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We are looking for a Senior Full Stack Engineer who thrives at the intersection of intelligent systems and polished product experiences. You'll work across the entire stack from designing React interfaces that surface AI capabilities to engineers and end users, to building the Python and Node.js services that power our LLM-based Agentic platform. A key part of this role is hands-on experience with designing, building, and integrating MCP servers that connect our AI agents to internal tools, financial data systems, and third-party APIs. You'll collaborate closely with product, compliance, and cross-functional engineering teams to build financial technology that's fast, secure, and genuinely intelligent.
Who You Are:
You have experience building Retrieval‑Augmented Generation (RAG) systems or knowledge‑base chatbots.
You're Hands‑on with vector databases such as Pinecone, Chroma, or pgvector on Postgres/Aurora.
Have AWS certification (Developer, Solutions Architect, or Machine Learning Specialty).
Experience with observability tooling (Datadog, New Relic) and cost‑optimization strategies for AI workloads.
Background in microservices, domain‑driven design, or event‑sourcing patterns.
What Youll Actually Be Doing:
Design, build, and continuously improve our LLM-based Agentic platform. Own end-to-end architecture decisions from model orchestration and prompt design to retrieval pipelines, tool-calling patterns, and evaluation frameworks.
Architect and build high-performance services in Python and/or Node.js. Design systems for extreme speed, reliability, and real-time data processing under high traffic conditions.
Design and maintain MCP servers that give AI agents structured, secure access to internal banking systems, external APIs, databases, and developer tools making Agentic platform composable and extensible by design.
Build intuitive React interfaces that expose AI capabilities like chat interfaces, agentic dashboards, real-time streaming UIs, and internal tooling. Own state management patterns and component architecture at scale.
Partner with product managers, business stakeholders, compliance, and engineering teams to translate vision into scalable technical requirements and roadmaps.
Design and ensure the platform meets enterprise-grade security and financial regulatory standards.
Actively upskill fellow engineers on full-stack best practices, LLM integration patterns, and production of AI systems. Help define coding standards and contribute to a culture of engineering excellence.
Evaluate emerging models, frameworks, and tooling. Prototype and integrate the most impactful advances into our platform and internal developer productivity tooling.
Requirements

Were looking for a hands-on Data Platform Team Lead to guide a high-performing team in designing, scaling, and operating the infrastructure that powers Chargeflows platform.

This role combines architectural leadership with people management. Youll define the technical direction for our data platform while developing engineers, strengthening execution, and building a culture of ownership and technical excellence.

Youll be responsible for the reliability, performance, security, and cost efficiency of data systems supporting millions of daily transactions and critical product, machine-learning, and analytics use cases. This is a role for someone who can move comfortably between long-term architecture, hands-on technical problem-solving, and day-to-day team leadership.

The impact youll have

Build and evolve the data infrastructure that safeguards our clients revenue and powers critical product, ML, and analytics use cases.
Establish scalable engineering standards and operational practices (reliability, security, governance, and cost efficiency).
Lead and grow a team of data/infrastructure engineers while cultivating technical excellence and psychological safety.

What youll own (Your arena)
Leadership & Mentorship: Lead, mentor, and scale a team of talented data and infrastructure engineers.
Create strong execution rituals: clear ownership, high-quality delivery, feedback loops, and growth plans.
Data Infrastructure & FinOps: Own the architecture and evolution of our modern data stack and platform services.
Drive cloud cost management (FinOps): cost visibility, optimization initiatives, and capacity planning.
High-Performance Engineering: Oversee the design of distributed systems, real-time streaming, and batch pipelines capable of processing millions of daily transactions with minimal latency.
Define technical direction for storage, compute, and data movement patterns (event-driven + lakehouse).
Operational Excellence Champion Infrastructure-as-Code (IaC), CI/CD, and testing practices for infrastructure and data systems.
Establish observability standards (monitoring/alerting, SLOs, incident response, postmortems).
Partner on security compliance and data governance across the R&D organization.
Strategic Collaboration: Act as the bridge between data engineering, product, data science, and core R&D teams to execute cross-functional initiatives.
Translate business goals into platform roadmaps, milestones, and measurable outcomes.