Website:
liquidity.io
Job details:
Liquidity.io | SecureGate.ai | Authenticated.ai
Location: India, Remote
About the Role
Liquidity.io, SecureGate AI, and Authenticated.ai are seeking a highly technical, hands-on Senior Engineer focused on AI infrastructure, DevOps, cloud architecture, and platform engineering across our fintech, identity, security, and AI platforms.
This role combines advanced software engineering, AI-native development, infrastructure automation, cloud operations, and production systems ownership. The ideal candidate is deeply experienced in building scalable cloud-native systems, deploying AI-enabled applications, operating secure production environments, and supporting highly available regulated infrastructure.
You will work closely with engineering leadership, product, security, compliance, and operations teams to design, build, deploy, and maintain reliable AI-driven systems operating in regulated financial and security environments.
ResponsibilitiesAI Engineering & Platform Development
- Design, develop, and deploy AI-enhanced applications, infrastructure, and automation systems.
- Implement AI-assisted engineering workflows using Claude, OpenAI APIs, Cursor, GitHub Copilot, and related technologies to improve development velocity and product quality.
- Build and maintain systems utilizing embeddings, vector databases, retrieval-augmented generation (RAG), prompt engineering, and agentic AI workflows.
- Develop scalable APIs, backend services, and cloud-native applications supporting fintech, identity, cybersecurity, and AI platforms.
- Optimize AI inference pipelines, GPU workloads, and model deployment infrastructure for production environments.
- Collaborate with product and engineering stakeholders to rapidly prototype and deploy AI-native product features.
DevOps, Cloud Infrastructure & Reliability
- Design and operate scalable cloud infrastructure on AWS, GCP, or Azure.
- Build and maintain CI/CD pipelines, Infrastructure-as-Code environments, and automated deployment systems using technologies such as Docker, Kubernetes, Terraform, GitHub Actions, and related tooling.
- Improve system reliability, observability, scalability, and operational efficiency through monitoring, automation, logging, alerting, and incident response practices.
- Support production operations, disaster recovery, platform uptime, and infrastructure security initiatives.
- Implement infrastructure automation and configuration management across distributed cloud environments.
- Troubleshoot complex production issues across infrastructure, networking, application, and AI systems.
Trading Systems & Regulated Infrastructure
- Support the development and operation of high-performance, highly available trading systems and infrastructure supporting alternative asset and ATS exchange operations.
- Assist in designing scalable, secure systems supporting broker-dealer operations, transfer agency platforms, digital assets, identity verification, and AI security products.
- Collaborate with compliance, legal, and security teams to support regulatory, audit, and cybersecurity requirements.
- Implement secure software development lifecycle (SSDLC) practices and operational controls appropriate for regulated financial systems.
Engineering Collaboration & Execution
- Collaborate with globally distributed engineering teams across the United States and India.
- Participate in architecture discussions, technical planning, code reviews, and engineering standards initiatives.
- Contribute to roadmap execution, technical documentation, operational procedures, and engineering best practices.
- Mentor junior engineers and contribute to a high-performance, collaborative engineering culture.
- Work cross-functionally with product, operations, compliance, and executive stakeholders to deliver production-ready systems and platform enhancements.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or related technical field, or equivalent practical experience.
- 10+ years of software engineering, DevOps, infrastructure, or platform engineering experience.
- Strong hands-on experience with AI/LLM technologies including OpenAI APIs, Claude, embeddings, vector databases, RAG systems, and AI agent frameworks.
- Extensive experience with cloud infrastructure and distributed systems on AWS, GCP, or Azure.
- Strong expertise with Docker, Kubernetes, Terraform, GitHub Actions, CI/CD pipelines, observability platforms, and Infrastructure-as-Code practices.
- Experience building and operating scalable backend systems, APIs, and production cloud services.
- Strong understanding of DevOps, system reliability, monitoring, logging, networking, and security best practices.
- Experience supporting production systems in regulated, high-security, or financial environments is strongly preferred.
- Familiarity with fintech infrastructure, trading systems, ATS platforms, digital assets, cybersecurity, identity platforms, or transfer agency systems is highly desirable.
- Experience working with globally distributed engineering teams in remote-first environments.
- Strong troubleshooting, debugging, problem-solving, and communication skills.
- Experience with GPU infrastructure, AI model deployment, inference optimization, or large-scale AI systems is a plus.
- Familiarity with Python, TypeScript, Go, or modern backend development stacks is preferred.
Benefits
- Competitive salary and equity compensation
- Comprehensive health, dental, and vision insurance
- Remote-first work environment
- Generous paid time off and vacation policy
- Opportunities for professional growth and technical leadership
- Dynamic, fast-paced, highly collaborative engineering culture
- Opportunity to help build next-generation AI, fintech, and security platforms
Join us in building scalable AI-native infrastructure and next-generation financial technology platforms operating at the intersection of fintech, security, and artificial intelligence. Because apparently the future now requires every engineer to simultaneously understand Kubernetes, GPUs, financial regulation, distributed systems, and prompt engineering while pretending burnout is a productivity framework.
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