AI Engineer

SleekFlow; Kuala Lumpur; Remote; MYR 120.000 - 180.000; Vollzeit

Benefits dieser Stelle

13th-month salary

Stock options

Flexible work-from-home policy

Work From Anywhere scheme

Transport allowance

Education allowance

Birthday leave

Comprehensive medical insurance

Zusammenfassung

SleekFlow, a cutting-edge AI-driven SaaS company, seeks a mid-level LLM/RAG/Multi-Agent Infrastructure Engineer in Malaysia. You will design, build, and optimize infrastructure to integrate Large Language Models via APIs, create efficient RAG systems, and support multi-agent frameworks.

Fluency in English is required and 1–2 years of relevant experience is expected. You will work across AI applications, knowledge retrieval, and automation to deliver scalable, high-performance solutions that

Qualifikationen

• Experience integrating LLM APIs and building RAG pipelines with vector search tools.
• Knowledge of multi-agent systems and their infrastructure needs.
• Experience in knowledge base design, indexing, and retrieval.
• CI/CD & MLOps experience, deployment pipelines, and monitoring.
• Prompt engineering with advanced techniques for accuracy.

Aufgaben

• LLM Evaluation: assess various LLMs to fit applications.
• RAG Pipeline Engineering: scale architectures with vector stores.
• Multi-Agent Coordination: enable distributed communications.
• Knowledge Base Development: structure and index data.
• Databases & Storage: use Redis, PostgreSQL, ElasticSearch for retrieval.
• Observability & Monitoring: logging and tracing for API health.
• Security & Compliance: data privacy and governance in AI deployments.
• Collaboration: work with researchers and engineers to deploy models.

Tools

FAISS

Weaviate

Pinecone

LangChain

AutoGen

CrewAI

Redis

PostgreSQL

ElasticSearch

Kafka

Ray

Jobbeschreibung

About SleekFlow

SleekFlow is an AI Suite for Revenue-Driving Conversations. We are trusted by over 2,000 enterprises globally. But we are more than just a SaaS company; we are an AI-native movement redefining the B2C relationship across 70+ countries.

At our core is AgentFlow—an AI GTM workforce that learns, improves, and acts as a self-healing knowledge base for businesses. From first-click conversion to long-term retention, we turn every conversation into a data-backed growth opportunity. Headquartered in Singapore with a global presence in Hong Kong, the UAE, and the US, we are looking for exceptional people to help us build an AI operating system that matters.

Join us and rewrite how the world engages at scale.

Learn more from our blogs for developers: https://sleekflow.io/blog/category/developer-blog

Mid-Level

Location: Malaysia

Minimum Experience: 1~2 years of experience working with RAG/LLM development and deployment

Language: Fluency in English is required

Role

We are seeking a highly skilled LLM/RAG/Multi-Agent Infrastructure Engineer to design, develop, and optimize infrastructure for integrating Large Language Models (LLMs) via APIs, building efficient Retrieval-Augmented Generation (RAG) systems, and enabling multi-agent frameworks. You will work at the intersection of AI applications, knowledge retrieval, and automation to create high-performance, scalable solutions that power next-generation AI-driven applications.

Key Responsibilities

• LLM Evaluation: Assess the strengths and limitations of various LLMs (e.g., OpenAI, Anthropic, Cohere) to determine the best fit for specific applications and use cases.
• RAG Pipeline Engineering: Develop and scale RAG architectures, integrating vector databases, retrieval mechanisms, and embedding models for efficient knowledge retrieval.
• Multi-Agent Coordination: Design robust infrastructure to support multi-agent interactions, enabling efficient message passing, distributed decision-making, and autonomous collaboration.
• Knowledge Base Development: Design and implement structured knowledge bases that enhance LLM output quality by integrating domain-specific data, ontologies, and automated document indexing.
• Databases & Storage: Use vector databases, NoSQL databases, and caching mechanisms (e.g., Redis, PostgreSQL, ElasticSearch) to support efficient knowledge retrieval and AI workloads.
• Observability & Monitoring: Establish logging, monitoring, and tracing systems for API performance, system health, and anomaly detection.
• Security & Compliance: Ensure best practices for data privacy, security, and compliance in AI deployments.
• Collaboration: Work closely with AI researchers, ML engineers, and software developers to integrate AI models into production environments effectively.

Required Qualifications

• Experience with LLM APIs & RAG: Hands-on experience in integrating LLM APIs (e.g., OpenAI, Anthropic, Cohere) and building RAG pipelines with vector search (e.g., FAISS, Weaviate, Pinecone).
• Multi-Agent Frameworks: Familiarity with multi-agent systems (e.g., LangChain, AutoGen, CrewAI) and their infrastructure requirements.
• Knowledge Base Engineering: Experience in designing, indexing, and maintaining structured and unstructured knowledge bases, including knowledge graph construction, ontology design, and text embedding techniques.
• CI/CD & MLOps: Experience with ML model versioning, deployment pipelines, and monitoring tools.
• Prompt Engineering Expertise: Proficiency in designing clear, structured prompts, optimizing AI responses through iterative refinement, and leveraging advanced techniques like few-shot learning and chain-of-thought reasoning for improved accuracy and coherence.

Preferred Qualifications

• Prior experience in AI infrastructure for high-traffic SaaS or enterprise AI applications.
• Knowledge of reinforcement learning and agent-based AI systems.
• Experience with real-time streaming architectures (Kafka, Ray, or similar).
• Experience in leveraging structured and semi-structured data for improving LLM-generated outputs.

Our Culture Code

• Open-mindedness – We welcome different viewpoints and give and take feedback openly, always ready to challenge our own assumptions.
• Collaboration – We have each other's back, share knowledge freely, and treat every teammate with equal respect.
• Growth – We pursue continuous improvement, embrace new challenges, and treat mistakes as chances to learn.
• Ownership – We take initiative, see things through, and hold ourselves accountable for the outcome.
• Grit & Adaptability – We stay resilient through setbacks and adapt to change with patience and persistence.

What We Offer:

• Attractive compensation package, including a 13th-month salary.
• Stock options in a rapidly growing startup.
• A fun, diverse, and international team culture.
• Comprehensive group medical insurance.
• Transport allowance.
• Examination & education allowance.
• Paid birthday leave.
• Flexible work-from-home policy.
• “Work From Anywhere” scheme.
• Rewarding continuous learning from experienced team leads.
• Many more exciting perks and growth opportunities!

Confidence can sometimes hold us back from applying for a job. But we'll let you in on a secret: there's no such thing as a 'perfect' candidate.