Senior Backend Engineer

DeepSee-posted 9 days ago

Full-time • Senior

Remote • Draper, UT

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DeepSee delivers an open and flexible agentic platform to accelerate AI adoption for financial services in front, middle, and back-office operations. Our cloud-based platform seamlessly integrates with existing bank architectures, whether they’re just starting their AI transformation journey or looking to enhance existing in-house capabilities with Agentic AI solutions. With DeepSee’s pre-trained & pre-configured agents, banking and capital markets firms can automate and orchestrate manual, repetitive tasks—freeing domain experts for strategic work, reducing risk, and streamlining operations to drive greater efficiency. We are looking for an experienced and forward-thinking Sr. Backend Engineer to to architect and build high-performance, scalable backend services as part of a best-in-class engineering organization. The role is ideal for someone who thrives in a polygot environment (Java & Python), can tackle complex performance challenges, and is working with and excited about cutting-edge AI technologies.

Backend Architecture & Performance Design and implement scalable microservices using Java (Spring Boot) and Python (FastAPI) in a modern cloud-native architecture
Optimize high-throughput data processing pipelines handling large volumes of emails and documents
Identify and resolve performance bottlenecks in CPU-intensive document extraction and processing workflows
Database & Data Engineering Design complex PostgreSQL queries and optimize database performance through strategic indexing and query refactoring
Work with both relational (PostgreSQL) and NoSQL (e.g., MongoDB) databases to ensure efficient data persistence
Implement robust data pipelines with event-driven architecture using Kafka
Eliminate N+1 query patterns and implement efficient data access patterns
AI & Intelligent Automation Build and deploy production-ready agentic AI systems using frameworks (e.g., Semantic Kernel, LangChain, LangGraph, agent-framework, and SDKs)
Integrate Azure OpenAI, Azure Foundry and other LLM services into backend processing workflows
Implement guardrails, tracing, monitoring, and human-in-the-loop systems for AI agent operations
Design intelligent document extraction and classification systems to enhance automation
Use transfer learning, model distillation, and ensemble model techniques to create fit-for-purpose models that are highly performant and accurate
System Reliability & Observability Implement comprehensive monitoring, logging, and alerting using Prometheus, Grafana, and distributed tracing tools
Establish SLO/SLI metrics and performance dashboards for production systems
Design fault-tolerant systems with proper error handling, retry logic, and circuit breakers
Write thorough unit, integration, and smoke tests using JUnit, Mockito, Pytest, and Playwright
Collaboration & Technical Leadership Work closely with Product and Engineering teams to translate requirements into technical solutions
Conduct code reviews and mentor team members on best practices
Document architectural decisions (ADRs) and create operational runbooks
Deep dive technically while also operating at the strategic, organizational level

5+ years of backend development experience with strong fundamentals in distributed systems and microservices architecture
Strong proficiency in Python 3.10+ including asynchronous programming, FastAPI, and async/await patterns
Solid Java experience (Java 17+) with Spring Boot, Spring Data JPA, and RESTful API development
Expert-level SQL skills with PostgreSQL, including complex query optimization and index design
Event-driven architecture experience with Kafka or similar message queue systems
Testing expertise with JUnit, Mockito, and Pytest for comprehensive test coverage
Production experience building and deploying agentic AI systems (LangChain, LangGraph, agent-framework, or similar)
Strong understanding of LLM integration patterns, prompt engineering, and AI observability/tracing
Experience with Docker containerization and cloud platforms (AWS/Azure)
Proficiency with modern development tools: Git, uv, Gradle, pre-commit hooks, linting/formatting automation
Comfortable with ambiguity and rapid change in a fast-paced startup environment
Strong problem-solving skills with ability to diagnose and resolve complex performance issues
Ownership mentality—responsible for the reliability of systems you build, including on-call participation
Ability to leverage AI tools (GitHub Copilot, Claude, ChatGPT) to augment productivity

Experience with MapStruct for Java bean mapping and Tortoise ORM for async Python persistence
Document processing libraries: Apache Tika, PDFBox, Apache POI for PDF, Excel, and email parsing
Microsoft Graph API integration, especially for Outlook/email automation
Knowledge graph design and development using open-source tools
OpenAPI/Swagger for API documentation and contract-first development
Feature flag systems for progressive rollouts and A/B testing
Rust toolchain familiarity or HTTPX for high-performance HTTP operations
Experience in financial services, banking, or capital markets with understanding of regulatory requirements (SOC2, ISO27001)
Domain-Driven Design (DDD) principles and implementation patterns
Background in ETL pipelines and data-intensive applications
Exposure to Azure AI Foundry, Microsoft 365 Agents SDK, or Copilot integration
Understanding of MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication patterns
Experience-driven empathy for engineering pain points—you've felt the frustration of poorly architected systems and know how to fix them
A voracious and intrinsic desire to learn and fill in missing skills—and an equally strong talent for sharing learnings clearly and concisely with others
Track record of successfully refactoring legacy codebases while maintaining system stability

Competitive compensation package including equity, with remote work options
100% company-paid premiums on health, dental, and vision insurance
Opportunity to work on cutting-edge AI technology with real impact
Collaborative and innovative work environment

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