{"id":1318399,"url":"https://alion.io/job/techcombank-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":2469027,"name":"Techcombank","domain":"techcombank.com","url":"https://alion.io/company/techcombank-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hanoi, Vietnam"],"countries":["VN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19000,"max_usd":48000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1507},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"RAG","optional":false},{"name":"Agile","optional":true},{"name":"Apache Kafka","optional":true},{"name":"DPO","optional":true},{"name":"ETL/ELT","optional":true},{"name":"Fine-tuning","optional":true},{"name":"Java","optional":true},{"name":"JAX","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLMOps","optional":true},{"name":"LoRA","optional":true},{"name":"Model Distillation","optional":true},{"name":"NLP","optional":true},{"name":"PEFT","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Scala","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-09-03T00:00:00Z","employer_posted_date":"2026-09-03","last_verified_at":"2026-09-30T22:46:02Z","board_verified":true,"closed_at":null,"days_open":28,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":28},"description":"KEY ACCOUNTABILITIES (maximum 3 sections and 2000 words for each section)\nKey Accountabilities (1)\nAI Craft - Specialization\n- Apply and evaluate established and emerging algorithms under production constraints; resolve complex modeling issues within project scope (e.g. data quality gaps, moderate distribution shift, performance trade-offs), while escalating highly ambiguous or cross-system problems.\n- Implement and operate multi-agent workflows and stateful pipelines for defined use cases; experiment with models/frameworks hands-on and extend existing agent patterns and prompt libraries where applicable.\n- Apply optimisation techniques (latency, cost, quality) using existing approaches; monitor system performance and contribute to tuning and capacity decisions within the team.\n- Demonstrate solid domain expertise and continue developing advanced skills; support team members through technical execution and knowledge sharing; participate in reviews and follow established engineering practices\nAI Craft - Evaluation\n- Design and execute evaluation setups for features/systems using predefined approaches (holdout sets, offline metrics, structured human or LLM-based review loops).\n- Analyse results, identify issues, and propose improvements to models or prompts.\n- Support controlled experiments (e.g. basic A/B tests, shadow testing) under guidance; ensure adherence to evaluation standards and processes.\nKey Accountabilities (2)\nEngineering for Production\n- Apply and contribute to testing strategies for AI systems (data validation, model regression, prompt-output checks, basic agent testing), leveraging existing tools and frameworks.\n- Implement and maintain components of data platforms supporting ML and LLM/RAG workloads; consider cost, latency, and freshness trade-offs within assigned scope.\n- Design and build end-to-end AI solutions for specific use cases, including data flow, serving, caching, fallback, and monitoring; ensure compatibility with existing systems and APIs following defined standards.\n- Operate within established CI/CD and operational processes (deployment, drift monitoring, incident handling); participate in incident response and continuous improvement activities.\n- Assist in refining internal tools, guidelines, and processes to improve team efficiency and engineering quality.\"\nKey Accountabilities (3)\n\"Research & Emerging Technologies & AI Safety, Ethics & Responsible AI\n- Apply and evaluate emerging AI technologies and approaches in designing and implementing solutions for specific projects/use cases.\n- Apply responsible AI standards and ensure compliance with safety, ethical, and regulatory guidelines.\n- Perform basic risk analysis within project scope; propose and implement mitigation measures.\n- Conduct system testing and evaluation (e.g., stability, reliability); support risk assessment activities.\n- Provide support in mentoring other engineers on best practices.\nQualifications\n- Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related quantitative field\n- Strong foundation in mathematics, statistics, and machine learning principles\n- Relevant certifications in AI/ML, Cloud (Azure, AWS, GCP), or Data Engineering are a plus\n- English proficiency in line with Techcombank’s policy\nWork Experience\n- 5+ years of experience in AI/ML, data engineering, and software development, with proven delivery of end-to-end AI solutions in production environments\n- Strong expertise in AI specialization, including machine learning, deep learning, NLP, and LLM applications, RAG with hands-on experience in experimentation, model evaluation, and performance tuning\n- Demonstrated experience in designing and building scalable AI systems and architectures, including microservices-based solutions and distributed systems\n- 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\n- Proficiency in programming languages such as Python, Go, Java, or Scala, and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, / JAX, transformers, fine-tuning (LoRA, DPO), distillation, evaluation.)\n- Experience in AI experimentation & evaluation, including A/B testing, model benchmarking, validation techniques, and monitoring model performance in production\n- 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\n- Experience in MLOps/LLMOps practices (Level 2), including model deployment, CI/CD pipelines, versioning, and monitoring (e.g., Kubernetes, GPU orchestration, vector DBs, CI/CD for ML, drift and bias monitoring.)\n- Proven ability in business needs analysis, translating business problems into AI-driven solutions and measurable outcomes\n- Experience managing stakeholders, collaborating with cross-functional teams (business, risk, IT), and influencing decision-making\n- Track record of delivering AI projects end-to-end using Agile methodologies, ensuring timelines, quality, and business impact\n- Exposure to emerging technologies and research trends in AI, with the ability to evaluate and adopt new approaches when relevant\n- Basic experience or potential in AI strategy development and leadership, including mentoring junior team members and contributing to capability building","description_format":"text","description_chars":5571,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"Advanced (C1)","optional":false}]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-26T20:13:10Z"}],"liveness":{"score":39,"band":"fade","label":"Fading","p_open":1,"p_active":0.702,"p_room":0.55,"age_days":28,"expected_fill_days":21,"reasons":["conf:6","velocity","win:tail"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/techcombank-senior-ai-engineer","json_url":"https://alion.io/job/techcombank-senior-ai-engineer.json","meta":{"generated_at":"2026-10-01T11:01:17Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2332,"day_limit":5000,"remaining_today":2668,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}