{"id":1318364,"url":"https://alion.io/job/techcombank-expert-ai-engineering","title":"Expert, AI Engineering","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":19500,"max_usd":49000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1507},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","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":"CI/CD","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":"2026-09-14T00:00:00Z","employer_posted_date":"2026-09-14","last_verified_at":"2026-09-28T21:13:19Z","board_verified":true,"closed_at":null,"days_open":15,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":15},"description":"Job Purpose\n- Lead the design and delivery of advanced AI solutions, ensuring high performance, scalability, and cost efficiency in production environments.\n- Solve complex AI challenges (modeling, evaluation, multi-agent systems) and develop reusable frameworks and standards adopted across teams.\n- Ensure AI systems are developed and operated responsibly, addressing safety, ethical risks, and governance requirements.\nKey Accountabilities (1)\nAI Craft - Specialization\n- Evaluate novel algorithms and training techniques against production constraints; diagnose and unblock the hardest cross-cutting Modeling problems (severe distribution shift, low-resource settings, multi-task architecture); build reusable Modeling patterns adopted across teams.\n- Implement complex multi-agent orchestration, long-running stateful workflows, and quality optimisation at scale; evaluate new models and frameworks hands-on; build reusable agent patterns and prompt libraries adopted across teams.\n- Evaluates and adopts advanced optimisation techniques; designs multi-tenant serving and capacity strategies; builds performance-regression frameworks and cost dashboards adopted across teams.\n- Recognised expert in the sub-domain inside the org; selects between competing approaches based on production constraints; reviews and unblocks others' sub-domain work; tackles the harder problems (low-resource scenarios, distribution shift, real-time constraints); the person teams escalate to.\nAI Craft - Evaluation\n- Build evaluation tooling and automated experiment pipelines adopted across teams\n- Design and run online A/B tests with statistical rigour & calibrate human and LLM-judge evaluation\n- Resolve the hardest evaluation problems (subjective tasks, rare-event detection, long-tail safety).\nKey Accountabilities (2)\nEngineering for Production\n- Design testing strategies for AI systems (data validation, model regression, prompt-output, agent-trajectory tests); evaluate and introduce new tooling; build internal libraries, SDKs, and code templates that raise the engineering floor across teams.\n- Architect data platforms that serve both ML training and LLM/RAG workloads; design for cost, latency, and freshness trade-offs; build reusable data-quality, lineage, and observability tooling adopted across teams.\n- Architect complex AI systems combining ML and agentic components; design for graceful degradation, cost-efficiency, evolvability, and multi-tenancy; build reference implementations and integration patterns adopted by other teams; lead migration and convergence of inherited or siloed systems where warranted; balance near-term delivery against long-term architectural coherence.\nKey Accountabilities (3)\nResearch & Emerging Technologies & AI Safety, Ethics & Responsible AI\n- Conduct in-depth evaluation of emerging AI technologies within the assigned domain/project; build prototypes to validate feasibility and risks; provide recommendations for appropriate implementation approaches for specific use cases.\n- Contribute to the development and refinement of responsible AI standards within the domain; ensure solutions comply with established guidelines and regulations.\n- Analyse ethical and safety risks of AI systems at solution/project level; propose appropriate risk mitigation measures.\n- Participate in designing and executing testing activities (e.g., adversarial testing, risk assessments) to improve system robustness and reliability.\n- Support AI risk assessments in product reviews, acting as a technical advisor within the domain.\nKey Relationships - Direct Manager\nSenior Manager/ Director/ Head, AI Engineering\nKey Relationships - Direct Reports\nKey Relationships - Internal Stakeholders\nBusiness Tribe, Enabling Tribe (IT or Data - Engineer/Governance), division heads (Business, Finance, Risk, Corporate Affairs, IT), CEO, CIO, CDAO, Chief AI Transformation Officer, Chairman\nKey Relationships - External Stakeholders\nExternal stakeholders include vendors and partners providing professional services\nSuccess Profile - Qualification and Experiences\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- 8+ 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":6714,"description_truncated":false,"requirements":{"experience_years_min":8,"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":77,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.853,"p_room":0.9,"age_days":14,"expected_fill_days":31,"reasons":["conf:14","velocity","win:mid"],"computed_at":"2026-09-28T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/techcombank-expert-ai-engineering","json_url":"https://alion.io/job/techcombank-expert-ai-engineering.json","meta":{"generated_at":"2026-09-29T02:17:47Z","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":1945,"day_limit":5000,"remaining_today":3055,"minute_limit":60,"resets_at":"2026-09-30T00:00:00Z"}}}