TraceLink
Applied Scientist, GenAI
US - MA - Wilmington · Staff+ · Full-time
Sponsorship not specified$152k-$189kDetected 55 days ago
PythonCode ReviewVector DatabasesAWSGCPAzureCloud PlatformsCI/CDMachine LearningNLPLLMsRAGAgentic AIAI OrchestrationA/B TestingSupply ChainResearchCollaboration
About the role
- Powered by the Integrate-Once™ OPUS platform, TraceLink links more than 300,000 network participants, enabling multi-enterprise processes at global scale.
- Founded in 2009 with the simple mission of protecting patients, today Tracelink has 5 global offices, over 800 employees and more than 1700 customers in over 60 countries around the world.
- Our expanding product suite continues to protect patients and now also enhances multi-enterprise collaboration through innovative new applications such as MINT.
Responsibilities
- Hands-on ownership of building and shipping multi-agent systems (planner/executor, tool-using agents, supervisor patterns, routing, role-based agents) from prototype to production.
- Write production-quality code for agent orchestration, tool integration, memory/state design, and context management.
- Lead context engineering strategies for multi-agent coordination: prompt design, state persistence, agent handoffs, grounding, constraints, and safety controls.
- Implement evaluation frameworks for multi-agent systems covering quality, latency, cost, robustness, and failure mode detection.
- Collaborate with platform and product engineering to ensure solutions are cloud-native, secure, observable, and scalable (monitoring, logging, CI/CD).
- Optimize for cost and latency via model routing, caching, compression strategies, and inference efficiency improvements.
- (prompt orchestration, tool calling, memory/state design, routing, constraint handling)
- MS/PhD in CS/ML/NLP/Stats (or equivalent applied experience building production systems)
Requirements
- Experience with Advanced RAG, semantic search, embeddings, and cross-encoders
- Ability to translate ambiguous requirements into concrete architectures, metrics, and deliverables
- Required Knowledge & Experience
Nice to have
- Familiarity with enterprise constraints: privacy, security, data governance, permissions, auditability
- Experience designing and running GenAI observability: traces, prompt/versioning, tool call logging, feedback loops
- Proven experience deploying GenAI/ML systems in cloud environments (AWS/Azure/GCP)
- Experience with scalable inference and service operations: containers, APIs, observability, reliability practices
Compensation
- TraceLink is committed to providing competitive compensation and benefits to all employees.
Company info
- Tracelink is recognized as an industry leader by Gartner and IDC, and for having a great company culture by Comparably.
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