Solutions Architect (AI)

Techconnect.id; Jakarta Pusat; On-site; IDR 600,000,000 - 1,200,000,000; Full time

Job summary

Techconnect.id seeks a Solution Architect (AI) to design end-to-end AI/ML and generative AI architectures aligned with business needs. You will translate use cases into scalable technical designs, including LLM integration and RAG pipelines, while evaluating platforms and vendors for enterprise deployment.

You will define data pipelines and MLOps practices for training, deployment, monitoring, and retraining, ensuring governance and responsible AI across solutions, and collaborating with Data

Qualifications

• 8–12+ years in solution/enterprise architecture roles, including AI/ML focus.
• Hands-on experience with LLMs, RAG architectures, prompt engineering, and vector DBs.
• Proficiency with at least one major cloud AI platform (Azure, AWS, or GCP).
• Solid understanding of MLOps: versioning, CI/CD for ML, monitoring, retraining.
• Python proficiency; familiarity with TensorFlow, PyTorch, and HF.

Responsibilities

• Design end-to-end AI/ML and generative AI solution architectures aligned to business requirements.
• Translate business use cases into technical designs, including LLMs and RAG pipelines.
• Evaluate AI/ML platforms, frameworks, and vendors for enterprise needs.
• Define data pipelines and MLOps practices for training, deployment, monitoring, and retraining.
• Ensure governance, security, privacy, and responsible AI alignment across solutions.
• Collaborate with Data Engineering, Data Science, EA, and Product teams to embed AI.
• Build proofs-of-concept and prototypes to validate AI use cases before scale.
• Provide technical leadership and mentorship to engineering teams.
• Track AI/GenAI tech trends and advise leadership on roadmap priorities.
• Document architectures and key decisions for governance and knowledge continuity.

Skills

Architectural leadership

AI/ML expertise

Communication skills

Cloud platforms experience

MLOps

Data governance

Enterprise integration

Education

Bachelor's or Master's in CS/DS/Engineering

Tools

Azure AI/OpenAI Service

AWS Bedrock/SageMaker

GCP Vertex AI

Pinecone

Weaviate

pgvector

TensorFlow

PyTorch

Hugging Face

Job description

The Solution Architect (AI) designs and delivers end-to-end AI, machine learning, and generative AI solutions that integrate cleanly into the enterprise's existing technology landscape. This role translates business use cases into scalable, secure, and governable solution architectures — evaluating platforms and vendors, defining data and MLOps pipelines, and partnering closely with Data Engineering, Data Science, Enterprise Architecture, and Product teams to move AI initiatives from proof-of-concept to production.

• Design end-to-end AI/ML and generative AI solution architectures aligned to business requirements and enterprise architecture standards.
• Translate business use cases into technical solution designs, including LLM integration, RAG (Retrieval-Augmented Generation) pipelines, and ML model deployment.
• Evaluate and select AI/ML platforms, frameworks, and vendors (e.g., Azure AI/OpenAI Service, AWS Bedrock/SageMaker, GCP Vertex AI, open-source LLMs).
• Define data pipelines and MLOps practices for model training, deployment, monitoring, versioning, and retraining.
• Ensure AI solutions comply with data governance, security, and privacy requirements, and align with responsible AI principles.
• Collaborate with Data Engineering, Data Science, Enterprise Architecture, and Product teams to embed AI capabilities into existing systems.
• Build proofs-of-concept and prototypes to validate AI use cases before committing to full-scale implementation.
• Provide technical leadership and mentorship to engineering teams implementing AI solutions.
• Track emerging AI/GenAI technologies and advise leadership on adoption strategy and roadmap prioritization.
• Document solution architectures, integration patterns, and key technical decisions for governance and knowledge continuity.

• 8–12+ years in solution or enterprise architecture roles, including 3+ years focused specifically on AI/ML or generative AI solutions.
• Hands-on experience with LLMs, RAG architectures, prompt engineering, and vector databases (e.g., Pinecone, Weaviate, pgvector).
• Practical experience with at least one major cloud AI platform: Azure AI/OpenAI Service, AWS Bedrock/SageMaker, or GCP Vertex AI.
• Solid understanding of MLOps practices — model versioning, CI/CD for ML, monitoring, and automated retraining pipelines.
• Proficiency in Python and familiarity with core ML frameworks (TensorFlow, PyTorch, Hugging Face).
• Strong grounding in data architecture, APIs, microservices, and enterprise integration patterns.
• Working knowledge of responsible AI principles, data privacy regulations (e.g., GDPR), and AI governance frameworks.
• Excellent communication skills — able to translate complex AI concepts for both technical and non-technical stakeholders.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• Cloud AI certification (e.g., Azure AI Engineer Associate, AWS Certified Machine Learning – Specialty, Google Cloud Professional ML Engineer).
• Enterprise architecture certification (e.g., TOGAF), especially if the role will interface closely with the broader EA practice.
• Experience standing up an AI Center of Excellence or AI governance framework from scratch.