AI/ML Architect

🔹 Key Responsibilities:
• Design end-to-end AI/ML architectures including data ingestion, feature stores, model training pipelines, and real-time inference services
• Build and optimize MLOps practices (CI/CD for ML) for automated deployment, monitoring, and retraining
• Collaborate with Salesforce and Digital Engineering teams to integrate AI capabilities such as Agentforce and custom LLMs into business workflows
• Evaluate and select AI tools, frameworks, and cloud platforms across AWS, Azure, and GCP
• Optimize model latency, throughput, and cloud infrastructure costs through architectural reviews
🔹 Technical Requirements:
• 7+ years of software engineering and data architecture experience
• 3+ years focused on ML systems
• Strong expertise with AWS SageMaker, Azure ML, Databricks
• Hands-on experience designing RAG architectures
• Knowledge of vector databases like Pinecone, Weaviate, and Milvus
• Experience with LangChain, LlamaIndex, Spark, Flink, or Snowflake
• Understanding of SOC2, GDPR, HIPAA, data residency, and model privacy
🔹 Soft Skills:
• Strong problem-solving ability to convert business challenges into technical solutions
• Passion for mentoring ML Engineers and conducting code reviews