AI Engineer

Data And AIHyderabad

Posted On

18 Jun 2026

End Date

18 Jun 2027

Required Experience

7 - 8 Years

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Basic Section

Grade

Role

Senior Software Engineer

Employment Type

Full Time

Employee Category

Organisational

Group Company

NewVison

Company Name

New Vision Softcom & Consultancy Pvt. Ltd

Function

Business Units (BU)

Department/Practice

Data And AI

Department/Practice

Data Engineering

Region

APAC

Country

India

Base Office Location

Hyderabad

Working Model

Hybrid

Weekly Off

Hyderabad Office Standard

State

Telangana

Skills

Skill

AI

MACHINE LEARNING

PYTHON

C#

DOCKER AND KUBERNETES

CI/CD INTEGRATION

SQL

COSMOS DB

MACHINE LEARNING

REST API

Highest Education

GRADUATION/EQUIVALENT COURSE

CERTIFICATION

AWS CERTIFIED MACHINE LEARNING – SPECIALTY (MLS-C01)

MICROSOFT CERTIFIED: AZURE AI ENGINEER – ASSOCIATE EXAM AI-100

Working Language

ENGLISH

Job Description

JOB SUMMARY

The Applied AI Solutions Architect is a strategic role responsible for designing, implementing, and managing AI-driven solutions that align with business objectives. This position bridges technical expertise in artificial intelligence (AI) and machine learning (ML) with business strategy, ensuring scalable, ethical, and high-performing AI systems. The AI Solutions Architect collaborates with cross-functional teams to deliver innovative solutions, leveraging generative AI, cloud platforms, and modern architectures like Retrieval-Augmented Generation (RAG).

• Location: Hyderabad (preferred) but open to other locations
• Shift timing: 2 PM – 11 PM IST (no exceptions)

ESSENTIAL DUTIES

• Solution Design: Architect end-to-end AI/ML pipelines, including data ingestion, preprocessing, model training, deployment, and monitoring, ensuring scalability and performance.
• Technology Selection: Evaluate and select appropriate AI frameworks, tools, and cloud services (e.g., AWS SageMaker, Azure AI, Google Cloud AI) based on project requirements.
• Generative AI Implementation: Design solutions using large language models (LLMs) and RAG architecture for applications like content generation, customer engagement, or product design.
• Collaboration: Work with data scientists, engineers, product managers, and executives to translate business needs into technical solutions, acting as a trusted advisor.
• Governance and Ethics: Implement responsible AI practices, addressing bias, security, and compliance in AI systems.
• MLOps and AIOps: Establish CI/CD pipelines, model versioning, and monitoring frameworks to operationalize AI solutions.
• Thought Leadership: Advocate for AI-driven innovation, mentor teams, and communicate technical concepts to non-technical stakeholders.
• Performance Optimization: Ensure AI solutions meet latency, cost, and quality requirements, optimizing production environments.
• Monitor and tune workloads within the Microsoft Fabric platform to ensure cost-effective and efficient operations

TECHNICAL SKILLS

• AI Techniques: Expertise with the concepts of generative AI, prompt engineering, fine-tuning, and RAG.
• Azure Ecosystem: Expertise in Azure Machine Learning, Azure OpenAI Service (GPT, Codex, DALL·E), Azure AI Search (RAG pattern), Azure Cognitive Services, and Azure DevOps.
• AI Frameworks: Familiarity with Microsoft Semantic Kernel, Autogen C#, PyTorch, Scikit-learn, ONNX, and Hugging Face Transformers.
• Programming: Skilled in Python and C# for AI/ML development, with expertise in vector search using Azure Cosmos DB, prompt engineering, and content safety filters.
• Data Tools: Familiarity with SQL Server and Cosmos DB.

ADDITIONAL ASSETS

• DevOps: Knowledge of version control (Git) and CI/CD (Azure DevOps, Docker, Kubernetes via Azure Kubernetes Service).
• Data Engineering: Understanding of ETL processes and data lakes.
• Microsoft Purview: Understanding of Microsoft Purview for data governance.
• Compliance: Familiarity with compliance regulations (716, GDPR, GLBA, HIPAA).
• Knowledge of Microsoft Responsible AI principles.

SOFT SKILLS

• Strong communication skills with the ability to collaborate across technical and non-technical teams.
• Results driven; high integrity; ability to influence, negotiate and build relationships; superior communication skills; making complex decisions and leading teams through complex challenges.
• Self-…