Senior AI Platform Engineer (AU, Retail, Hybrid)

Schedule: Monday to Friday (6AM to 3PM PHT)
Hybrid: 2-3x per week onsite

About the Role
As the Senior AI Platform Engineer, you turn agreed process opportunities into secure, reliable automations across client's business units. You work with business owners to understand the process before choosing deterministic workflow logic or bounded AI, then connect systems, interpret information and execute controlled actions. Document processing, classification, triage, approvals, reconciliation and exception handling are illustrative workloads.

Conversational entry points can help where useful, but building chatbots for large-scale web-facing products is not your primary purpose.
You independently deliver and operate complex, agreed components and workflows within established architecture, security and responsible AI guardrails. You improve local patterns, contribute reusable capability and mentor through reviews and pairing.

What will you do?

• Map processes, systems, data, rules, approval points and exceptions with business owners. Select deterministic steps or bounded AI according to the problem and risk.
• Agree baselines, acceptance criteria and handoffs with delivery partners, and measure adoption, cycle time, manual effort, quality and cost.
• Deliver agreed orchestration services, connectors and reusable components through APIs, events and controlled tool calls.
• Build stateful workflows with validated inputs, retries, idempotency and recovery from partial failure, with clear manual handoffs when confidence, permissions or availability are insufficient.
• Test model outputs and complete workflow/action behaviour, including unsafe inputs and approval enforcement.
• Apply least privilege, secure secrets, data minimisation and auditability; treat retrieved content as untrusted and preserve human validation for consequential actions.
• Release with code review, CI/CD, infrastructure-as-code and regression checks. Monitor failures, latency, consumption and cost; maintain support runbooks and resolve root causes.
• Improve local patterns and contribute tested implementation evidence to shared platform guidance. Review designs with Principal, Lead and architecture/security partners.
• Mentor through pairing, constructive code review and knowledge sharing, and document capabilities, limitations and operating procedures for safe adoption

What Success Looks Like

• Business users adopt your workflows in day-to-day operations, with measured improvements in cycle time, manual effort, quality or cost against agreed baselines.
• Automations recover predictably from interruptions and exceptions, prevent duplicate consequential actions and provide usable manual handoffs.
• Permission boundaries, audit trails and human approvals work in practice; evaluations demonstrate acceptable model behaviour and correct workflow actions.
• Business and engineering owners can see workflow health, failures, latency and model/infrastructure consumption, making support and cost trade-offs explicit.
• Tested connectors, local patterns, documentation and enablement reduce rework and support safe reuse across business units.

Who you are?

• Production software engineering and multi-system enterprise integration depth, including programming, APIs, events and data handling. Chat-only or prompt-demonstration experience is insufficient.
• Process discovery with business owners: mapping rules, controls and exceptions; agreeing acceptance criteria; enabling adoption; and measuring cycle time, manual effort, quality or cost.
• Practical AI-enabled orchestration with actionable tool/API calls, bounded permissions and human approvals, with sound judgement about deterministic automation versus probabilistic AI and safe manual handoff.
• Testing and evaluation of model behaviour and workflow/action correctness, including argument validation, approval enforcement, unsafe inputs, duplicate events and regression risk.
• Production delivery and operation using CI/CD, infrastructure-as-code, secure identity and secrets, observability and runbooks; resilient state, retries, idempotency, recovery and cost management.
• Clear collaboration with technical and non-technical partners, constructive reviews and mentoring, with the ability to explain limitations and trade-offs.
• Strong Azure AI experience is preferred. Relevant examples include Azure AI/Azure OpenAI, search and document processing, Functions/Logic Apps, identity and secrets, API/event integration, and Microsoft 365/Graph/Power Automate. Expertise in every named product is not required.

Join the awesome team and enjoy these benefits & perks:

• Hybrid Work Arrangement
• Medical, Dental Coverage and Life insurance from day 1 of employment
• Paid Vacation and Sick Leave (with Quarterly Sick Leave Conversion)
• Competitive salary package and annual appraisal
• Financial Assistance Program
• Mandatory Government Benefits and 13th Month Pay
• Complimentary Sleeping Quarters, Coffee at no cost
• Complimentary Office Fitness and Wellness Facilities at no cost
• Regular Company Events, Work Life Balance, and Career growth opportunities
• Accessible location at the heart of Metro Manila --- the Mega Tower, EDSA

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Equal Employment Statement
Employment decisions at ConnectOS will be conducted without consideration of factors such as age', race, color, religion, gender, disability status, sexual orientation, gender identity or expression, genetic information, and marital status. ConnectOS ensures the full confidentiality of the data it processes.