Sr/Expert AI Engineer Data Scientist, Python - 4B063

Top 3 Reasons To Join Us

The Job

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

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

Own the design and implementation of AI-driven productsCustomer 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

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

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

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

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.

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.

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.

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.