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
• 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 MLflowWorkflow 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
BENEFITS OF JOINING TNEX FINANCE
1. Attractive Compensation and Rewards
2. Comprehensive Benefits Package
3. Learning, Development, and Career Advancement
4. Professional Work Environment and Dynamic Corporate Culture
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