Senior AI Engineer
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Before you apply
LocationHyderabad; Pune, Maharashtra
Typefull-time
SenioritySenior
Experience4–6 yrs
Company size1,001–5,000 people
PostedAug 25, 2026 · 2mo ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
Strong hands-on proficiency in Python and/or .NET (C#, ASP.NET Core), Java, or Node.js
Practical experience with GenAI APIs (OpenAI, Azure OpenAI), LangChain, LlamaIndex, RAG patterns, or agentic workflow frameworks
Hands-on experience with AWS, Azure, or GCP—microservices, Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Azure DevOps)
Exposure to workflow orchestration engines, RPA tools, or custom automation scripts
4–6 years of hands-on software engineering experience, with 2+ years as Senior AI engineer
Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related technical field
Clear technical communication—able to explain code implementation to teammates and project managers
Collaborative team player accustomed to working across global/offshore time zones
Curious and self-motivated — proactively explores new AI tools, frameworks, and engineering patterns
Familiarity with enterprise systems (Oracle, SAP, Salesforce, or ServiceNow)
Cloud Certification (AWS, Azure, or GCP) at associate/developer level
Experience working in client-facing delivery environments within IT services or consulting organizations
Skills
Python
.NET
C#
ASP.NET Core
Java
Node.js
OpenAI
Azure OpenAI
LangChain
LlamaIndex
AWS
Azure
GCP
Docker
Kubernetes
GitHub Actions
Azure DevOps
Oracle
SAP
Salesforce
ServiceNow
Senior AI Engineer2
Requirements
Technical Skills
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Engineering Stack: Strong hands-on proficiency in Python and/or .NET (C#, ASP.NET Core), Java, or Node.js.
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AI & GenAI: Practical experience with GenAI APIs (OpenAI, Azure OpenAI), LangChain, LlamaIndex, RAG patterns, or agentic workflow frameworks.
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Cloud & DevOps: Hands-on experience with AWS, Azure, or GCP—microservices, Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Azure DevOps).
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Automation: Exposure to workflow orchestration engines, RPA tools, or custom automation scripts.
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Enterprise Platforms: Familiarity with enterprise systems (Oracle, SAP, Salesforce, or ServiceNow) is a plus.
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Certifications: Cloud Certification (AWS, Azure, or GCP) at associate/developer level is a plus.
Soft Skills
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Clear technical communication—able to explain code implementation to teammates and project managers.
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Collaborative team player accustomed to working across global/offshore time zones.
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Curious and self-motivated — proactively explores new AI tools, frameworks, and engineering patterns.
Experience
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Experience: 4–6 years of hands-on software engineering experience, with 2+ years as, Senior AI engineer
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Hands-on experience building and delivering enterprise-grade solutions across cloud, AI/ML, and application engineering.
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Experience working in client-facing delivery environments within IT services or consulting organizations is preferred.
Key Responsibilities
1. Hands-on Engineering & Delivery
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Write production-grade code to build component-level features and API integrations based on technical designs and blueprints.
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Actively contribute to daily engineering deliverables—developing backend microservices, driving unit testing, refactoring code, and resolving technical debt.
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Conduct peer code reviews to ensure code quality, performance, maintainability, and adherence to team engineering standards.
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Troubleshoot and resolve complex bugs, API integration issues, and performance bottlenecks within application microservices.
AI & Engineering Framework Adoption
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Learn, implement, and integrate for AI-native feature— including GenAI integration patterns, agentic workflows, and intelligent automation
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Contribute to the development and maintenance of AI engineering frameworks, solution accelerators, and reusable technical assets.
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Evaluate and experiment with new tools, APIs, and platforms in the AI and cloud-native space.
Technical Consulting & Problem Solving
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Engage with client technical teams to understand system landscapes, integration requirements, and technical constraints.
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Propose pragmatic, technology-forward solutions to complex engineering challenges across application modernization, AI integration, and cloud migration.
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Support the Solution and Principal Architect in pre-sales activities including technical assessments, proof-of-concept design, and effort estimation.
Cloud & Automation Execution
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Develop and deploy cloud-native services on AWS, Azure, or GCP using containers (Docker, Kubernetes), serverless functions, and event-driven patterns.
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Implement intelligent automation components using workflow orchestration engines, RPA integrations, or custom AI-driven pipelines.
Engineering Community & Mentoring
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Mentor junior engineers—supporting technical upskilling on AI tools, cloud platforms, and modern engineering practices.
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Contribute to Jade’s internal community of practice through knowledge sharing, documentation, and participation in architecture discussions.
Education
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Bachelor’s degree in Computer Science, Computer Engineering, Information Technology, or a related technical field is required**.**