Senior Software Engineer

Cryoport Systems; California (MO); On-site; USD 130,000 - 185,000; Full time

Job summary

Cryoport Systems is seeking a Senior Software Engineer to lead technical initiatives, optimize delivery, and steer architectural decisions across teams. You will build and support core value stream components, including AI-powered features and intelligent systems, enabling growth and reliability for our life sciences customers.

Join a team that values technical excellence, scalable systems, and collaboration with product managers, data scientists, and engineers to deliver high-impact solutions

Qualifications

• B.S. in CS or equivalent; MS preferred.
• 8+ years building multi-tier distributed web apps with Ruby, JavaScript, Python.
• 5+ years designing REST/JSON APIs and microservices.
• 2+ years hands-on AI/ML in production environments.
• Experience with LLMs, LangChain, vector DBs, and RAG pipelines.

Responsibilities

• Lead technical initiatives and drive architectural decisions.
• Build and evolve core value stream app components, including AI features.
• Mentor engineers and promote responsible AI development.
• Collaborate with product managers and designers to align tech with business goals.

Skills

AI/ML engineering

Microservices

LangChain

LLM APIs

Docker/Kubernetes

Ruby on Rails

Python

JavaScript/React

Education

B.S. in Computer Science

M.S. in Computer Science

Tools

Docker

Kubernetes

AWS

Elasticsearch

GitHub

JIRA

Job description

Cryoport Systems is a comprehensive supply chain partner for the life sciences industry, delivering specialized solutions to meet the challenges of the biopharmaceutical, cell and gene therapy, reproductive medicine, and animal health markets. Our offerings span logistics, BioServices and biostorage, cryopreservation, and consulting, ensuring the highest standards of quality and reliability for sensitive materials. With our expansive platform of management solutions and decades of temperature-controlled supply chain expertise, Cryoport Systems helps Enable the Outcome by supporting certainty and precision in the supply chain, whether advancing groundbreaking therapies, supporting families on their reproductive journeys, or enhancing animal health programs.

POSITION SUMMARY

As a Senior Software Engineer at Cryoport Systems, 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.

You will be responsible for building, evolving and supporting core value stream application components — including AI-powered features and intelligent systems — essential for our organization’s growth. Your leadership will ensure system success and foster technical excellence, allowing Cryoport Systems to deliver certainty and reliability across our business.

Key Responsibilities

1. Technical Expertise

• Implement scalable, resilient, and maintainable software systems aligned with technical roadmaps, including AI-powered features such as LLM integrations, RAG pipelines, and agentic workflows.
• Execute value stream initiatives in an agile environment, ensuring that features meet business and technical goals.
• Apply and ensure best practices in software development, including modularization, code quality, testing, security and data modelling.
• Establish engineering best practices around prompt management, AI evaluation frameworks, and observability for AI systems.

2. AI Engineering

• Design and build production-grade AI systems, integrating foundation models (e.g., OpenAI, Anthropic) via frameworks such as LangChain or LlamaIndex.
• Architect retrieval-augmented generation (RAG) pipelines and vector search solutions using tools like Pinecone, Weaviate, or pgvector.
• Evaluate and benchmark foundation models and open-source alternatives for suitability, performance, and cost-efficiency.
• Design and maintain scalable ML serving infrastructure and model deployment pipelines.
• Collaborate with data science teams to bring model-driven capabilities to production reliably.

3. Systems Thinking and Innovation

• Participate in technical discussions, architecture reviews, and roadmap planning.
• Contributed to the technical vision and architecture for the stream.
• Advocate for Domain-Driven Design (DDD) and loosely coupled architectures.
• Review and assess new technologies, frameworks, and tools to enhance efficiency and scalability.

Stream Alignment

• 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 objectives laid out no technical roadmaps.

Team Leadership and Collaboration

• Support and mentor 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.

Tooling/Technologies

• Ruby, Java, Python, JavaScript, MySQL, Docker, Elasticsearch, GitHub, JIRA, AWS
• Ruby on Rails, Scala, Micronaut, React
• LLM APIs (OpenAI, Anthropic), LangChain, LlamaIndex, vector databases, RAG pipelines

Qualifications

• B.S. in Computer Science or equivalent degree (required) / M.S. in Computer Science (preferred)
• 8+ 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.
• 5+ years architecting, implementing, and maintaining JSON API’s.
• 2+ years of hands‑on AI/ML engineering experience in production environments.
• Extensive knowledge of microservices, APIs, event-driven architectures, containerization (Docker, Kubernetes), and data modelling.
• Hands‑on experience with LLM APIs (OpenAI, Anthropic, etc.) and frameworks such as LangChain, LlamaIndex, or equivalent.
• Experience with vector databases (Pinecone, Weaviate, pgvector), semantic search architectures.
• Familiarity with ML serving infrastructure and cloud-based AI deployment patterns.
• Experience with model evaluation, prompt engineering, and AI observability tooling.
• Knowledge of fine-tuning techniques (LoRA, RLHF) or MLOps tooling (MLflow, Weights & Biases) is a plus.

Key Competencies

• Problem-Solving: Strong, detail-oriented analytical skills and a hands-on approach to troubleshooting and resolving technical challenges.
• Innovation: A forward-thinking mindset, constantly looking for ways to innovate and improve operations; passion for automating processes.
• Strategic Vision: Ability to align stream initiatives with broader business objectives.
• Collaboration: Excellent interpersonal skills and ability to collaborate across functional teams.