Lead Site Reliability Engineer

ABOUT CLIENT

Our client is a global technology company that specializes in providing innovative IT solutions for the financial services industry

JOB DESCRIPTION

Lead a team of SREs, offering technical guidance and coaching while promoting a culture of reliability and continuous improvement.
Define and advance SRE practices such as SLIs/SLOs, error budgets, and incident response processes across production systems.
Take ownership of the design and evolution of automated cloud operations, driving the adoption of Infrastructure-as-Code (Terraform, CloudFormation) and CI/CD pipelines.
Oversee major incident responses, prioritize rapid resolution, conduct root cause analysis, and implement preventive measures.
Collaborate closely with Development, DevOps, and Cloud Engineering teams to incorporate reliability and resilience at every delivery stage.
Establish and track key reliability metrics (availability, latency, error rates) and drive initiatives for continuous improvement.
Assess and implement AWS-native and third-party tools to enhance monitoring, alerting, and automation.
Serve as the main contact for Service Reliability topics with clients, ensuring transparency and alignment on reliability goals.
Ensure compliance with industry standards and internal policies related to security, audit, and operational risk.

JOB REQUIREMENT

Minimum 7 years of experience working as an SRE Engineer, with exposure to data platform solutions being beneficial.
Extensive experience with cloud platform, including IAM, ECS, EKS, Lambda, and CloudWatch.
Proficiency in deploying and managing containerized services, particularly on Kubernetes.
Hands-on experience with Infrastructure-as-Code and automation tools like Terraform or Scalr.
Strong knowledge of cloud architecture, with an emphasis on maintaining service SLAs and ensuring high availability.
Experience with cloud security practices, SSO solutions, and authentication protocols (e.g., Auth0, SAML/OIDC, OAuth).
Familiarity with deploying and maintaining data processing frameworks and ML platforms such as Airflow, Airbyte, Superset, Metabase, Databricks, Snowflake, MLflow, etc., is advantageous.
Certifications such as AWS Certified DevOps Engineer - Professional or AWS Solutions Architect - Professional.
Experience in highly regulated industries.
Knowledge of advanced security practices and compliance frameworks (PCI-DSS, ISO 27001, SOC2).
Multi-region/multi-AZ architecture design for high availability and disaster recovery.

WHAT'S ON OFFER

We offer a professional and enjoyable working atmosphere.
We prioritize your long-term development.
We are dedicated to creating a future-ready digital bank platform.
Competitive salary
13th-month salary guarantee
Performance bonus
Access to professional English courses
Premium health insurance
Generous annual leave allowance

CONTACT

PEGASI – IT Recruitment Consultancy | Email: recruit@pegasi.com.vn | Tel: +84 28 3622 8666
We are PEGASI – IT Recruitment Consultancy in Vietnam. If you are looking for new opportunity for your career path, kindly visit our website www.pegasi.com.vn for your reference. Thank you!

Job Summary

Company Type:

Outsource

Technical Skills:

System, Devops

Location:

Ho Chi Minh, Ha Noi - Viet Nam

Working Policy:

Job ID:

J00771

Status:

Close

Related Job:

AI Engineer

Ho Chi Minh - Viet Nam


Product

  • AI
  • Python

#AI-Powered Insurance Solutions Develop and deploy machine learning models to support insurance recommendation, pricing, risk assessment, and claims automation Build and maintain AI-powered features integrated into our embedded insurance platform - from data pipelines to inference APIs Design and implement RAG (Retrieval-Augmented Generation) pipelines and LLMbased assistants for internal and customer-facing use cases Collaborate with product and engineering teams to translate business requirements into practical AI solutions Participate in the full ML/AI lifecycle: data collection, feature engineering, model training, evaluation, deployment, and monitoring Contribute to our internal AI agent framework - building, testing, and improving multiagent workflows using LangChain, LangGraph, or similar tools Ensure AI models and services meet performance, reliability, and compliance standards in a regulated (insurance) environment Participate in developing CI/CD workflows for AI/ML/Data pipelines. Contribute to Agent Development Toolkits (ADK) and the automated Software Development Life Cycle (SDLC) that accelerate AI-native feature delivery#R&D & Engineering Tasks Research and experiment with state-of-the-art AI/ML techniques and evaluate their applicability to insurance use cases Prototype new AI capabilities quickly, iterate based on feedback, and graduate successful experiments into production Document experiments, model architectures, and engineering decisions clearly for team knowledge sharing Stay current with the AI ecosystem (LLM advances, agent frameworks, tooling) and bring relevant insights back to the team Support Full Stack Engineers in using the AI Development Toolkit (ADK) to develop applications - guiding and enabling their use of the toolkit rather than building the applications yourself - and maintain a basic understanding of the SDLC to help ensure consistent engineering standards across the platform Contribute to and continuously enhance the system knowledge base, ensuring documentation, patterns, and learnings are accessible to the agents

Negotiation

View details

Backend Engineer

Ho Chi Minh - Viet Nam


Product

  • Typescript
  • NodeJS
  • Python
  • AI

Build the core gateway: a unified, OpenAI-compatible API in front of multiple providers (OpenAI, Anthropic, Google, plus self-hosted and OSS models). Own provider routing and reliability: load balancing, automatic failover, and cost and latency-aware routing. Build billing and metering that is correct, not approximate: per-request token accounting, usage ledgers, cost attribution per team, user, and key, budgets, and spend limits. Ship org controls: API key management, per-team and per-user quotas, rate limiting, and RBAC. Handle streaming and performance: low-overhead proxying, streaming responses, connection handling, and caching where it helps. Contribute to the Jan Agent and connect it to the router: route its model and tool calls through the gateway, and make agent traffic first-class in metering, controls, and observability. Make deliberate speed-versus-correctness calls: move fast where iteration is cheap, refuse to cut corners where a bug means a bad charge or a leaked key, and pay down debt on your own initiative.

Negotiation

View details

AI Transformation Lead

Ho Chi Minh - Viet Nam


Outsource

  • AI

Develop a 3-year AI transformation roadmap aligned with business goals in IT outsourcing, product development, and ODC services. Prioritize highest-impact AI use cases in the organization using a build-vs-buy-vs-partner framework. Establish AI governance for model selection, cost management, data privacy, IP protection, and ethical AI guidelines. Implement AI-assisted development workflows for 1,000+ engineers, including AI code generation, review, automated testing, and AI-powered debugging. Drive adoption of AI orchestration platforms to automate repetitive engineering tasks. Create internal AI skills/training programs and a culture of continuous AI experimentation. Measure and report on productivity gains, quality improvements, and time-to-market acceleration from AI adoption. Collaborate with product teams to define AI features for various products. Lead the development of AI Copilots, intelligent assistants, and autonomous agents embedded within products. Guide the architecture of an Ontology-Based AI ERP/MES Platform, including Knowledge Graphs, GraphRAG, and Multi-Agent Systems. Identify new AI-powered product opportunities in logistics, manufacturing, and supply chain to create new revenue streams. Advocate for AI internally, communicate the vision, celebrate wins, and address concerns across all levels. Partner with HR to define new AI-focused roles and refine hiring criteria. Collaborate with ODC/Client Delivery teams to package and sell AI capabilities to existing and new clients. Represent the company externally in conferences, thought leadership, and talent branding to position the company as an AI leader in the IT services industry.

Negotiation

View details