Calliere Group

• Take ownership of complex engineering initiatives, leading technical design, implementation, delivery, and ongoing operational excellence. • Design, build, and maintain scalable software solutions using technologies such as C#, .NET Framework, SQL Server, React, jQuery, DocumentDB (MongoDB), Azure, and related integration platforms. • Develop and support modern service architectures, including RESTful APIs, GraphQL, modular monoliths, microservices, and event- or integration-driven solutions as appropriate. • Partner closely with Architecture, Product, and DevOps to define technical solutions that are scalable, reliable, performant, secure, and aligned with platform strategy. • Provide technical leadership and guidance through solution design, code reviews, mentoring, estimation, and hands-on problem solving. • Contribute to and improve engineering practices such as CI/CD, automated testing, observability, release quality, and operational readiness using Azure DevOps and related tooling. • Apply sound engineering principles and practices such as domain-driven design (DDD), test-driven development (TDD), vertical slice architecture (VSA), and clean modular design where appropriate. • Identify and resolve system bottlenecks, reliability concerns, and performance issues across applications, services, data stores, and integrations. • Leverage AI-enabled tools such as Codex, Claude Code, or similar technologies to improve engineering efficiency and software delivery outcomes. • Collaborate effectively across teams and stakeholders to drive clear technical decisions, reduce risk, and deliver measurable results.

• Build and evolve the systems that provision, update, secure, and observe isolated agent execution environments • Design reusable abstractions around queues, locks, background job processing, and service-bus mechanics • Extend and refine the infrastructure-as-code foundation (Pulumi) • Work directly with Linux systems, persistent storage, OS-level disks, container boundaries, permission models, logging pipelines, and runtime debugging • Operate within a small, high-ownership, cross-functional team running weekly delivery cycles

• Contribute across the stack with a primary emphasis on backend systems. • Design, build, and maintain scalable services and APIs. • Contribute to product features end-to-end. • Maintain and extend integrations while ensuring systems can scale with growth. • Diagnose and resolve performance issues, bugs, and developer experience challenges. • Contribute to ongoing improvements in engineering practices and architecture. • Example initiatives may include improving how users interpret performance data, building unified data access layers, and handling large-scale ingestion of external data sources.

• Build and own backend services in Python and Node.js, architect serverless compute layers, and develop the APIs that tie frontend experiences to the underlying data and logic. • Contribute to sophisticated workflow engines; state machines, asynchronous event pipelines, and reliable retry/failure patterns across distributed services. • Design and evolve RESTful interfaces, integrate third-party and internal systems, and leverage advanced NoSQL data modeling techniques (composite key strategies, transactional operations) to keep things fast and correct under load. • Monitor, debug, and continuously improve system observability and deployment reliability on cloud-native infrastructure. • Collaborate across time zones, contribute meaningfully in code reviews, take end-to-end ownership of features, and help shape how the team works, not just what it ships.

• Design, implement, and deploy AI/ML systems end-to-end, from prototypes to hardened production services • Build and maintain data pipelines, retrieval layers, and training/inference workflows that support LLM and other model types • Develop and evolve retrieval-augmented generation (RAG) setups, including chunking strategies, embedding selection, and vector search design • Implement and tune agentic / multi-step workflows that orchestrate tools, APIs, and models to complete complex tasks • Add observability around AI behavior: evaluations, logging, metrics, and guardrails to monitor quality, drift, and failures • Integrate models with existing application backends and APIs, and design clean interfaces for internal and external consumers • Optimize systems for performance and cost (token usage, caching strategies, routing between models, etc.) • Contribute to architecture decisions, code reviews, and technical strategy within your team

• Build and maintain backend services in Node.js, including serverless components (for example, functions-as-a-service and API gateways) • Design and integrate APIs that power web frontends, partner integrations, and AI-augmented features • Contribute to frontend work using modern state management and interaction patterns, with an emphasis on accessibility and keyboard-friendly UI • Write clean, well-structured, and well-tested code with a strong focus on automated unit and integration tests • Support the design and maintenance of workflows using orchestration tools such as workflow engines or state machines • Contribute to event-driven and asynchronous processing using queues, pub/sub, or similar messaging patterns • Improve reliability by strengthening error handling, retries, and failure recovery paths • Develop and evolve RESTful APIs within a modular or microservices-style architecture • Integrate with large internal and external systems, including data platforms and institutional services • Help optimize performance and scalability of services, including thoughtful schema and access-pattern design for SQL or NoSQL stores • Implement secure data handling practices aligned with privacy and compliance expectations • Investigate and resolve issues in production environments, collaborating with more senior team members where needed • Contribute to logging, monitoring, and debugging workflows so the team can see and trust what the system is doing in real time • Support deployment and release processes in a cloud-native environment, including reviewing and improving pipelines over time • Work closely with distributed, cross-functional teams building large-scale platforms in domains such as education, financial services, or enterprise SaaS • Participate in code reviews, design sessions, and technical planning • Take ownership of features spanning UI, API, and data layers, driving them from definition through to production rollout • Continually grow your skills, staying current with modern Node.js, cloud, and frontend practices

• Design and build REST APIs and web applications for cloud services and on-site device configuration, monitoring, and management • Develop intuitive management UIs for both cloud-based workflows and local hardware deployment • Architect backend services that bridge cloud (AWS) and on-premises AI compute environments • Design low-latency database schemas covering job tracking, results storage, audit logging, and device management • Build and maintain containerized AI inference pipelines deployed on both cloud and dedicated GPU hardware • Implement end-to-end observability (telemetry, logging, alerting) across distributed environments • Identify and resolve performance bottlenecks in inference pipelines and large binary data workflows • Ensure software meets regulatory compliance standards (FDA 21 CFR Part 11/820, SOC2) • Partner closely with ML Engineering and Research teams to bring models into production • Contribute to design reviews, architecture discussions, and incident response rotations • Produce technical documentation for API specs, deployment guides, and regulatory submissions

• Process and analyze genomic and other omics datasets (for example, whole‑genome, whole‑exome, RNA‑seq, or similar assays), including alignment, quality assessment, variant detection, and annotation. • Develop, document, and maintain reproducible analysis pipelines using modern workflow or pipeline tools and scripting languages. • Implement best practices for data quality control, including monitoring run performance, detecting technical issues, and proposing corrective actions. • Integrate data from multiple sources, harmonize formats and metadata, and prepare analysis‑ready datasets. • Work with common bioinformatics tools and file formats (e.g., FASTQ, BAM/CRAM, VCF, BED, GFF/GTF) in a Unix/Linux environment. • Develop and execute exploratory analyses, including cohort‑level summaries, visualization of key metrics, and interpretation of variant and gene‑level results. • Prepare clear, well‑structured reports, figures, and presentation materials describing methods, assumptions, and findings for collaborators with diverse backgrounds. • Contribute to the evaluation and adoption of new algorithms, tools, and workflows in bioinformatics and data analysis. • Collaborate with other team members on study design, analysis plans, timelines, and prioritization of tasks.

• Guide and mentor a senior team, with real investment in their growth, performance, and long-term trajectory. • Define where bioinformatics is going and how it supports broader product and scientific goals. • Partner closely with product and engineering leaders to ensure the work being done actually moves the needle. • Represent the function at the leadership level—clearly communicating priorities, tradeoffs, and where investment is needed. • Bring structure to how projects are planned, executed, and tracked so things scale without chaos. • Work cross-functionally to translate biological insight into usable, production-grade tools. • Play a key role in hiring and shaping the team as it grows. • Keep the team aligned with evolving tools, standards, and best practices in the genomics space.

• Join a small, senior team at the early stages of building a product from scratch • Convert product requirements into thorough technical design documentation • Architect and implement backend services built to handle enterprise-scale demand • Design systems with high availability and fault tolerance in mind • Embed security thinking at every layer — application, API, and infrastructure • Own API design across both public-facing and internal service boundaries, including schema modeling and integration patterns • Work cross-functionally with product and design stakeholders throughout the development lifecycle • Thrive in a remote-first environment using a blend of synchronous video calls and async communication • Stay current with emerging technologies and approach new challenges with genuine curiosity • Take part in engineering hiring by conducting interviews and evaluating candidates