GenAI Lead - 12 Months Contract

PERSOL TECH SERVICES PTE. LTD.; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

PERSOL TECH SERVICES PTE. LTD. seeks a senior enterprise AI architect to design and deliver scalable AI solutions across applications, data platforms and security.

You will lead end-to-end AI workflows, model deployments and governance for enterprise environments in Singapore. The role requires hands-on experience with LLMs, RAG, AI agents and vector databases, plus strong collaboration with data scientists, engineers and business stakeholders to drive AI initiatives with governance and cost

Qualifications

• 12+ years of enterprise solution architecture experience.
• Strong expertise in AI, ML, DL and Generative AI technologies.
• Hands-on experience with LLMs, RAG, AI Agents and multi-agent architectures.
• Experience with AI frameworks (LangChain, LangGraph, DSPy, OpenAI, Anthropic, Databricks).
• Strong LLMOps knowledge including evaluation, prompt engineering, observability and CI/CD.

Responsibilities

• Design and implement enterprise AI solutions translating business requirements into scalable architectures.
• Lead AI/ML pipelines, model deployment strategies and LLMOps across development and production.
• Architect data platforms for structured, unstructured and vectorised data for AI workloads.
• Develop vector search and data pipelines using Kafka, Kinesis or Pub/Sub.
• Collaborate with data scientists, engineers and stakeholders to deliver enterprise AI initiatives.

Skills

AI architectures

LLMs

LLMOps

Data platforms

Kubernetes

Docker

Cloud security

Stakeholder management

Education

Bachelor's degree in CS/AI/DS/SE/IT

Tools

LangChain

LangGraph

DSPy

OpenAI APIs

Anthropic Claude

Databricks AI

Delta Lake

Apache Kafka

Kinesis

Google Pub/Sub

Pinecone

Milvus

pgvector

Job description

Duration: 1 year

Working Hours: 8.30am - 6pm, Monday - Fridays.

Location: Central

Key Responsibilities

• Design and implement enterprise-grade Generative AI and Agentic AI solutions, translating business requirements into scalable AI architectures.
• Develop and deploy production-ready AI applications using Retrieval-Augmented Generation (RAG), AI agents and Large Language Models (LLMs).
• Design end-to-end AI solution architecture spanning applications, data platforms, integrations, security and observability.
• Lead the design and implementation of AI/ML pipelines, model deployment strategies and LLMOps practices across development and production environments.
• Build and optimise AI solutions using frameworks such as LangChain, LangGraph, DSPy and enterprise AI platforms.
• Architect scalable data platforms supporting structured, unstructured and vectorised data for AI workloads.
• Design and implement vector search solutions using technologies such as Pinecone, Milvus or pgvector.
• Develop batch and streaming data pipelines using modern data engineering technologies including Kafka, Kinesis or Pub/Sub.
• Establish LLMOps capabilities including model evaluation, prompt management, observability, model monitoring, tracing and CI/CD automation.
• Evaluate and recommend AI models, foundation models and cloud AI services based on performance, scalability, governance and cost optimisation.
• Implement Responsible AI practices including AI guardrails, model governance, explainability, privacy and security controls.
• Design secure AI platforms incorporating Zero Trust principles, Identity and Access Management (IAM), OAuth2/OIDC, Key Management Services (KMS) and compliance requirements.
• Lead technical design reviews, proof-of-concepts (POCs), MVP delivery and production deployment of AI solutions.
• Collaborate with cross-functional teams including data scientists, data engineers, software engineers and business stakeholders to deliver enterprise AI initiatives.
• Provide technical leadership, mentor engineering teams and establish reusable AI architecture patterns, frameworks and best practices.
• Communicate technical solutions, business value, implementation risks and delivery roadmaps to senior stakeholders and clients.

Requirements

• Bachelor's degree in computer science, Artificial Intelligence, Data Science, Software Engineering, Information Technology or a related discipline.
• Minimum 12 years of professional experience in enterprise solution architecture, software engineering, data platform architecture or AI solution delivery.
• Must have one or more of the following certifications: AWS / Azure / Google AI Certifications, AWS / Azure / Google Data Science Certifications, AWS / Azure / Google Solution Architect Certifications, TOGAF 9 Certification (The Open Group), Equivalent industry-recognized architect certifications
• Strong expertise in Artificial Intelligence, Machine Learning, Deep Learning and Generative AI technologies.
• Hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents and multi-agent architectures.
• Experience with AI frameworks including LangChain, LangGraph, DSPy, OpenAI APIs, Anthropic Claude and Databricks AI.
• Strong LLMOps knowledge including model evaluation, prompt engineering, prompt versioning, observability, MLflow, OpenTelemetry and AI CI/CD pipelines.
• Strong data engineering expertise including Delta Lake, Apache Iceberg, Apache Hudi, Kafka, Kinesis and Google Pub/Sub.
• Experience with vector databases including Pinecone, Milvus, pgvector or equivalent.
• Experience designing RESTful APIs, GraphQL, gRPC and event-driven architectures.
• Strong understanding of Kubernetes, Docker, Serverless Computing, Infrastructure as Code (Terraform, CloudFormation) and cloud-native architectures.
• Strong knowledge of AI security, Responsible AI, Zero Trust architecture, OAuth2, OIDC, JWT, mTLS, IAM and data governance.
• Strong communication, stakeholder management and client engagement skills.