Jobs at Calliere

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.

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.

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.

Embed with client teams to design, build, and ship AI-driven integrations and automations. Responsibilities include prompt and retrieval design, prototyping with no-code tools and custom Python/JavaScript, hardening prototypes for production (reliability, logging, monitoring, access control), handling sensitive data, producing runbooks/specs, and collaborating with platform and engagement leads to drive adoption and reusable patterns.

Embed as the senior technical lead inside portfolio companies to discover business problems, architect and ship production AI systems (model/provider selection, retrieval/grounding, guardrails), own reliability and deployment end-to-end, mentor engineers, and convert solutions into reusable patterns and platform assets.

Design and build a high-performance consumer marketplace platform. Implement onboarding, search, booking/ordering flows, and lifecycle management. Create third-party integrations, contribute to frontend architecture and backend services, and partner with product and design. Own features end-to-end from concept through deployment while ensuring code quality and scalable data models.

Design and build backend systems and internal tooling for AI-native products: secure data access for agents, agent orchestration, evaluation/observability for non-deterministic outputs, performance and latency optimization, and end-to-end feature ownership from concept to production.

Lead technical POCs and pre-sales engagements to turn proofs-of-concept into production deployments. Troubleshoot complex integrations (identity, security, networking, observability), design custom solutions, run onboarding and enablement, and act as the technical lead during sales to ensure successful rollout and adoption.

Lead a cross-functional web platform team owning the CMS, AI-assisted landing page tooling, design system, and web performance. Partner with product, design, and growth to drive acquisition/onboarding, provide hands-on technical direction, coach engineers, and deliver high-quality, scalable web platform capabilities.

Lead and grow an engineering squad of 8–15 engineers, owning hiring, career development, performance, budget, headcount, delivery, and team results. Partner with engineering managers, Product, and Delivery to prioritize customer value and ship predictably. Drive AI-native engineering practices and continuous improvement in a remote, high-growth startup environment. This is a people-leadership role rather than a hands-on coding position.

Lead the data migration practice and analysts, owning complex customer migrations from legacy legal and accounting systems through go-live. Build C# and SQL conversion tooling, troubleshoot databases and cloud servers, document migration logic, and guide nontechnical customers through exports. Support AWS and Azure SOC 2 controls, data residency, retention, and AI-assisted development.

Build and maintain C# and SQL data migration tooling, staging schemas, scripts, and cloud automation. Lead complex legal accounting migrations, troubleshoot databases and cloud servers, write custom SQL, and support migration analysts with technical guidance. Create client-facing documentation, map and validate data, enforce SOC 2 and data residency controls across AWS and Azure, and use AI coding tools to automate recurring work.

Lead a player-coach engineering team building AI agents that create, launch, and optimize marketing campaigns. Own technical strategy, roadmap delivery, architecture, reliability, hiring, and team development. Solve problems involving content generation, customer context management, marketing insights, and campaign orchestration across advertising and lifecycle platforms.

Own the end-to-end design and implementation of Loancrate’s user experience, from Figma wireframes through accessible React and TypeScript components. Build and maintain a scalable shadcn/ui design system and component library, translate mortgage workflows into intuitive experiences, and establish consistent visual and interaction standards in partnership with product and engineering.

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.

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.

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.

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.