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Senior AI Engineer

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Hybrid

Senior AI Engineer

BCS Information Technology Corp.

Senior AI Engineer

Skills

DynamoDBTypescriptPythonC#AWS LambdaGitMachine LearningAIAWSNo-code AutomationsMicrosoft Power PlatformComplianceJavascriptAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

₱1,800,000 – ₱2,520,000 / year

Location:

Taguig, Metro Manila, Philippines

Work mode:

Hybrid

Published on:

25 August 2026

What they need


About the role

The Senior AI Engineer will play a critical role in expanding client's AI Practice by designing, building, integrating and operationalising AI-enabled solutions that improve delivery speed, employee productivity, customer experience, operational efficiency and decision quality across the business. This role is highly hands-on and consultative. You will work across business units, technology teams, vendors and delivery squads to identify high-value AI opportunities, translate business problems into scalable technical solutions, and deliver secure, production-ready AI applications using the Microsoft and AWS technology stacks. The role will anchor on practical AI delivery across Microsoft Copilot, Copilot Studio, Power Platform, Azure AI services, AWS AI/ML and generative AI capabilities, data integration, workflow automation, model orchestration, APIs and enterprise application integration.

Key responsibilities

  • Design, build and deliver AI-powered applications, agents, copilots, automations, prototypes and production-ready solutions that improve business efficiency, customer experience and internal workflows.
  • Translate business problems into technical solution designs, delivery plans and measurable outcomes.
  • Build solutions using Microsoft and AWS AI capabilities, including Microsoft Copilot ecosystem, Copilot Studio, Power Platform, Azure AI services, AWS AI/ML services, generative AI APIs and enterprise integration patterns.
  • Develop AI-enabled workflows that integrate with business systems, documents, data sources, APIs, enterprise applications and collaboration platforms.
  • Design and implement prompt engineering, retrieval augmented generation patterns, agent workflows, model evaluation approaches and reusable AI components.
  • Prepare, structure and integrate data required for AI use cases, while ensuring appropriate handling of sensitive, confidential and business-critical information.
  • Support solution testing, validation, monitoring, troubleshooting, optimisation and continuous improvement.
  • Establish reusable engineering patterns, reference architectures and delivery accelerators across Microsoft and AWS AI platforms.
  • Champion secure, scalable and maintainable AI engineering practices across development, testing, deployment, monitoring and support.
  • Collaborate with security, risk, architecture and infrastructure teams to ensure AI solutions meet enterprise standards, privacy obligations and governance requirements.

Qualifications:

  • Significant experience designing, building, deploying and supporting software, automation, data or AI-enabled solutions in enterprise environments.
  • Working experience with AWS services and cloud-native design patterns, ideally including AWS AI/ML or generative AI services such as AWS Bedrock, SageMaker, Lambda, API Gateway, S3, CloudWatch, DynamoDB, RDS, ECS/EKS, Step Functions or related AWS services.
  • Experience working with Microsoft AI and automation technologies such as Microsoft Copilot ecosystem, Copilot Studio, Power Platform, Azure AI services, Azure Functions, Logic Apps, Microsoft Graph, Azure OpenAI, Azure AI Search, Azure AI Foundry or related Microsoft AI services.
  • Strong hands-on experience with modern programming languages, preferably C#, Python, JavaScript/TypeScript or equivalent.
  • Experience designing retrieval augmented generation, vector search, document intelligence, semantic search, knowledge assistants or enterprise agent patterns.
  • Experience with model evaluation, LLM testing, prompt evaluation, guardrails, token/cost optimisation and monitoring of generative AI solutions.
  • Demonstrated experience building AI-enabled applications, workflow automations, data-driven solutions, copilots, agents or integrations.
  • Experience with DevOps practices, Git-based source control, CI/CD pipelines, infrastructure automation, testing and release management.
  • Understanding of security, privacy, compliance, identity and access considerations when delivering AI-enabled solutions.
  • Demonstrated ability to communicate complex technical ideas clearly to business and technical stakeholders.

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