GenAI Platform Architect / Lead (Banking & Finance)

CodeAnalytiqa Consultancy and Services; Addison (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

CodeAnalytiqa Consultancy and Services seeks a GenAI Platform Architect/Lead with 10+ years of experience to design, secure, and scale our next-generation Financial AI platform. You will lead the architecture of production-grade systems powering Generative AI, LLMs, AI agents, and real-time data pipelines under strict financial regulatory standards.

Responsibilities include end-to-end AI platform design, multi-agent workflows, secure data streams, containerised microservices, and rigorous

Qualifications

• 10+ years in software, data, and ML engineering (Financial Services preferred).
• Design secure, compliant, scalable infrastructure for enterprise banking GenAI apps.
• Experience with Kubernetes, cloud platforms, and secure APIs.

Responsibilities

• Design end-to-end AI platform architecture supporting LLMs, models, and ML workflows.
• Build multi-agent orchestration and secure RAG systems for finance use cases.
• Establish high-throughput, low-latency data pipelines for financial data streams.
• Architect containerised microservices with zero-trust security and high availability.
• Implement governance, bias detection, explainability, cost optimization, and audits.

Skills

Generative AI & LLMs

AI Orchestration

Python

Kafka

Spark

Kubernetes

Cloud Platforms

APIs

Microservices

Tools

LangChain

LlamaIndex

CrewAI

Pinecone

Milvus

Qdrant

Job description

Job Description: GenAI Platform Architect / Lead (Banking & Finance)

We are seeking a GenAI Platform Architect/Lead with 10+ years of experience to design, secure, and scale our next-generation Financial AI platform. You will lead the architecture of production-grade systems powering Generative AI, Large Language Models (LLMs), AI agents, and real-time data pipelines under strict financial regulatory standards.

Position Overview

• Experience: 10+ years in software, data, and machine learning engineering (Financial Services preferred)
• Core Focus: Designing highly secure, compliant, and scalable infrastructure for enterprise banking GenAI applications

Key Responsibilities

• FinTech AI Architecture: Design end-to-end AI platform architecture supporting LLMs, quantitative models, and machine learning workflows.
• Agentic Financial Workflows: Build multi-agent orchestration frameworks and secure Retrieval-Augmented Generation (RAG) systems for market analysis, fraud detection, and customer operations.
• Real-time Data Streams: Establish high-throughput, low-latency data pipelines to ingest transaction records, market feeds, and unstructured financial documents.
• Compliant Infrastructure: Architect containerised microservices on Kubernetes ensuring zero-trust security, data privacy (PII masking), and high availability.
• AI Governance: Implement rigorous bias detection, explainability tools, cost optimization, and audit logging to comply with financial regulations.

Required Technical Skill Set

• Generative AI & LLMs: Advanced knowledge of fine-tuning financial LLMs (e.g., FinGPT), embedding models, and vector databases (e.g., Pinecone, Milvus, Qdrant).
• AI Orchestration: Hands-on experience building RAG pipelines and multi-functional AI Agents using frameworks like LangChain, LlamaIndex, or CrewAI.
• Programming: Expert-level Python skills for AI/ML development and enterprise backend integration.
• Financial Data Engineering: Proven experience handling large-scale financial data streams using Kafka and Spark.
• Core ML & Risk Modeling: Solid grounding in traditional Machine Learning (ML), MLOps pipelines, and model risk management (MRM) frameworks.
• Cloud & DevOps: Strong Kubernetes (K8s) orchestration expertise coupled with Enterprise Cloud platforms (AWS, Azure, or GCP).
• Backend Systems: Deep understanding of secure APIs (REST, gRPC) and Microservices architecture.

Industry-Specific Competencies

• Knowledge of financial regulatory compliances (e.g., SEC, FINRA, GDPR, PCI-DSS, EU AI Act).
• Experience with secure data handling, data sovereignty, and encryption at rest and in transit.