Build the intelligent enterprise with us

Responsibilities

• Architect and implement AI agent systems with explicit tool boundaries, permissions, and escalation paths
• Build retrieval and grounding layers over enterprise data with permission-aware access and traceable citations
• Design evaluation suites and shadow-mode testing to validate AI behavior against real cases before release
• Collaborate with client engineering, security, and risk teams to move AI from pilot to production
• Mentor engineers and contribute to Artiminds practice standards and reusable patterns

Qualifications

• Significant experience delivering machine learning or LLM-based systems in production environments
• Strong Python skills and familiarity with frameworks such as LangGraph, Semantic Kernel, or equivalent
• Experience with at least one major cloud AI platform (Azure OpenAI, Amazon Bedrock, Vertex AI)
• Working knowledge of MLOps, evaluation methods, and responsible AI practices
• Ability to communicate technical trade-offs clearly to business stakeholders

Responsibilities

• Design and implement batch and streaming pipelines with testing, lineage, and observability
• Build governed data models, semantic layers, and certified datasets for analytics and AI consumers
• Harmonize complex source data, including retail, syndicated, and operational manufacturing data
• Implement data quality rules and monitoring close to the source
• Document platforms and transfer knowledge to client engineering teams

Qualifications

• Hands-on experience with Databricks, Snowflake, or Microsoft Fabric in production
• Strong SQL and Python or Scala skills; experience with dbt or similar transformation frameworks
• Familiarity with Spark, Kafka, or cloud-native streaming services
• Understanding of data governance, master data, and data modeling practices
• Experience in CPG, retail, or manufacturing data is a plus

Responsibilities

• Design secure, governed landing zones and target architectures aligned to client business priorities
• Lead application portfolio assessments and disposition decisions
• Define infrastructure-as-code standards, CI/CD patterns, and platform operating models
• Guide migration waves, cutover planning, and modernization of priority applications
• Establish FinOps practices and cost governance with client teams

Qualifications

• Deep experience architecting solutions on at least one major cloud provider; multi-cloud exposure preferred
• Proficiency with Terraform, Kubernetes, and modern DevOps tooling
• Strong understanding of cloud security, identity, networking, and compliance frameworks
• Experience leading enterprise migration or modernization programs
• Relevant cloud architecture credentials are welcome

Responsibilities

• Lead process discovery and fit-gap analysis for SAP, Microsoft Dynamics 365, or Salesforce programs
• Design integration architectures using API-led and event-driven patterns
• Oversee configuration, extension, and data migration workstreams
• Advise clients on reducing customization debt and maintaining upgradeability
• Coordinate with implementation partners and client stakeholders across business and IT

Qualifications

• Multiple full-cycle implementations or major enhancements of an enterprise ERP or CRM platform
• Strong understanding of finance, supply chain, or manufacturing business processes
• Experience with integration platforms such as Azure Integration Services, MuleSoft, or Boomi
• Ability to translate business requirements into platform designs and clear documentation
• Consulting experience with executive-level stakeholders

Responsibilities

• Design integration architectures between plant systems and enterprise applications
• Define common asset and process data models across multiple manufacturing sites
• Lead OT/IT data flow design with attention to network segmentation and security
• Work with plant engineers and IT teams to contextualize and validate operational data
• Support AI and analytics use cases in quality, maintenance, and planning with reliable data foundations

Qualifications

• Experience integrating MES, SCADA, historian, or quality systems with ERP in manufacturing environments
• Familiarity with ISA-95, OPC UA, MQTT, and industrial connectivity platforms
• Understanding of event-driven integration and streaming technologies
• Experience working in discrete or process manufacturing plants
• Strong collaboration skills across operations, engineering, and IT

Responsibilities

• Design and execute structured testing of product visibility across AI assistants, AI search, and retailer algorithms
• Analyze product information accuracy, competitive positioning, and digital shelf performance
• Trace visibility gaps to root causes in product data, content, and syndication processes
• Build dashboards and reports that unify AI visibility and digital shelf metrics
• Present findings and recommendations to brand, e-commerce, and data stakeholders

Qualifications

• Experience in e-commerce analytics, digital shelf, category management, or product information management
• Strong analytical skills with SQL and Python or equivalent; Power BI or Tableau experience
• Understanding of how retailer search and recommendation systems and generative AI assistants work
• Familiarity with PIM and syndication platforms such as Salsify or Akeneo is a plus
• Clear written and verbal communication for executive audiences