Senior Software Engineer

Cryoport Systems; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Cryoport Systems is seeking a Senior Software Engineer to lead technical initiatives, shape architecture, and drive delivery across value streams.

You will mentor engineers, collaborate with product, data science, and AI teams to build production-grade systems and AI features using Ruby, Java, Python, and JavaScript.

This role emphasizes domain-driven design, observability, secure software practices, and scalable cloud-native solutions to support Cryoport's expanding life sciences platform.

Qualifications

• BS in CS or equivalent; MS preferred.
• 8+ years architecting, implementing, and maintaining 100,000+ lines of code in Ruby on Rails, J2EE, JS (React/Node), Python.
• 5+ years architecting JSON APIs.
• 2+ years hands-on AI/ML engineering in production.
• Extensive knowledge of microservices, APIs, event-driven architectures, Docker, Kubernetes, and data modeling.
• Hands-on with LLM APIs and LangChain, LlamaIndex.
• Experience with vector databases (Pinecone, Weaviate, pgvector) and semantic search.
• Familiarity with ML serving infrastructure and cloud deployment patterns.
• Experience with model evaluation, prompt engineering, and AI observability tooling; LoRA/RLHF or MLOps a plus.

Responsibilities

• Technical Expertise: build scalable, maintainable software aligned with roadmaps.
• Implement AI-powered features like LLM integrations and RAG pipelines.
• Lead agile value stream initiatives and ensure alignment with business goals.
• Apply best practices in modularization, testing, security, and data modeling.
• Establish engineering best practices around prompt management and observability for AI systems.
• AI Engineering: design production-grade AI systems with foundation models (OpenAI, Anthropic) via LangChain/LlamaIndex.
• Architect retrieval-augmented generation pipelines and vector search using Pinecone/Weaviate/pgvector.
• Evaluate models and frameworks for performance, cost, and suitability.
• Design and maintain scalable ML serving infra and deployment pipelines.
• Collaborate with data science teams to bring model-driven capabilities to production.

Skills

Ruby on Rails

Java

JavaScript

Python

J2EE

React

Node.js

JSON APIs

AI/ML engineering

LLM APIs

Education

B.S. in Computer Science or equivalent

M.S. in Computer Science (preferred)

Tools

Docker

Kubernetes

LangChain

LlamaIndex

Pinecone

Weaviate

pgvector

OpenAI API

Anthropic

GitHub

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

• 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 modeling.
• Establish engineering best practices around prompt management, AI evaluation frameworks, and observability for AI systems.
• 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.
• 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 modeling.
• 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.