priorities and scaling the platform.

Build and deploy AI-powered software, full-stack applications, integrations, data pipelines, and automation for business processes. Partner with sales, finance, supply chain, production, and product teams to identify opportunities, launch measurable improvements, and own systems through testing, monitoring, documentation, training, and support. Establish engineering practices and connect ERP, accounting, commerce, shipping, spreadsheet, and plant data systems.

Leads and grows a distributed software engineering team building a scalable cloud data and analytics platform. Owns architecture, data modeling, technical delivery, roadmaps, product collaboration, agile planning, quality standards, security alignment, vendor relationships, and engineering KPIs. The role remains hands-on with coding, code reviews, documentation, data architecture, deployment, and development of SaaS data products using Azure or AWS, Microsoft Fabric or Snowflake, and Power BI.

Build and operate end-to-end agentic AI products from initial concept through production and product-market fit. Responsibilities include developing agents, retrieval and orchestration systems, integrating tools, shaping product direction with design and product partners, hardening systems after launch, and creating reusable engineering primitives. The role requires entrepreneurial ownership, production AI experience, strong engineering judgment, and the ability to work effectively with technical and commercial stakeholders.

Leads multiple engineering teams delivering AI-powered data connectivity solutions. Owns execution, delivery, technical direction, operational reliability, and cross-team coordination. Develops engineering talent through coaching, hiring, and performance management while partnering with Product and Engineering leadership on priorities and organizational planning. Guides architecture, cloud-native development, incident response, SLOs, and AI-assisted software development practices. Requires strong Java/Kotlin expertise, cloud architecture experience, and technical judgment across distributed systems.

Design, develop, test, maintain, and support enterprise software applications, APIs, services, integrations, and user-facing functionality. Translate requirements into technical designs, write maintainable code, participate in Agile planning and code reviews, troubleshoot production issues, and collaborate with analysts, QA, architects, and operations teams. Contribute to automated testing, technical documentation, production support, and continuous engineering improvement.

Develop secure, scalable, production-ready AI applications, services, and APIs. Integrate machine-learning and generative AI models into enterprise systems, build data and retrieval workflows, develop prompts, and implement testing, monitoring, logging, and evaluation. Collaborate with product, data, platform, and engineering teams while applying security, privacy, responsible-AI, and governance practices. Troubleshoot issues, document technical designs, participate in code reviews and Agile ceremonies, and support continuous improvement.

Lead end-to-end development of an AI-driven decision-support system for multi-sensor data. Responsibilities include building data ingestion and fusion pipelines, training and deploying supervised and unsupervised ML models, optimizing near-real-time inference, creating GPU-accelerated dashboards, integrating modular containerized systems, and supporting secure deployment and testing. The role works directly with the founder, owns technical delivery autonomously, and collaborates with subcontractors on human factors, model validation, and security auditing.

Manage and grow a product engineering team at a remote cloud cost-management software company. Lead prioritization, delivery, quality standards, recruiting, and cross-functional collaboration with product, design, and leadership. Help engineers ship customer-focused features spanning spend management, interfaces, data pipelines, visualizations, and application performance. Coach engineers, remove blockers, promote ownership, and guide tradeoffs between velocity and quality.

Design and build cloud cost-management capabilities, including forecasting, anomaly alerts, cost allocation, data pipelines, transformation models, visualizations, and reusable UI components. Own features end to end from planning through release while improving application reliability and performance. Collaborate closely with engineers and founding team members, contribute to technical design and roadmap decisions, and work pragmatically in a fast-moving distributed startup environment.

Build and maintain cloud infrastructure, automation, configuration management, and CI/CD pipelines. Operate Kubernetes, Helm, and Docker workloads across multiple public clouds; configure observability tooling; troubleshoot production systems spanning networking, databases, serverless functions, and caching; and participate in a 24/7 on-call rotation. The role also involves owning infrastructure projects end to end and collaborating across engineering and product teams.

Design and deliver backend services for a sophisticated B2B platform. Build durable APIs, data models, resilient workflows, and systems that handle failures, retries, and complex business rules. Improve developer tooling, observability, and operational reliability while contributing to architecture decisions and engineering standards. Partner with product, design, and customer-facing teams, translate ambiguous requirements into technical plans, mentor teammates, and maintain high-quality production software.

Senior backend engineer to architect and implement distributed, cloud-native backend services and public APIs that ingest and normalize high-volume IoT/sensor data. Lead design and deployment of resilient ingestion pipelines, workflow orchestration, authentication, and monitoring in AWS. Interface with enterprise clients, shape product and architecture, and drive engineering standards and automation.

Own and ship major parts of a core web application for power users. Build high-performance, stateful interfaces for search, transactions, and workflows. Collaborate with backend, product, and design to define and deliver end-to-end features with full ownership.

Own and improve backend services for an AI-native learning platform: build Python/Node.js services, design serverless/cloud-native architectures, implement event-driven workflows and advanced NoSQL models, integrate LLM-based features (RAG, embeddings, vector search), ensure production reliability, observability, testing, and frontend API integrations while collaborating in a cross-functional remote team.