Tóm lược
Mô tả công việc
Tóm tắt công việc
Role Overview
We are scaling agentic AI across the enterprise using a multi-platform agent stack comprising Microsoft Copilot Studio, Google AgentSpace, AWS Bedrock, and Dataiku.
This role designs, builds, and operates production-grade AI agents that can:
- reason and plan,
- retrieve enterprise knowledge,
- take actions via tools and APIs,
- operate safely under governance and audit constraints.
Agents are expected to go beyond chat and support real business workflows across IT, operations, and other functions.
The role is platform-aware but not platform-locked. Candidates may come from any ecosystem, but must demonstrate the ability to deliver agentic systems on at least one of the supported platforms and adapt across the rest.
What you will build
Examples of solutions you will deliver include:
- Enterprise Support and Ops Agents
• Leverage AI and machine learning to learn from past tickets, emails and logs to triage requests and monitor systems
• Propose or execute actions with escalation and full audit trails
• Perform automated root cause analysis for complex enterprise environment
- Knowledge and Policy Agents
• Grounded Q&A over SOPs, manuals, and policies
• Citations, traceability, and access-controlled retrieval
• Security attestation agent to reduce administrative work and to guide users for policy compliance
• System onboarding agent to guide users and help in troubleshooting, price and cost estimation
- Workflow and Action Agents
• Multi-step orchestration (e.g. read request → analyze → fetch data → draft response → trigger approval → update system)
Responsibilities
1. Agentic Solution Design
- Design goal-driven agents that decompose tasks, select tools, manage state, and recover from failures.
- Implement agent patterns such as planner–executor, coordinator–worker, reflection/self-check, and human‑in‑the‑loop decision gates.
2. Platform Implementation
You will work across one or more of the following platforms:
- Microsoft Copilot Studio
• Build copilots with plugins, connectors, and enterprise guardrails
- Google AgentSpace
• Build agents integrated with other applications or tools (e.g. ITSM, SIEM, Workflow management system)
• Orchestrate multi-step workflows and API-driven actions
- AWS Bedrock
• Design secure agentic workflows using Bedrock models and tools
- Dataiku
• Operationalize agents within analytics, ML pipelines, and business workflows
- An operational Hybrid Machine Learning and LLM model to support smart Digital Platform and Security Operations
- ML models detect anomalies → LLM explains them
- ML predicts incidents → LLM drafts remediation and healing steps
- ML scores risk → LLM supports human decision‑making
3. Retrieval and Grounding (RAG)
- Design enterprise RAG pipelines including ingestion, chunking, embeddings, retrieval, reranking, and citation.
- Ensure retrieval respects role-based access control and data classification.
4. Evaluation, Observability, and Operations
- Build evaluation frameworks for non-deterministic systems: task success metrics, grounding checks, hallucination detection, and regression tests.
- Implement observability for prompts, retrieval, and tool calls.
- Own solutions from POC through MVP and production.
5. Security, Governance, and Responsible AI
- Enforce least-privilege tool access, audit logging, secrets management, prompt-injection defenses, and safe action boundaries.
- Design human approval checkpoints for high-risk or irreversible actions.
- Comply with enterprise AI governance and ethics requirements.
- 14 days Annual leaves + 3 Sick leaves
- Private Health Insurance
- Annual Salary Review
- Performance Bonus
- 100% salary in probation period
- Free LinkedIn Learning Account
- Company Events & Team Building
Yêu cầu công việc
Requirements
- 3-5+ years professional software engineering experience.
- Hands-on experience building GenAI or LLM systems beyond basic chatbots i.e. a hybrid Machine Learning and LLM model in an operational platform
- Strong understanding of agentic concepts: tool/function calling, state and memory, planning and execution loops.
- Practical experience with at least one of: Microsoft Copilot Studio, Google AgentSpace, AWS Bedrock, or Dataiku.
- Experience with vector databases and embeddings.
Prefered skills and experiences:
- Familiarity and experience with UiPath is an added advantage
- Familiarity and experience with project management concepts and methodologies is preferred
Ngôn ngữ
-
English
Nói: Intermediate - Đọc: Intermediate - Viết: Intermediate
Yêu cầu kỹ thuật
- Machine Learning
- Python
- LLM
- AI (Artificial Intelligence)
- AWS
- UiPath
- Vector
- GenAI
- Amazon Bedrock
- Copilot
NĂNG LỰC
- Planning Skills
- Project Management
Thông tin doanh nghiệp
ST Engineering is a leading global technology, defense, and engineering conglomerate.
Headquartered in Singapore, established in 1997, the company has grown into a powerhouse, offering innovative solutions across aerospace, defense, urban solutions, and satellite communications. With a strong presence in over 50 cities worldwide, ST Engineering delivers cutting-edge technologies to industries such as aerospace, defense, and smart cities. The company is committed to creating sustainable solutions that address both current and future challenges. Backed by a dedicated workforce, ST Engineering continues to lead in providing mission-critical systems and services to customers around the world.