Expert, AI Engineering (40001865)

Trách nhiệm chính

• Lead design and delivery of advanced AI solutions, ensuring high performance, scalability, and cost efficiency in production environments.
• Solve complex AI challenges (modeling, evaluation, multi-agent systems) and develop reusable frameworks and standards adopted across teams.
• Ensure AI systems are developed and operated responsibly, addressing safety, ethical risks, and governance requirements.
• Evaluate novel algorithms and training techniques against production constraints; diagnose and unblock hard cross-cutting modeling problems.
• Implement complex multi-agent orchestration, long-running stateful workflows, and quality optimization at scale; build reusable agent patterns and prompt libraries.
• Evaluate and adopt advanced optimization techniques; design multi-tenant serving and capacity strategies; build performance-regression frameworks and cost dashboards.
• Build evaluation tooling and automated experiment pipelines; design and run online A/B tests with statistical rigor; calibrate human and LLM-judge evaluation.
• Resolve hardest evaluation problems (subjective tasks, rare-event detection, long-tail safety).
• Design testing strategies for AI systems; build internal libraries, SDKs, and code templates.
• Architect data platforms for ML training and LLM/RAG workloads; design for cost, latency, freshness trade-offs; build data-quality, lineage, and observability tooling.
• Architect complex AI systems combining ML and agentic components; design for graceful degradation, cost-efficiency, evolvability, and multi-tenancy; lead migration and convergence of inherited or siloed systems.
• Conduct in-depth evaluation of emerging AI technologies; build prototypes; provide recommendations.
• Contribute to responsible AI standards; ensure compliance with guidelines and regulations.
• Analyze ethical and safety risks; propose mitigation measures.
• Participate in testing activities (adversarial testing, risk assessments) to improve robustness.
• Support AI risk assessments in product reviews; act as technical advisor.

Yêu cầu công việc

• Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or related quantitative field.
• Strong foundation in mathematics, statistics, and machine learning principles.
• Relevant certifications in AI/ML, Cloud (Azure, AWS, GCP), or Data Engineering are a plus.
• English proficiency in line with Techcombank’s policy.
• 8+ years of experience in AI/ML, data engineering, and software development, with proven delivery of end-to-end AI solutions in production environments.
• Strong expertise in AI specialization, including machine learning, deep learning, NLP, LLM applications, RAG with hands‑on experience in experimentation, model evaluation, and performance tuning.
• Demonstrated experience in designing and building scalable AI systems and architectures, including microservices-based solutions and distributed systems.
• Solid experience in data engineering for AI, including building ETL/ELT pipelines, data lakes/warehouses, and handling structured & unstructured data using tools like Spark, Kafka, Airflow, and SQL/NoSQL databases.
• Proficiency in programming languages such as Python, Go, Java, or Scala, and experience with AI/ML frameworks (TensorFlow, PyTorch, JAX, transformers, fine‑tuning LoRA, DPO, distillation, evaluation).
• Experience in AI experimentation & evaluation, including A/B testing, model benchmarking, validation techniques, and monitoring model performance in production.
• Working knowledge of AI Safety, Ethics & Responsible AI, Red‑team­ing, model risk management, alignment with SBV, MAS, Basel III, ensuring fairness, transparency, explainability, and compliance with regulatory requirements.
• Experience in MLOps/LLMOps practices (Level 2), including model deployment, CI/CD pipelines, versioning, and monitoring (Kubernetes, GPU orchestration, vector DBs, CI/CD for ML, drift and bias monitoring).
• Proven ability in business needs analysis, translating business problems into AI‑driven solutions and measurable outcomes.
• Experience managing stakeholders, collaborating with cross‑functional teams (business, risk, IT), and influencing decision‑making.
• Track record of delivering AI projects end‑to‑end using Agile methodologies, ensuring timelines, quality, and business impact.
• Exposure to emerging technologies and research trends in AI, with ability to evaluate and adopt new approaches when relevant.
• Basic experience or potential in AI strategy development and leadership, including mentoring junior team members and contributing to capability building.

Thông tin khác

• Location: Hà Nội, Vietnam
• No specified headcount; default 1