Partner with supply chain functional leads to elicit and document business requirements and translate them into technical specifications for AI-driven decision support tools, ensuring every solution delivers measurable business value.
Act as the primary technical lead for applied AI implementation. Take pre-developed models from internal partners or 3rd-party vendors (COTS) and successfully deploy them within the supply chain GCP space.
Work closely with Knowledge Graph engineering teams to execute model interface against enterprise ontologies, you will design decision-intelligence frameworks that proactively identify and mitigate risks across the global N-tier supplier network. Simulate 'what-if' scenarios using Generative AI and Graph analytics, and enable the supply chain to remain resilient against geopolitical, environmental, and logistical shocks, providing automated prescriptive solutions for supply-chain, logistics and capacity re-allocation before disruptions impact production.
Champion and implement AI-assisted development practices. Implement agentic workflows (e.g., AutoGen, CrewAI) and use LLM-based tools (e.g., GitHub Copilot, automated PR agents, and AI-generated documentation) to accelerate delivery with high code quality for the Decision Intelligence platform.
Design the 'connective tissue' between Knowledge Graph updates and model inference engines. Establish rigorous guardrail frameworks for toxicity, hallucination rates, and latency. Maintain automated pipelines that ensure decision-support tools are always powered by the most current data.
Develop reusable integration patterns and data contracts to ensure that AI solutions can be scaled across multiple business units without redundant engineering effort.

Requirements

Bachelor of Computer Science, Information Systems, Systems Programming or equivalent combination of relevant education and experience
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
3+ years of professional Software Development experience with proven progressive experience in AI/ML, data science, or advanced analytics, with a proven track record of delivering production-grade solutions in large enterprise environments.
2+ years in Python and SQL. Familiarity with Graph Query Languages (e.g., Cypher).
2+ years of demonstrated experience with MLOps principles and tools (e.g., Azure ML, AWS SageMaker, GCP AI Platform, Kubeflow, MLflow) and designing / implementing AI-specific SDLCs.
2+ years of experience designing, deploying, and maintaining LLM-powered applications in production, with focus on prompt engineering, RAG pipelines, safety controls, hallucination mitigation, observability, cost optimization, etc.
2+ years of technical expertise in cloud services (GCP/Vertex AI) and data integration patterns.

Benefits

Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up childcare and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
Paid time off and the option to purchase additional vacation time.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonSQLGraph Query LanguagesMLOpsAI/MLdata scienceadvanced analyticsLLM-powered applicationsprompt engineeringdata integration patterns

Soft Skills

collaborationproblem-solvingcommunicationleadershiporganizational skills

Certifications

Bachelor of Computer ScienceBachelor of EngineeringBachelor of Data Science