Artificial Intelligence Architect-Immediate joiner

Synechron; Pune District, Bengaluru, Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Synechron is seeking an Enterprise AI Architecture lead to shape AI/ML strategy across functions, from use-case prioritization to governance. You will design scalable reference architectures, drive MLOps and LLMOps, and partner with stakeholders to translate business problems into AI-powered solutions.

Strong cloud, data engineering, and governance experience are essential for delivering enterprise-grade AI platforms.

Qualifications

• 12+ years in Technology Architecture, Data Engineering, AI/ML, or Enterprise Solution Design.
• Strong expertise in AI/ML, Generative AI, LLMs, MLOps, and Cloud Architecture.
• Experience designing enterprise-scale AI solutions on Azure, AWS, or GCP.
• Hands-on knowledge of Python, TensorFlow, PyTorch, LangChain, Vector Databases, Azure AI Services, OpenAI, Databricks, MLflow, and Kubernetes.
• Strong understanding of data platforms, model lifecycle management, inference architecture, and AI governance.
• Excellent stakeholder management, consulting, and communication skills.

Responsibilities

• AI Use Case Definition & Business Value Realization: Partner with stakeholders to identify, evaluate, and prioritize AI/ML use cases with measurable outcomes.
• AI Architecture & Solution Design: Design scalable end-to-end AI/ML reference architectures for data, models, deployment, monitoring, and retraining.
• AI Platform & Technology Strategy: Develop AI/ML platform strategies; lead MLOps, LLMOps, and CI/CD integration.
• Governance, Security & Responsible AI: Embed Responsible AI, ensure security, privacy, regulatory compliance, and risk controls.

Skills

AI/ML Strategy

LLMs

MLOps

Cloud Architecture

Python

TensorFlow

PyTorch

LangChain

Vector Databases

OpenAI

Databricks

Kubernetes

Stakeholder Mgmt

Consulting

Communication

Tools

Azure

AWS

GCP

Databricks

MLflow

Kubernetes

Vector Databases

Job description

Key Responsibilities

AI Use Case Definition & Business Value Realization

• Partner with business stakeholders to identify, evaluate, and prioritize AI/ML use cases across functions such as Operations, Customer Experience, Risk, Finance, HR, Supply Chain, and IT.
• Define measurable business outcomes, KPIs, and value propositions including productivity improvement, cost optimization, revenue growth, and enhanced customer experience.
• Drive technology-led use cases such as Intelligent Automation, AIOps, Predictive Maintenance, Anomaly Detection, Knowledge Assistants, and Developer Productivity solutions.
• Convert complex business challenges into AI-powered solution approaches and implementation roadmaps.

AI Architecture & Solution Design

• Design scalable end-to-end AI/ML reference architectures covering data ingestion, feature engineering, model development, deployment, monitoring, and retraining.
• Define architecture patterns for Machine Learning, Deep Learning, Generative AI, and Large Language Model (LLM) solutions.
• Architect real-time and batch inference systems across cloud, hybrid, and on-premise environments.
• Ensure solutions meet enterprise standards for scalability, security, reliability, governance, and cost efficiency.

AI Platform & Technology Strategy

• Develop AI/ML platform strategies leveraging cloud-native, open-source, and commercial technologies.
• Provide architectural leadership for MLOps and LLMOps implementation, model lifecycle management, and CI/CD integration.
• Evaluate emerging AI technologies and recommend build, buy, or partner approaches.
• Drive standardization and best practices for enterprise AI platforms.

Governance, Security & Responsible AI

• Embed Responsible AI principles, including fairness, explainability, transparency, and ethical AI usage.
• Ensure compliance with enterprise security, privacy, regulatory, and risk management requirements.
• Collaborate with governance, security, and compliance teams to establish AI control frameworks and guardrails.

Required Skills & Qualifications

• 12+ years of experience in Technology Architecture, Data Engineering, AI/ML, or Enterprise Solution Design.
• Strong expertise in AI/ML, Generative AI, LLMs, MLOps, and Cloud Architecture.
• Experience designing enterprise-scale AI solutions on Azure, AWS, or GCP.
• Hands-on knowledge of AI frameworks and platforms such as Python, TensorFlow, PyTorch, LangChain, Vector Databases, Azure AI Services, OpenAI, Databricks, MLflow, and Kubernetes.
• Strong understanding of data platforms, model lifecycle management, inference architecture, and AI governance.
• Excellent stakeholder management, consulting, and communication skills.