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.

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.

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.

Lead and grow the bioinformatics function by mentoring a senior team, defining strategy and processes, partnering with product and engineering, translating biological insight into production-grade tools, and driving hiring and standards for large-scale genomics workflows.

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.

Develop and run reproducible analysis pipelines for NGS and other omics data, perform QC, integrate and harmonize datasets, generate cohort summaries and visualizations, and communicate results to collaborators.

Design, build, and operate scalable backend systems and APIs across a distributed service-oriented architecture. Own features end-to-end, partner with product stakeholders, ship shared infrastructure, and maintain high code quality. Participate in an on-call rotation and collaborate in a distributed North American team to deliver reliable, high-performance user experiences.

Build and maintain platform systems that provision, secure, and observe isolated agent execution environments. Design reusable primitives for queues, jobs, locks, and service-bus mechanics. Extend Pulumi-based IaC, work with containers, Linux internals, storage, permissions, logging, and runtime debugging. Ship reliable, maintainable infrastructure-driven application code and collaborate in a small cross-functional team.