oracle
AI Engineer - TI
WSP
Bengaluru, IND
Entry · 0–3 years experience
Onsite
Discovered 3 days ago
azureazure-functionsgitkubernetesopenaipython
Key Skills for This Role
azureazure-functionsgitkubernetesopenaipython
Full Job Posting
Qualifications
- Bachelor’s degree in Computer Science, Engineering, Data Science or a related discipline. • 0–3 years of relevant software, data or AI engineering experience, including internships or strong project experience. • Working knowledge of Python, REST APIs, SQL and software engineering fundamentals. • Practical understanding of LLMs, embeddings, RAG, prompt engineering and evaluation methods. • Exposure to Azure AI services, Git-based development, CI/CD and cloud security principles. • Strong analytical, troubleshooting, documentation and stakeholder communication skills.
- WSP-Aligned Technology Stack The role will use and support the approved enterprise stack below. Equivalent technologies may be considered only where formally approved through WSP architecture, security and governance processes.
- Cloud platform Microsoft Azure AI services Azure OpenAI, Azure AI Search, Azure AI Document Intelligence, Azure Machine Learning and approved Azure AI services Application hosting Azure App Service, Azure Functions and Azure Kubernetes Service where architecturally approved Data and security Azure Storage, Azure Key Vault, SQL and approved NoSQL services Engineering lifecycle Azure DevOps, Git, CI/CD, automated testing, Azure Monitor and approved observability services Architecture REST APIs, microservices, event-driven and serverless patterns, secure API-first integration
- Deliver maintainable AI components that progress from prototype through controlled production deployment. • Improve solution quality through structured evaluation, monitoring and iterative optimisation. • Contribute to reusable AI capabilities and patterns across the Middle East portfolio. Preferred Qualifications • Microsoft Azure or Azure AI certification. • Experience with agentic AI orchestration, document intelligence or enterprise search. • Knowledge of MLOps, model lifecycle management and production monitoring. • Experience working in multi-disciplinary, agile or globally distributed teams.
- Ways of Working • Collaborate effectively with Middle East stakeholders, GCC delivery teams, product owners, engineering specialists and enterprise technology functions. • Work within WSP standards for architecture, cybersecurity, data protection, responsible AI, quality assurance and delivery governance. • Communicate clearly, document decisions and support transparent delivery reporting across distributed teams.
- Bachelor’s degree in Computer Science, Engineering, Data Science or a related discipline.
- 0–3 years of relevant software, data or AI engineering experience, including internships or strong project experience.
- Working knowledge of Python, REST APIs, SQL and software engineering fundamentals.
- Practical understanding of LLMs, embeddings, RAG, prompt engineering and evaluation methods.
- Exposure to Azure AI services, Git-based development, CI/CD and cloud security principles.
- Strong analytical, troubleshooting, documentation and stakeholder communication skills.
- WSP-Aligned Technology Stack
- The role will use and support the approved enterprise stack below. Equivalent technologies may be considered only where formally approved through WSP architecture, security and governance processes.
- Deliver maintainable AI components that progress from prototype through controlled production deployment.
- Improve solution quality through structured evaluation, monitoring and iterative optimisation.
- Contribute to reusable AI capabilities and patterns across the Middle East portfolio.
Responsibilities
- Develop GenAI applications, agents and automation workflows using approved designs and engineering standards.
- Implement retrieval-augmented generation, function calling, structured outputs and prompt patterns to improve solution reliability and usability.
- Integrate AI components with enterprise systems, APIs, approved vector search services and governed data sources.
- Build and maintain ingestion, chunking, embedding, indexing and retrieval pipelines for structured and unstructured content.
- Create evaluation datasets and execute repeatable testing for accuracy, grounding, safety, latency and solution quality.
- Apply responsible AI controls including validation, guardrails, content filtering, traceability and human oversight.
- Develop clean, reusable and well-documented Python components and participate in code reviews.
- Support deployment, monitoring, incident resolution and continuous optimisation of AI solutions.
Preferred Qualifications
- Microsoft Azure or Azure AI certification.
- Experience with agentic AI orchestration, document intelligence or enterprise search.
- Knowledge of MLOps, model lifecycle management and production monitoring.
- Experience working in multi-disciplinary, agile or globally distributed teams.
- Ways of Working
- Collaborate effectively with Middle East stakeholders, GCC delivery teams, product owners, engineering specialists and enterprise technology functions.
- Work within WSP standards for architecture, cybersecurity, data protection, responsible AI, quality assurance and delivery governance.
- Communicate clearly, document decisions and support transparent delivery reporting across distributed teams.
About WSP
Professional Services10,001+Founded 1959
WSP is a global professional services firm headquartered in Montréal, providing engineering, advisory, and science-based expertise. It serves clients across transportation and infrastructure, property and buildings, earth and environment, energy, water, and other sectors.
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