Senior Backend Engineer

Overview

Job Summary

Key Responsibilities

• Design and architect the orchestration layer for AI agents (Agent of Agents framework), coordinating specialized AI workers such as Controllership Agent and Treasury Agent, while managing state, task routing, and error handling.
• Develop the Task Router & Intent Classifier services to map user prompts to specific skills or playbooks, ensuring deterministic execution for critical financial and engineering workflows.
• Build scalable, containerized microservices optimized for high-concurrency requests within the LeverEDGE platform, delivering low-latency responses for real-time market intelligence and design trade-off analysis.
• Construct a secure Data Access Layer (DAL) for SAP S/4HANA and Ariba connectivity, enforcing strict validation logic before any transaction is committed to ensure data integrity and security.
• Engineer a scalable, secure, and observable connection layer for the central data lakehouse platform, ensuring all read transactions are authenticated, authorized, and audited.
• Implement backend logic to interface with Vector Databases (e.g., Weaviate) and Retrieval-Augmented Generation (RAG) models, enabling the Knowledge Mining Chatbot to securely query historical proposals and technical documents.
• Develop robust external API connectors for data feeds (e.g., S&P Global, Orbis) to power Supply Chain Risk Scoring engines and LeverEDGE component comparative analysis, with handling for rate limiting, caching, and data normalization.
• Design and deploy defense-grade security services, including Gateway & Policy Guard, to enforce Authentication, Role-Based Access Control (RBAC), and redaction of Personally Identifiable Information (PII) and International Traffic in Arms Regulations (ITAR) data before it reaches Large Language Models (LLMs).
• Optimize systems for strictly air-gapped or on-premise deployment, ensuring efficient resource usage on local GPU clusters rather than relying on cloud scaling.
• Implement comprehensive reliability engineering practices, including logging, tracing, monitoring, and observability mechanisms, adhering to EDGE Group policies and enterprise best practices for high availability and auditability.

Required Qualifications

• 5+ years of experience in Backend Engineering with a focus on building distributed systems or platforms that serve ML/AI models in production environments.
• Expert proficiency in Python (FastAPI/Django) for AI integration and strong experience with Go or Java for high-performance microservices development.
• Deep experience with Docker and Kubernetes (k8s) for deploying scalable applications in on-premise environments.
• Strong background in designing RESTful APIs and gRPC services, with experience building API Gateways (e.g., Kong, NGINX) for traffic management and security.
• Proficiency with Relational Databases (PostgreSQL) for transactional data and Vector Databases (Weaviate, Milvus) for semantic search applications.
• Familiarity with enterprise integration patterns and ERP protocols (OData, SOAP) is a strong plus.
• Ability to thrive in a structured 'Governance Collision' environment, delivering Agile software (Sprints, MVPs) that passes rigorous 'Stage Gate' reviews and Systems Engineering audits.
• Experience building systems requiring high availability, auditability, and defense-grade security, preferably in Fintech, Healthcare, or Defense sectors.
• Proven track record of collaborating with Data Scientists to productize models and working with Frontend Engineers to deliver seamless user experiences.
• Experience implementing comprehensive logging, tracing, monitoring, and observability mechanisms adhering to enterprise best practices.

Technical Skills

• Expert proficiency in Python (FastAPI/Django) for AI integration and backend development, with strong experience in building scalable microservices using Go or Java for high-performance applications.
• Deep expertise in containerization and orchestration with Docker and Kubernetes (k8s), including deployment and management of scalable applications in on-premise environments.
• Strong background in designing and implementing RESTful APIs and gRPC services, with hands-on experience building and securing API gateways (e.g., Kong, NGINX) for traffic management and authentication.
• Proven proficiency in relational databases such as PostgreSQL for transactional data management, alongside experience with vector databases (Weaviate, Milvus) for semantic search and retrieval-augmented generation (RAG) applications.
• Familiarity with enterprise integration patterns and ERP protocols, including OData and SOAP, to facilitate secure and scalable connectivity with systems like SAP S/4HANA and Ariba.
• Experience implementing defense-grade security measures, including authentication, role-based access control (RBAC), and data redaction for personally identifiable information (PII) and International Traffic in Arms Regulations (ITAR)-sensitive data.
• Knowledge of scalable data lakehouse architectures and secure, observable connection layers for centralized data platforms, ensuring authenticated, authorized, and audited transactions.
• Strong foundation in reliability engineering, including comprehensive logging, tracing, monitoring, and observability mechanisms adhering to enterprise best practices for high-availability systems.
• Experience optimizing systems for air-gapped or on-premise deployment, with an emphasis on efficient resource utilization on local GPU clusters rather than cloud-based scaling.

Company And Project Focus

Location

Company Overview

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