Sr/Expert AI Engineer (Data Scientist, Python) - 4B063
TNEX
Mô tả công việc
We are building customer-facing and internal AI products that directly impact growth, risk, operations, and customer experience in a regulated fintech environment. As a Senior / Expert AI Platform Engineer, you will lead the delivery of LLM-powered products such as chatbots, voicebots, and analytics co-pilots, while ensuring they are production-grade, compliant, and measurable. This is a product-heavy role: success is defined by business outcomes, not just infrastructure. You will work end-to-end across data → model → product → monitoring, partnering closely with Product, Risk, Compliance, and Engineering teams. What Youʼll Build: Customer-facing AI used by millions of users, AI assistants embedded in critical fintech workflows, A trusted, compliant AI platform adopted across the company, Measurable business impact across growth, cost, and risk Why Join Us: Build real AI products, not demos, Direct ownership of business-critical systems, Strong executive sponsorship for AI & GenAI, Modern stack: AWS Bedrock, dbt, Airflow, MLflow, High trust, high impact, expert-level autonomy Main Responsibilities include: 1. AI Products & Customer Journeys Own the design and implementation of AI-driven products Customer service chatbots & voicebots Internal analytics & decisioning co-pilots AI assistants for operations, sales, and risk teams Translate business problems (conversion, cost-to-serve, fraud, credit decisioning, CX) into AI solutions Design LLM workflows using RAG, agents, tools, and structured reasoning Integrate models via AWS Bedrock with strict controls on latency, cost, and reliability 2. Fintech-Grade AI & ML Platform Build and evolve a shared AI & ML platform supporting: Predictive ML (risk, fraud, personalization) LLM & GenAI workloads Productionize models with strong MLOps practices: Experiment tracking & model registry (MLflow) CI/CD for models, prompts, and agents Orchestrate data & ML pipelines using Airflow Enable analytics, features, and training datasets using dbt Support both real-time inference and batch decisioning 3. Risk, Governance & Compliance (Critical) Design AI systems aligned with fintech governance requirements: Model versioning, traceability, and auditability Explainability and decision logging where required Implement guardrails for: Hallucination control & safe completion Data privacy & PII protection Model misuse and prompt injection Partner with Risk, Compliance, and Legal to enable safe GenAI adoption Support internal reviews, validations, and regulator-ready documentation 4. Monitoring, Quality & Continuous Improvement Define and operate AI observability: Model & prompt performance Drift, bias, and degradation Latency & cost efficiency Build feedback loops from users, agents, and business teams Continuously improve prompts, models, and product experience
Yêu cầu công việc
Strong Python engineering skills Proven experience delivering AI/ML systems in production Hands-on experience with LLMs & GenAI (RAG, embeddings, evaluation) Experience using AWS Bedrock in real products Solid MLOps experience with MLflow Workflow orchestration with Airflow Experience with dbt and modern analytics/data stacks Strong product mindset: ability to connect AI outputs to business outcomes Expert-Level Expectations Act as a technical authority for AI products and platforms Make architecture and design decisions with long-term scalability in mind Mentor senior engineers and influence AI best practices across teams Proactively identify high-impact AI use cases in fintech Balance innovation with risk, compliance, and operational stability Nice to Have Experience in fintech, banking, or regulated industries Voicebot systems (STT/TTS, real-time streaming) Feature store or online decisioning systems Kubernetes or large-scale inference platforms Experience working with regulators, audits, or model risk teams
Quyền lợi
1. Attractive Compensation and Rewards Competitive salary benchmarked against the market and aligned with your capabilities. The final salary package will be negotiated upon successfully passing the interview process. Year-end performance bonus ranging from 2 to 5 months' average salary, depending on individual performance evaluation results. 2. Comprehensive Benefits Package Statutory insurance coverage and additional private health insurance for employees. Diverse employee benefits, including flexible working hours, company trips, birthday leave, and more. Access to employee loan programs with preferential interest rates. 3. Learning, Development, and Career Advancement Structured and in-depth training programs focused on Re-skilling, Up-skilling, and New-skilling, tailored to specific job groups and career paths. Close mentoring and coaching from direct managers, senior leaders, and industry experts. Management development programs for high-potential employees, preparing them for future leadership and managerial roles. Priority is given to promoting internal talent into management positions, providing clear career progression opportunities. 4. Professional Work Environment and Dynamic Corporate Culture Friendly, supportive, and collaborative workplace that values accountability and mutual respect. Innovative and dynamic environment that encourages creativity, continuous learning, and improvement. Respect for diversity, with a strong emphasis on teamwork and effective collaboration. A wide range of cultural, sports, and recreational activities that foster employee engagement and a positive workplace atmosphere.