Lead APAC Data and AI enablement by acting as the business translator between regional priorities, enterprise technology strategy, and practical market execution.
Responsibilities
Champion the APAC Data and AI enablement agenda
Translate business priorities into scalable Data and AI solutions
Partner with enterprise platforms to scale reusable capabilities
Drive adoption, value realization, and stakeholder alignment
Build regional AI capability and responsible operating discipline
Requirements
Bachelor’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field
Master’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field
Software Development Engineer in Test contractor focused on Agentic AI systems and backend services.
Compensation
$58—$72 USD
Responsibilities
Develop and execute comprehensive QE strategies and test plans for Agentic AI systems, backend services, APIs, and service integrations.
Design and maintain scalable automated test frameworks across API, functional, integration, contract, regression, and end-to-end testing.
Develop testing approaches for non-deterministic AI behavior and establish meaningful evaluation criteria.
Identify quality risks early and apply risk-based, shift-left testing practices throughout the development lifecycle.
Integrate automated testing into CI/CD pipelines and establish effective quality gates.
Requirements
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience.
Nice to have: Experience testing Agentic AI workflows, including planning, multi-step execution, tool calling, memory, or state management.
Nice to have: Experience with AI evaluation techniques such as evaluation datasets, semantic evaluation, LLM-as-a-Judge, groundedness, relevance, or hallucination detection.
Nice to have: Experience with AI/LLM evaluation or observability tools such as LangSmith, DeepEval, Ragas, Arize Phoenix, Promptfoo, or similar technologies.
Design, build, and maintain an AI agent platform and related infrastructure, support DevOps operations, and enable engineering teams to adopt AI technologies.
Responsibilities
Design, build, and maintain our AI agent platform, including multi-agent orchestration, tool integrations, context management, and agent execution.
Develop robust evaluation and testing frameworks for AI agents, including automated evals, regression testing, and quality monitoring.
Build observability for AI systems, covering execution tracing, reliability, latency, performance, and cost optimization.
Implement security and governance for agentic systems, including access controls, human-in-the-loop approvals, audit logging, and safe execution.
Build and maintain the infrastructure required to deploy, scale, and operate AI applications in production.
As a Technical Solution Architect, become a part of a cross-functional development team engineering experiences of tomorrow, focusing on AI transformation and replacing manual decision-making workflows with reliable, auditable AI-assisted systems.
Lead the design and implementation of production-grade AI agent systems, including backend services, orchestration, retrieval, evaluation, observability, and deployment.
Own the technical design and implementation of AI agent systems
Build robust backend services, APIs, adapters, and connectors
Design agent workflows involving tool use, routing, state management, memory, retrieval, human-in-the-loop steps, and controlled multi-step execution
Develop retrieval and knowledge-grounding capabilities, including RAG pipelines, SQL-based agents, web search, reranking, citation, and context management
Define and implement evaluation strategies using representative datasets, golden tests, failure taxonomies, regression testing, human review, and production feedback
Requirements
Master’s degree in Computer Science, Software Engineering, or a related technical field
A hands-on technical contributor (Generative AI) responsible for building, deploying, and maintaining production-grade AI/ML and Generative AI solutions across client and internal initiatives.
Compensation
The pay range for this position is $107500.00 - $161300.00/yr.
Responsibilities
Design, implement, test, deploy, and maintain production-grade AI/ML and Generative AI solutions.
Build and integrate LLM-powered application capabilities including summarization, Q&A, document processing, semantic search, and workflow augmentation.
Develop retrieval-augmented generation (RAG) solutions using embeddings, chunking strategies, vector databases or search, semantic retrieval, and grounding techniques.
Integrate hosted AI services and foundation models into enterprise applications through secure APIs, microservices, and cloud-native services.
Develop and maintain backend services, APIs, pipelines, and automation using Python and related frameworks.
Executive Director, Data and AI EnablementNewReinsurance Group of America · Bangsar, Malaysia
AI Platform Engineershipzero · Hamburg, Germany
Senior Software Engineer - AI AgentsMULTIVERSE COMPUTING · Zaragoza, Spain
Senior AI Software DeveloperWorldQuant · London, United Kingdom
AI/ML Engineer IITEKsystems · Remote, US