SymphonyAI
Job Description
We are seeking an experienced
AI Architect
to design, govern, and scale end-to-end AI solutions that deliver measurable business outcomes. This role sits at the intersection of data, machine learning, engineering, and product, translating business needs into robust, secure, and scalable AI architectures. The AI Architect will define reference architectures, select platforms and tools, and guide teams in building production‑grade AI systems across the enterprise.
Key Responsibilities
Platform Architecture & Vision
Own the end‑to‑end architecture for the AI platform, spanning:
Agent frameworks and orchestration layers
Semantic and knowledge graph foundations
Data and signal ingestion fabric
Model, reasoning, and tool‑execution services
Product and solution enablement layers
Establish modular, extensible reference architectures enabling rapid product and solution development.
Drive architectural consistency across teams building on AI Platform.
Agentic & Knowledge‑Driven AI Systems
Architect agent‑based systems capable of reasoning, planning, retrieval, and execution across enterprise workflows.
Design hybrid AI architectures combining:
LLMs and multi‑model stacks
Knowledge graphs and ontologies
Vector retrieval and semantic search
Deterministic services and enterprise APIs
Lead the evolution of CINDE’s semantic layer and retail knowledge foundation.
Solution Architecture & Business Enablement
Partner with Product, Engineering, and Business leaders to translate strategy into scalable technical systems.
Architect AI solutions across retail and CPG domains, including:
Forecasting, demand intelligence, and optimization
Price, promotion, and assortment intelligence
Shopper personalization and retail media
Store, shelf, and inventory intelligence
Enterprise revenue and decision automation
Ensure architectures directly support revenue growth, product velocity, operational efficiency, and customer impact.
AI Platform Engineering, MLOps & LLMOps
Define CINDE standards for:
Model lifecycle management
Agent deployment and orchestration
Prompt, workflow, and tool governance
Experimentation and evaluation pipelines
Design scalable MLOps / LLMOps / AgentOps foundations:
CI/CD for AI and agent workflows
Observability, telemetry, and quality measurement
Versioning, monitoring, drift detection, and retraining
Governance, Security & Responsible AI
Embed enterprise‑grade security, privacy, and compliance into CINDE architecture.
Define and enforce Responsible AI frameworks across the platform:
Explainability, traceability, and auditability
Bias, safety, and risk controls
Regulatory and customer‑facing compliance readiness
Partner closely with Security, Legal, and Compliance leaders.
Technical Leadership & Influence
Serve as a technical north star across product and engineering organizations.
Mentor senior engineers, architects, and data scientists.
Influence platform decisions across multiple business units without direct authority.
Continuously assess emerging technologies and translate them into advantage.
Required Technical Skills
Cloud & Platform Engineering
Deep experience with AWS, Azure, or GCP AI platforms
Kubernetes, containerized AI workloads, and distributed systems
Infrastructure as Code and environment automation
Data, Knowledge & Signal Fabric
Enterprise data lakes and lakehouse platforms
Streaming and real‑time signal architectures
Strong distributed data processing background
Knowledge graph platforms, semantic modeling, and ontologies
AI, ML & Agentic Systems
Expert‑level Python
Production ML frameworks (PyTorch, TensorFlow, scikit‑learn)
Agent frameworks and orchestration platforms
Multi‑model system design
GenAI & Knowledge‑Grounded AI
Commercial and open‑source LLM ecosystems
RAG and hybrid retrieval architectures
Vector databases and embedding systems
Fine‑tuning, evaluation, and prompt lifecycle management
MLOps / LLMOps / AgentOps
MLflow, Kubeflow, or equivalent platforms
CI/CD for AI workloads
Model and agent observability, testing, and governance
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Design, Art/Creative, and Information Technology
Industries Software Development
Location Albany, NY
#J-18808-Ljbffr
We are seeking an experienced
AI Architect
to design, govern, and scale end-to-end AI solutions that deliver measurable business outcomes. This role sits at the intersection of data, machine learning, engineering, and product, translating business needs into robust, secure, and scalable AI architectures. The AI Architect will define reference architectures, select platforms and tools, and guide teams in building production‑grade AI systems across the enterprise.
Key Responsibilities
Platform Architecture & Vision
Own the end‑to‑end architecture for the AI platform, spanning:
Agent frameworks and orchestration layers
Semantic and knowledge graph foundations
Data and signal ingestion fabric
Model, reasoning, and tool‑execution services
Product and solution enablement layers
Establish modular, extensible reference architectures enabling rapid product and solution development.
Drive architectural consistency across teams building on AI Platform.
Agentic & Knowledge‑Driven AI Systems
Architect agent‑based systems capable of reasoning, planning, retrieval, and execution across enterprise workflows.
Design hybrid AI architectures combining:
LLMs and multi‑model stacks
Knowledge graphs and ontologies
Vector retrieval and semantic search
Deterministic services and enterprise APIs
Lead the evolution of CINDE’s semantic layer and retail knowledge foundation.
Solution Architecture & Business Enablement
Partner with Product, Engineering, and Business leaders to translate strategy into scalable technical systems.
Architect AI solutions across retail and CPG domains, including:
Forecasting, demand intelligence, and optimization
Price, promotion, and assortment intelligence
Shopper personalization and retail media
Store, shelf, and inventory intelligence
Enterprise revenue and decision automation
Ensure architectures directly support revenue growth, product velocity, operational efficiency, and customer impact.
AI Platform Engineering, MLOps & LLMOps
Define CINDE standards for:
Model lifecycle management
Agent deployment and orchestration
Prompt, workflow, and tool governance
Experimentation and evaluation pipelines
Design scalable MLOps / LLMOps / AgentOps foundations:
CI/CD for AI and agent workflows
Observability, telemetry, and quality measurement
Versioning, monitoring, drift detection, and retraining
Governance, Security & Responsible AI
Embed enterprise‑grade security, privacy, and compliance into CINDE architecture.
Define and enforce Responsible AI frameworks across the platform:
Explainability, traceability, and auditability
Bias, safety, and risk controls
Regulatory and customer‑facing compliance readiness
Partner closely with Security, Legal, and Compliance leaders.
Technical Leadership & Influence
Serve as a technical north star across product and engineering organizations.
Mentor senior engineers, architects, and data scientists.
Influence platform decisions across multiple business units without direct authority.
Continuously assess emerging technologies and translate them into advantage.
Required Technical Skills
Cloud & Platform Engineering
Deep experience with AWS, Azure, or GCP AI platforms
Kubernetes, containerized AI workloads, and distributed systems
Infrastructure as Code and environment automation
Data, Knowledge & Signal Fabric
Enterprise data lakes and lakehouse platforms
Streaming and real‑time signal architectures
Strong distributed data processing background
Knowledge graph platforms, semantic modeling, and ontologies
AI, ML & Agentic Systems
Expert‑level Python
Production ML frameworks (PyTorch, TensorFlow, scikit‑learn)
Agent frameworks and orchestration platforms
Multi‑model system design
GenAI & Knowledge‑Grounded AI
Commercial and open‑source LLM ecosystems
RAG and hybrid retrieval architectures
Vector databases and embedding systems
Fine‑tuning, evaluation, and prompt lifecycle management
MLOps / LLMOps / AgentOps
MLflow, Kubeflow, or equivalent platforms
CI/CD for AI workloads
Model and agent observability, testing, and governance
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Design, Art/Creative, and Information Technology
Industries Software Development
Location Albany, NY
#J-18808-Ljbffr