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Job description
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
Your skills and experience
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
Why you'll love working here
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.
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