Senior Applied Scientist, GenAI & ML Systems
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Job Location:
Monthly Salary:
Posted on:
12 hours ago
Vacancies:
1 Vacancy
Job Summary
Company overview:
TraceLinks software solutions and Opus Platform help the pharmaceutical industry digitize their supply chain and enable greater compliance visibility and decision making. It reduces disruption to the supply of medicines to patients who need them anywhere in the world.
Founded in 2009 with the simple mission of protecting patients today Tracelink has 8 offices over 800 employees and more than 1300 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.
Tracelink is recognized as an industry leader by Gartner and IDC and for having a great company culture by Comparably.
We are seeking a highly experienced Senior ML Engineer GenAI & ML Systems to lead the design architecture and implementation of advanced agentic AI systems within our next-generation supply chain platforms (SCP)
This role is hands-on and execution-focused. You will design build deploy and maintain large-scale multi-agent systems capable of reasoning planning and executing complex workflows in dynamic non-deterministic environments. You will also own production concerns including context management knowledge orchestration evaluation observability and system reliability.
This position is ideal for a strong ML Engineer or Software Engineer with deep practical exposure to GenAI data science and modern ML systems who is comfortable working end-to-endfrom architecture through production deployment. Experience in life sciences supply chain or other regulated environments is a strong plus.
Key Responsibilities
Architect implement and operate large-scale agentic AI / GenAI systems that automate and coordinate complex supply chain workflows.
Design and build multi-agent systems including agent coordination planning tool execution long-term memory feedback loops and supervision.
Develop and maintain advanced context and knowledge management systems including:
RAG and Advanced RAG pipelines
Hybrid retrieval reranking grounding and citation strategies
Context window optimization and long-horizon task reliability
Own the technical strategy for reliability and evaluation of non-deterministic AI systems including:
Agent evaluation frameworks
Simulation-based testing
Regression testing for probabilistic outputs
Validation of agent decisions and outcomes
Fine-tune and optimize LLMs/SLMs for domain performance latency cost efficiency and task specialization (strong plus).
Design and deploy scalable backend services using Python and Java ensuring production-grade performance security and observability.
Implement AI observability and feedback loops including agent tracing prompt/tool auditing quality metrics and continuous improvement pipelines.
Apply and experiment with reinforcement learning or iterative improvement techniques within GenAI or agentic workflows where appropriate.
Collaborate closely with product data science and domain experts to translate real-world supply chain requirements into intelligent automation solutions.
Guide system architecture across distributed services event-driven systems and real-time data pipelines using cloud-native patterns.
Mentor engineers influence technical direction and establish best practices for agentic AI and ML systems across teams.
Required Qualifications
6 years of experience building and operating cloud-native SaaS systems on AWS GCP or Azure (minimum 5 years with AWS).
Strong ML Engineer / Software Engineer background with deep practical exposure to data science and GenAI systems.
Expert-level hands-on experience designing deploying and maintaining large multi-agent systems in production.
Proven experience with advanced RAG and context management including memory state handling tool grounding and long-running workflows.
6 years of hands-on Python experience delivering production-grade systems.
Practical experience evaluating monitoring and improving non-deterministic AI behavior in real-world deployments.
Hands-on experience with agent frameworks such as LangGraph AutoGen CrewAI Semantic Kernel or equivalent.
Solid understanding of distributed systems microservices and production reliability best practices.
Big Plus / Preferred Qualifications
Hands-on experience fine-tuning LLMs or SLMs for domain-specific tasks (training evaluation deployment).
Experience designing and deploying agentic systems in supply chain domains (logistics manufacturing planning procurement).
Strong knowledge of knowledge organization techniques including RAG Advanced RAG hybrid search and reranking.
Experience applying reinforcement learning reward modeling or iterative optimization in GenAI workflows.
Familiarity with Java and JavaScript/ECMAScript.
Experience deploying AI solutions in regulated or enterprise environments with governance security and compliance requirements.
Knowledge of life sciences supply chain or regulated industry ecosystems
Who You Are
A hands-on technical leader who moves seamlessly between architecture and implementation.
A builder who values practical production-ready solutions over prototypes.
Comfortable designing systems with probabilistic and emergent behavior.
Passionate about building GenAI systems that are reliable observable explainable and scalable.
A clear communicator who can align stakeholders and drive execution across teams.
Please see the Tracelink Privacy Policyfor more information on how Tracelink processes your personal information during the recruitment process and if applicable based on your location how you can exercise your privacy rights. If you have questions about this privacy notice or need to contact us in connection with your personal data including any requests to exercise your legal rights referred to at the end of this notice please contact .
Required Experience:
Senior IC
Key Skills
- Laboratory Experience
- Mammalian Cell Culture
- Biochemistry
- Assays
- Protein Purification
- Research Experience
- Next Generation Sequencing
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Flow Cytometry
About Company
TraceLink is the only network creation platform company that builds integrated business ecosystems with multienterprise applications - the true foundation for digitalization - delivering customer-centric agility and resiliency for end-to-end supply networks and leveraging the collecti ... View more
