Sr. AI Architect

Job Summary

We are planning weekday interviews for Sr. Architect

Exp - 15-18 Years

Location will be - Pune only

No job hops.

Kindly note - We will consider only immediate joiners to 15 days.

Role Description

Job Description

Senior AI Architect, Individual Contributor

Purpose of the Position: The Senior Data AI Architect, L3 or L4 defines and assures enterprise-grade AI architectures that convert business needs into secure, scalable and measurable AI capabilities. The role provides hands-on architecture leadership across AI/ML, Generative AI, LLMs, Agentic AI and enterprise knowledge solutions, while aligning designs with enterprise, data, security, cloud and engineering standards. Success is achieved through technical authority, evidence-based decisions and cross-functional influence-not line-management accountability.

Key Responsibilities and Weightage

• AI Architecture Strategy & Governance - Define AI/ML, GenAI and agentic target architectures, standards, reusable patterns and roadmaps; ensure alignment to enterprise architecture and product strategy. 15%
• Solution Architecture & Decision Ownership - Translate use cases into end-to-end architectures covering models, prompts/context, data, vector stores, APIs, orchestration, cloud/runtime and human oversight; own trade-offs and AD%
• GenAI, RAG & Agentic AI - Architect LLM applications, RAG/enterprise knowledge integration, tool-using agents and multi-agent workflows; define grounding, memory, access-control and evaluation approaches. 15%
• AI Engineering, MLOps & LLMOps - Define lifecycle patterns for experimentation, versioning, CI/CD/CT, model/prompt deployment, evaluation, monitoring, rollback and operational support. 15%
• Responsible AI, Security & Compliance - Embed privacy, security, IP protection, explainability, fairness, transparency, human oversight and auditability; partner with data, CISO, legal and governance stakeholders.
• Reliability, Performance & Cost - Design for availability, resilience, latency, throughput, observability and capacity; optimize model, token, computing, storage and data costs. 10%
• Innovation, Advisory & Architecture Assurance - Evaluate technologies/vendors, lead prototypes and architecture reviews, support critical deliveries, and influence stakeholders through clear evidence and technical expertise. 10%

Role Requirements and Success Profile

Experience, Industry Exposure and Certification

• Experience 18+ years overall in software engineering, data/AI and architecture, including extensive ownership of complex enterprise solution architectures and substantial recent delivery experience in AI/ML and Generative AI. Demonstrated progression from engineering to architecture and technical decision ownership.
• Industry exposure Proven architecture experience in large, regulated or complex enterprises. Automotive, mobility, manufacturing, connected products, enterprise platforms or similar data-intensive domains is advantageous. Evidence of moving AI solutions from discovery/prototype to secure production operation is essential.
• Certifications Preferred-not mandatory: one or more current, role-relevant credentials such as Microsoft Certified: Azure AI Engineer Associate; AWS Certified Machine Learning Engineer - Associate and/or Solutions Architect - Professional; Google Cloud Professional Machine Learning Engineer and/or Professional Cloud Architect; NVIDIA generative-AI/LLM certification; Databricks Generative AI Engineer Associate; TOGAF or iSAQB. Equivalent demonstrated expertise is acceptable.

Core Technical Competencies

• AI solution architecture: Expert - enterprise AI/ML, GenAI and hybrid architecture
• LLMs & Generative AI: Expert - model selection, prompt/context engineering, guardrails

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.