- Experience
- 7+ yrs
- Salary
- —
- Openings
- 1
- Posted
- 4 hours ago
- Work mode
- In office
- Resume
- Required to apply
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Job description
About Helius Technologies
Helius Technologies partners with enterprises across Asia and the Middle East, enabling technology transformations that emphasize reliability, governance, and accountable execution. Our focus is to reliably deliver technology outcomes that stand the test of time, particularly in heavily regulated and enterprise settings.
Role Overview
We seek an AI Engineering Lead to oversee the entire engineering lifecycle of AI platforms. You will collaborate with engineering teams, stakeholders, and delivery leads to drive the execution of technological projects. This leadership role demands a blend of strong technical expertise and a disciplined, accountable delivery approach.
As the technical authority for AI Platform Engineering, the incumbent will design, build, test, deploy, govern, and maintain AI solutions entirely on AWS. These solutions include Generative AI, Agentic AI, Retrieval-Augmented Generation, document intelligence, LLM integration, workflow orchestration, MLOps/LLMOps, and reusable AI engineering standards. Working closely with Enterprise and Cloud Architects, Cloud Platform Engineers, Data Science and Analytics teams, AI Governance, and delivery teams, the lead will ensure solutions are secure, scalable, reusable, cost-aware, and compliant with enterprise standards.
This leadership position requires hands-on guidance of solution designs, code reviews, team leadership, vendor oversight, and embedding production-grade engineering discipline within the AI function.
Essential Qualifications
- Over 7 years of experience in software or AI engineering, with at least 3 years as a senior lead or architect.
- Proven track record delivering AI/ML/Generative AI solutions in production settings.
- Strong expertise in AWS AI and cloud-native services such as Bedrock, SageMaker, Textract, Comprehend, OpenSearch, Lambda, API Gateway, Step Functions, and S3.
- In-depth knowledge of Generative AI engineering including LLM integration, prompt engineering, Retrieval-Augmented Generation architecture, embeddings, vector stores, evaluation frameworks, and hallucination control techniques.
- Experience designing secure, scalable, observable, and maintainable production-grade systems.
- Ability to oversee and provide technical governance on vendor-delivered AI solutions including design review, approach validation, and handover management.
- Proficient in production-level Python development including CI/CD, testing, observability, and code reviews.
- Demonstrated leadership through line management or technical mentorship of engineering teams.
- Experience working in regulated industries, especially in financial services or insurance sectors.
Preferred Skills
- Professional AWS certifications such as Solutions Architect Professional or Machine Learning Specialty.
- Experience with Agentic AI, Bedrock Agents, AgentCore, or related agent orchestration frameworks.
- Familiarity with LLMOps, MLOps, AI observability, model evaluation, registry, and production monitoring.
- Knowledge of AI risk management, model governance, responsible AI principles, and regulated data environments.
- Experience with vector databases or semantic search systems like OpenSearch, pgvector, Pinecone, or Weaviate.
- Capability working across traditional ML production processes and modern Generative AI deployments.
Additional Information
To apply, please prepare your updated resume including the following details: full name as per identification, current and expected salary in SGD, notice period or availability, reason for job change, and residential status in Singapore.
Why Join Us
Helius Technologies offers the opportunity to participate in complex projects with top enterprises across Asia and the Middle East. You will collaborate with a diverse team of over a thousand technology professionals across seven countries, supporting clients in BFSI, healthcare, and both public and private sectors. Our culture prioritizes reliability, accountability, and disciplined execution, harmonizing strong engineering practices with structured delivery for impactful results.