Job Title

Senior ML Engineer – GenAI & Agentic ML SystemsAbout the Role We are seeking a highly experiencedSenior ML Engineer – GenAI & ML Systemsto lead the design, architecture, and implementation of advancedagentic AI systemswithin our next-generation supply chain platforms. This role is hands-on and execution-focused. You will design, build, deploy, and maintainlarge-scale multi-agent systemscapable of reasoning, planning, and executing complex workflows in dynamic, non-deterministic environments. You will also own production concerns, includingcontext management, knowledge orchestration, evaluation, observability, and system reliability .This position is ideal for astrong ML Engineer or Software Engineerwith deep practical exposure toGenAI, data science, and modern ML systems , who is comfortable working end-to-end—from architecture through production deployment. Experience in life sciences supply chain or other regulated environments is a strong plus.Key Responsibilities Architect, implement, and operatelarge-scale agentic AI / GenAI systemsthat automate and coordinate complex supply chain workflows. Design and buildmulti-agent systems,including agent coordination, planning, tool execution, long-term memory, feedback loops, and supervision. Develop and maintainadvanced context and knowledge management systems , including: RAG andAdvanced RAGpipelines Hybrid retrieval, reranking, grounding, and citation strategies Context window optimization and long-horizon task reliability Own the technical strategy forreliability 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/SLMsfor domain performance, latency, cost efficiency, and task specialization (strong plus). Design and deploy scalable backend services usingPython and Java , ensuring production-grade performance, security, and observability. ImplementAI observability and feedback loops , including agent tracing, prompt/tool auditing, quality metrics, and continuous improvement pipelines. Apply and experiment withreinforcement learning or iterative improvement techniqueswithin 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+ yearsof experience building and operating cloud-native SaaS systems on AWS, GCP, or Azure (minimum5 years with AWS ). Strong ML Engineer / Software Engineer backgroundwith deep practical exposure to data science and GenAI systems. Expert-level, hands-on experiencedesigning, deploying, and maintaininglarge multi-agent systemsin production. Proven experience withadvanced RAG and context management , including memory, state handling, tool grounding, and long-running workflows. 6+ years of hands-on Python experiencedelivering production-grade systems. Practical experience evaluating, monitoring, and improvingnon-deterministic AI behaviorin real-world deployments. Hands-on experience with agent frameworks such asLangGraph, AutoGen, CrewAI, Semantic Kernel , or equivalent. Solid understanding ofdistributed systems, microservices, and production reliabilitybest practices.Big Plus / Preferred Qualifications Hands-on experience fine-tuning LLMs or SLMsfor domain-specific tasks (training, evaluation, deployment). Experience designing and deployingagentic systemsin supply chain domains (logistics, manufacturing, planning, procurement). Strong knowledge ofknowledge organization techniques , including RAG, Advanced RAG, hybrid search, and reranking. Experience applyingreinforcement learning, reward modeling, or iterative optimizationin GenAI workflows. Familiarity withJava and JavaScript/ECMAScript . Experience deploying AI solutions inregulated or enterprise environmentswith governance, security, and compliance requirements. Knowledge oflife sciences supply chainor regulated industry ecosystems.Who You Are Ahands-on technical leaderwho moves seamlessly between architecture and implementation. A builder who valuespractical, production-ready solutionsover prototypes. Comfortable designing systems withprobabilistic and emergent behavior . Passionate about building GenAI systems that arereliable, observable, explainable, and scalable . A clear communicator who can align stakeholders and drive execution across teams.