Principal Solution Architect

Job Description

Skill Set

• Analytics & Insights

• Total Experience :

• 15.00 to 20.00 Years

• No of Openings :

• 1

• Job Post Date :

• 09/07/2026

• Job Expiry Date :

• 20/08/2026

• Domain :

• IT

• Location :

• PUNE [India]

• Job Reference No :

• 4095439

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• Job Summary

• Job Description ‿ AI Architect (P2 / Offshore)

Role Overview

We are seeking a seasoned AI Architect to design and solution enterprise scale AI, Generative AI, Agentic AI, and LLM powered platforms for COE. The role focuses on scalable AI architecture, production deployment, governance, security, observability, and business value led solutioning across cloud and hybrid environments. Experience with Azure and AWS AI services is mandatory; exposure to SLM, domain SLM, ontology, and Knowledge Graphs is an added advantage.

Experience

Up to 18 years of overall IT experience

4+ years in AI/ML, Data Science, Advanced Analytics, GenAI, or Agentic AI

Proven experience in enterprise AI architecture, pre sales, RFPs, POCs, and production grade deployments

Exposure to AI use cases across BFSI, Manufacturing, Telecom, Healthcare, or similar domains

Key Responsibilities

Architecture & Solutioning

Define end to end AI, GenAI, and Agentic AI architectures for enterprise scale solutions.

Design LLM based systems including RAG, fine tuning, instruction tuning, multi agent orchestration, and autonomous workflows.

Translate business problems into scalable AI solutions across enterprise data platforms, Azure, AWS, and hybrid deployments.

Create reusable AI blueprints, accelerators, reference architectures, and governance models.

Engineering, Productionization & Governance

Architect robust data ingestion, feature engineering, model pipelines, and multimodal data integration.

Guide predictive, prescriptive, generative AI, NLP/NLU, semantic search, chatbot, and summarization solutions.

Implement MLOps/LLMOps, model lifecycle management, monitoring, observability, and continuous improvement.

Drive evaluation for accuracy, hallucination mitigation, bias, explainability, latency, cost, and scalability.

Embed Responsible AI, Zero Trust, data privacy, compliance, safety guardrails, and AI governance.

Stakeholder Engagement & Leadership

Lead client facing technical discussions, PoCs, demos, pre sales solutioning, and strategic AI advisory.

Collaborate with business stakeholders, product teams, and delivery teams to align AI solutions with outcomes.

Mentor data scientists, ML engineers, and AI developers on architecture, coding standards, and lifecycle best practices.

Evaluate emerging GenAI, Agentic AI, multimodal AI tools, platforms, frameworks, and accelerators.

Core Technology Stack

Cloud & AI: Azure AI, Azure OpenAI, AI Foundry, Fabric IQ, AWS SageMaker, AWS Bedrock, Databricks

AI/ML/GenAI: ML, Deep Learning, NLP/NLU, Computer Vision, LLMs, RAG, embeddings, vector databases, prompt engineering, fine tuning

Frameworks: Python, Pandas, NumPy, Scikit learn, PyTorch, TensorFlow, LangChain, LangSmith, Langfuse, LlamaIndex, Semantic Kernel, FastAPI, Flask

Data & Architecture: Knowledge Graphs, APIs, microservices, event driven architecture, enterprise integration patterns

DevOps/MLOps: Git, CI/CD, Docker, Kubernetes, MLflow, Kubeflow

Key Skills & Competencies

Strong architectural mindset, problem solving ability, and enterprise solution design expertise

Excellent communication, stakeholder management, consulting, and client facing skills

Ability to connect AI architecture with measurable business value

Strong understanding of security, governance, Responsible AI, and scalable AI delivery

Qualifications

• Background in Data Science, AI/ML, Computer Science, or related discipline

• Azure and AWS AI certifications preferred

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