Staff Software Engineer (Contingent)

Cryoport, Inc.•Remote - California, CA

About The Position

As a Staff Software Engineer at our organization, you will lead technical initiatives, optimize team delivery, and drive architectural decisions within one of our teams. You will collaborate closely with the technical leadership team to ensure deliverables align with the organization’s broader goals and support our clients’ needs, including the design and delivery of AI-powered capabilities. You will be responsible for building, evolving and supporting core value stream application components essential for our organization’s growth. Your leadership will ensure system success and foster technical excellence, allowing our team to deliver certainty and reliability across our business.

Requirements

B.S. in Computer Science or equivalent degree (required)
10+ years architecting, implementing, and maintaining 100,000+ lines of code multi-tier distributed web applications using Ruby (Ruby on Rails), J2EE, JavaScript (React, Node), Python, and other web technologies.
6+ years architecting, implementing, and maintaining JSON API’s.
Extensive knowledge of microservices, APIs, event-driven architectures, containerization (Docker, Kubernetes), and data modeling.
2+ years of hands-on AI/ML engineering experience in production environments.
Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.) and frameworks such as LangChain, LlamaIndex, or equivalent.
Experience with vector databases (Pinecone, Weaviate, pgvector) and semantic search architectures.
Familiarity with ML serving infrastructure and cloud-based AI deployment patterns.
Experience with model evaluation, prompt engineering, and AI observability tooling.
Strong, detail-oriented analytical skills and a hands-on approach to troubleshooting and resolving technical challenges.
A forward-thinking mindset, constantly looking for ways to innovate and improve operations; passion for automating processes.
Practical, hands-on judgment about where AI/LLM-based approaches add real value versus traditional engineering, with an eye toward reliability, cost, and responsible use.
Ability to align stream initiatives with broader business objectives.
Excellent interpersonal skills and ability to collaborate across functional teams.

Nice To Haves

M.S. in Computer Science (preferred)
Knowledge of fine-tuning techniques (LoRA, RLHF) or MLOps tooling (MLflow, Weights & Biases) is a plus.

Responsibilities

Architect, design and implement scalable, resilient, and maintainable software systems aligned with business objectives.
Execute value stream initiatives in an agile environment, ensuring that features meet business and technical goals.
Establish and enforce best practices in software development, including modularization, code quality, testing, security and data modeling.
Design, build, and productionize AI/ML and LLM-powered features (e.g., retrieval-augmented generation, agentic workflows) with the same rigor applied to core systems — including testing, observability, security, and cost/performance tradeoffs.
Participate in technical discussions, architecture reviews, and roadmap planning.
Define and evolve the technical vision and architecture for the stream.
Advocate for Domain-Driven Design (DDD) and loosely coupled architectures.
Evaluate and help introduce new technologies, frameworks, and tools to enhance efficiency and scalability.
Stay current on emerging AI/ML capabilities and identify practical opportunities to apply generative AI, automation, and intelligent tooling within the value stream.
Collaborate with product managers and stakeholders to understand business goals and translate them into technical requirements, including AI-driven capabilities.
Contribute to technical documentation and knowledge sharing across teams.
Ensure the team’s work aligns with the overall stream objectives and delivers measurable value to the business.
Mentor senior and mid-level engineers, fostering a culture of learning, technical ownership, and responsible AI development.
Work closely with product managers, designers, and engineering teams to align technical efforts with business goals.
Partner with platform and infrastructure teams to improve tooling, deployment pipelines, and cloud environments, helping to cultivate an ever-improving developer experience.